Functional insights from proteome-wide structural modeling of Treponema pallidum subspecies pallidum, the causative agent of syphilis.

PubMed

Houston, Simon; Lithgow, Karen Vivien; Osbak, Kara Krista; Kenyon, Chris Richard; Cameron, Caroline E

2018-05-16

Syphilis continues to be a major global health threat with 11 million new infections each year, and a global burden of 36 million cases. The causative agent of syphilis, Treponema pallidum subspecies pallidum, is a highly virulent bacterium, however the molecular mechanisms underlying T. pallidum pathogenesis remain to be definitively identified. This is due to the fact that T. pallidum is currently uncultivatable, inherently fragile and thus difficult to work with, and phylogenetically distinct with no conventional virulence factor homologs found in other pathogens. In fact, approximately 30% of its predicted protein-coding genes have no known orthologs or assigned functions. Here we employed a structural bioinformatics approach using Phyre2-based tertiary structure modeling to improve our understanding of T. pallidum protein function on a proteome-wide scale. Phyre2-based tertiary structure modeling generated high-confidence predictions for 80% of the T. pallidum proteome (780/978 predicted proteins). Tertiary structure modeling also inferred the same function as primary structure-based annotations from genome sequencing pipelines for 525/605 proteins (87%), which represents 54% (525/978) of all T. pallidum proteins. Of the 175 T. pallidum proteins modeled with high confidence that were not assigned functions in the previously annotated published proteome, 167 (95%) were able to be assigned predicted functions. Twenty-one of the 175 hypothetical proteins modeled with high confidence were also predicted to exhibit significant structural similarity with proteins experimentally confirmed to be required for virulence in other pathogens. Phyre2-based structural modeling is a powerful bioinformatics tool that has provided insight into the potential structure and function of the majority of T. pallidum proteins and helped validate the primary structure-based annotation of more than 50% of all T. pallidum proteins with high confidence. This work represents the first T. pallidum proteome-wide structural modeling study and is one of few studies to apply this approach for the functional annotation of a whole proteome.

Nitrate removal in stream ecosystems measured by 15N addition experiments: Total uptake

USGS Publications Warehouse

Hall, R.O.; Tank, J.L.; Sobota, D.J.; Mulholland, P.J.; O'Brien, J. M.; Dodds, W.K.; Webster, J.R.; Valett, H.M.; Poole, G.C.; Peterson, B.J.; Meyer, J.L.; McDowell, W.H.; Johnson, S.L.; Hamilton, S.K.; Grimm, N. B.; Gregory, S.V.; Dahm, Clifford N.; Cooper, L.W.; Ashkenas, L.R.; Thomas, S.M.; Sheibley, R.W.; Potter, J.D.; Niederlehner, B.R.; Johnson, L.T.; Helton, A.M.; Crenshaw, C.M.; Burgin, A.J.; Bernot, M.J.; Beaulieu, J.J.; Arangob, C.P.

2009-01-01

We measured uptake length of 15NO-3 in 72 streams in eight regions across the United States and Puerto Rico to develop quantitative predictive models on controls of NO-3 uptake length. As part of the Lotic Intersite Nitrogen eXperiment II project, we chose nine streams in each region corresponding to natural (reference), suburban-urban, and agricultural land uses. Study streams spanned a range of human land use to maximize variation in NO-3 concentration, geomorphology, and metabolism. We tested a causal model predicting controls on NO-3 uptake length using structural equation modeling. The model included concomitant measurements of ecosystem metabolism, hydraulic parameters, and nitrogen concentration. We compared this structural equation model to multiple regression models which included additional biotic, catchment, and riparian variables. The structural equation model explained 79% of the variation in log uptake length (S Wtot). Uptake length increased with specific discharge (Q/w) and increasing NO-3 concentrations, showing a loss in removal efficiency in streams with high NO-3 concentration. Uptake lengths shortened with increasing gross primary production, suggesting autotrophic assimilation dominated NO-3 removal. The fraction of catchment area as agriculture and suburban-urban land use weakly predicted NO-3 uptake in bivariate regression, and did improve prediction in a set of multiple regression models. Adding land use to the structural equation model showed that land use indirectly affected NO-3 uptake lengths via directly increasing both gross primary production and NO-3 concentration. Gross primary production shortened SWtot, while increasing NO-3 lengthened SWtot resulting in no net effect of land use on NO- 3 removal. ?? 2009.

Statistical analysis of modeling error in structural dynamic systems

NASA Technical Reports Server (NTRS)

Hasselman, T. K.; Chrostowski, J. D.

1990-01-01

The paper presents a generic statistical model of the (total) modeling error for conventional space structures in their launch configuration. Modeling error is defined as the difference between analytical prediction and experimental measurement. It is represented by the differences between predicted and measured real eigenvalues and eigenvectors. Comparisons are made between pre-test and post-test models. Total modeling error is then subdivided into measurement error, experimental error and 'pure' modeling error, and comparisons made between measurement error and total modeling error. The generic statistical model presented in this paper is based on the first four global (primary structure) modes of four different structures belonging to the generic category of Conventional Space Structures (specifically excluding large truss-type space structures). As such, it may be used to evaluate the uncertainty of predicted mode shapes and frequencies, sinusoidal response, or the transient response of other structures belonging to the same generic category.

Model updating strategy for structures with localised nonlinearities using frequency response measurements

NASA Astrophysics Data System (ADS)

Wang, Xing; Hill, Thomas L.; Neild, Simon A.; Shaw, Alexander D.; Haddad Khodaparast, Hamed; Friswell, Michael I.

2018-02-01

This paper proposes a model updating strategy for localised nonlinear structures. It utilises an initial finite-element (FE) model of the structure and primary harmonic response data taken from low and high amplitude excitations. The underlying linear part of the FE model is first updated using low-amplitude test data with established techniques. Then, using this linear FE model, the nonlinear elements are localised, characterised, and quantified with primary harmonic response data measured under stepped-sine or swept-sine excitations. Finally, the resulting model is validated by comparing the analytical predictions with both the measured responses used in the updating and with additional test data. The proposed strategy is applied to a clamped beam with a nonlinear mechanism and good agreements between the analytical predictions and measured responses are achieved. Discussions on issues of damping estimation and dealing with data from amplitude-varying force input in the updating process are also provided.

Warming and Resource Availability Shift Food Web Structure and Metabolism

PubMed Central

O'Connor, Mary I.; Piehler, Michael F.; Leech, Dina M.; Anton, Andrea; Bruno, John F.

2009-01-01

Climate change disrupts ecological systems in many ways. Many documented responses depend on species' life histories, contributing to the view that climate change effects are important but difficult to characterize generally. However, systematic variation in metabolic effects of temperature across trophic levels suggests that warming may lead to predictable shifts in food web structure and productivity. We experimentally tested the effects of warming on food web structure and productivity under two resource supply scenarios. Consistent with predictions based on universal metabolic responses to temperature, we found that warming strengthened consumer control of primary production when resources were augmented. Warming shifted food web structure and reduced total biomass despite increases in primary productivity in a marine food web. In contrast, at lower resource levels, food web production was constrained at all temperatures. These results demonstrate that small temperature changes could dramatically shift food web dynamics and provide a general, species-independent mechanism for ecological response to environmental temperature change. PMID:19707271

Test plan. GCPS task 7, subtask 7.1: IHM development

NASA Technical Reports Server (NTRS)

Greenberg, H. S.

1994-01-01

The overall objective of Task 7 is to identify cost-effective life cycle integrated health management (IHM) approaches for a reusable launch vehicle's primary structure. Acceptable IHM approaches must: eliminate and accommodate faults through robust designs, identify optimum inspection/maintenance periods, automate ground and on-board test and check-out, and accommodate and detect structural faults by providing wide and localized area sensor and test coverage as required. These requirements are elements of our targeted primary structure low cost operations approach using airline-like maintenance by exception philosophies. This development plan will follow an evolutionary path paving the way to the ultimate development of flight-quality production, operations, and vehicle systems. This effort will be focused on maturing the recommended sensor technologies required for localized and wide area health monitoring to a technology readiness level (TRL) of 6 and to establish flight ready system design requirements. The following is a brief list of IHM program objectives: design out faults by analyzing material properties, structural geometry, and load and environment variables and identify failure modes and damage tolerance requirements; design in system robustness while meeting performance objectives (weight limitations) of the reusable launch vehicle primary structure; establish structural integrity margins to preclude the need for test and checkout and predict optimum inspection/maintenance periods through life prediction analysis; identify optimum fault protection system concept definitions combining system robustness and integrity margins established above with cost effective health monitoring technologies; and use coupons, panels, and integrated full scale primary structure test articles to identify, evaluate, and characterize the preferred NDE/NDI/IHM sensor technologies that will be a part of the fault protection system.

Navier-Stokes and Euler solutions for lee-side flows over supersonic delta wings. A correlation with experiment

NASA Technical Reports Server (NTRS)

Mcmillin, S. Naomi; Thomas, James L.; Murman, Earll M.

1990-01-01

An Euler flow solver and a thin layer Navier-Stokes flow solver were used to numerically simulate the supersonic leeside flow fields over delta wings which were observed experimentally. Three delta wings with 75, 67.5, and 60 deg leading edge sweeps were computed over an angle-of-attack range of 4 to 20 deg at a Mach number 2.8. The Euler code and Navier-Stokes code predict equally well the primary flow structure where the flow is expected to be separated or attached at the leading edge based on the Stanbrook-Squire boundary. The Navier-Stokes code is capable of predicting both the primary and the secondary flow features for the parameter range investigated. For those flow conditions where the Euler code did not predict the correct type of primary flow structure, the Navier-Stokes code illustrated that the flow structure is sensitive to boundary layer model. In general, the laminar Navier-Stokes solutions agreed better with the experimental data, especially for the lower sweep delta wings. The computational results and a detailed re-examination of the experimental data resulted in a refinement of the flow classifications. This refinement in the flow classification results in the separation bubble with the shock flow type as the intermediate flow pattern between separated and attached flows.

Finite Element Based HWB Centerbody Structural Optimization and Weight Prediction

NASA Technical Reports Server (NTRS)

Gern, Frank H.

2012-01-01

This paper describes a scalable structural model suitable for Hybrid Wing Body (HWB) centerbody analysis and optimization. The geometry of the centerbody and primary wing structure is based on a Vehicle Sketch Pad (VSP) surface model of the aircraft and a FLOPS compatible parameterization of the centerbody. Structural analysis, optimization, and weight calculation are based on a Nastran finite element model of the primary HWB structural components, featuring centerbody, mid section, and outboard wing. Different centerbody designs like single bay or multi-bay options are analyzed and weight calculations are compared to current FLOPS results. For proper structural sizing and weight estimation, internal pressure and maneuver flight loads are applied. Results are presented for aerodynamic loads, deformations, and centerbody weight.

Decoding the future from past experience: learning shapes predictions in early visual cortex.

PubMed

Luft, Caroline D B; Meeson, Alan; Welchman, Andrew E; Kourtzi, Zoe

2015-05-01

Learning the structure of the environment is critical for interpreting the current scene and predicting upcoming events. However, the brain mechanisms that support our ability to translate knowledge about scene statistics to sensory predictions remain largely unknown. Here we provide evidence that learning of temporal regularities shapes representations in early visual cortex that relate to our ability to predict sensory events. We tested the participants' ability to predict the orientation of a test stimulus after exposure to sequences of leftward- or rightward-oriented gratings. Using fMRI decoding, we identified brain patterns related to the observers' visual predictions rather than stimulus-driven activity. Decoding of predicted orientations following structured sequences was enhanced after training, while decoding of cued orientations following exposure to random sequences did not change. These predictive representations appear to be driven by the same large-scale neural populations that encode actual stimulus orientation and to be specific to the learned sequence structure. Thus our findings provide evidence that learning temporal structures supports our ability to predict future events by reactivating selective sensory representations as early as in primary visual cortex. Copyright © 2015 the American Physiological Society.

GeneSilico protein structure prediction meta-server.

PubMed

Kurowski, Michal A; Bujnicki, Janusz M

2003-07-01

Rigorous assessments of protein structure prediction have demonstrated that fold recognition methods can identify remote similarities between proteins when standard sequence search methods fail. It has been shown that the accuracy of predictions is improved when refined multiple sequence alignments are used instead of single sequences and if different methods are combined to generate a consensus model. There are several meta-servers available that integrate protein structure predictions performed by various methods, but they do not allow for submission of user-defined multiple sequence alignments and they seldom offer confidentiality of the results. We developed a novel WWW gateway for protein structure prediction, which combines the useful features of other meta-servers available, but with much greater flexibility of the input. The user may submit an amino acid sequence or a multiple sequence alignment to a set of methods for primary, secondary and tertiary structure prediction. Fold-recognition results (target-template alignments) are converted into full-atom 3D models and the quality of these models is uniformly assessed. A consensus between different FR methods is also inferred. The results are conveniently presented on-line on a single web page over a secure, password-protected connection. The GeneSilico protein structure prediction meta-server is freely available for academic users at http://genesilico.pl/meta.

GeneSilico protein structure prediction meta-server

PubMed Central

Kurowski, Michal A.; Bujnicki, Janusz M.

2003-01-01

Rigorous assessments of protein structure prediction have demonstrated that fold recognition methods can identify remote similarities between proteins when standard sequence search methods fail. It has been shown that the accuracy of predictions is improved when refined multiple sequence alignments are used instead of single sequences and if different methods are combined to generate a consensus model. There are several meta-servers available that integrate protein structure predictions performed by various methods, but they do not allow for submission of user-defined multiple sequence alignments and they seldom offer confidentiality of the results. We developed a novel WWW gateway for protein structure prediction, which combines the useful features of other meta-servers available, but with much greater flexibility of the input. The user may submit an amino acid sequence or a multiple sequence alignment to a set of methods for primary, secondary and tertiary structure prediction. Fold-recognition results (target-template alignments) are converted into full-atom 3D models and the quality of these models is uniformly assessed. A consensus between different FR methods is also inferred. The results are conveniently presented on-line on a single web page over a secure, password-protected connection. The GeneSilico protein structure prediction meta-server is freely available for academic users at http://genesilico.pl/meta. PMID:12824313

The Alcohol Relapse Situation Appraisal Questionnaire: Development and Validation

PubMed Central

Martin, Rosemarie A.; MacKinnon, Selene M.; Johnson, Jennifer E.; Myers, Mark G.; Cook, Travis A. R.; Rohsenow, Damaris J.

2011-01-01

Background The role of cognitive appraisal of the threat of alcohol relapse has received little attention. A previous instrument, the Relapse Situation Appraisal Questionnaire (RSAQ), was developed to assess cocaine users’ primary appraisal of the threat of situations posing a high risk for cocaine relapse. The purpose of the present study was to modify the RSAQ in order to measure primary appraisal in situations involving a high risk for alcohol relapse. Methods The development and psychometric properties of this instrument, the Alcohol Relapse Situation Appraisal Questionnaire (A-RSAQ), were examined with two samples of abstinent adults with alcohol abuse or dependence. Factor structure and validity were examined in Study 1 (N=104). Confirmation of the factor structure and predictive validity were assessed in Study 2 (N=161). Results Results demonstrated construct, discriminant and predictive validity and reliability of the A-RSAQ. Discussion Results support the important role of primary appraisal of degree of risk in alcohol relapse situations. PMID:21237586

Meteorological Satellites (METSAT) and Earth Observing System (EOS) Advanced Microwave Sounding Unit-A (AMSU-A) Stress Analysis Report

NASA Technical Reports Server (NTRS)

Heffner, Robert

1996-01-01

Stress analysis of the primary structure of the Meteorological Satellites Project (METSAT) Advanced Microwave Sounding Units-A, A1 Module using static loads is presented. The structural margins of safety and natural frequency predictions for the METSAT design are reported.

A high-throughput approach to profile RNA structure.

PubMed

Delli Ponti, Riccardo; Marti, Stefanie; Armaos, Alexandros; Tartaglia, Gian Gaetano

2017-03-17

Here we introduce the Computational Recognition of Secondary Structure (CROSS) method to calculate the structural profile of an RNA sequence (single- or double-stranded state) at single-nucleotide resolution and without sequence length restrictions. We trained CROSS using data from high-throughput experiments such as Selective 2΄-Hydroxyl Acylation analyzed by Primer Extension (SHAPE; Mouse and HIV transcriptomes) and Parallel Analysis of RNA Structure (PARS; Human and Yeast transcriptomes) as well as high-quality NMR/X-ray structures (PDB database). The algorithm uses primary structure information alone to predict experimental structural profiles with >80% accuracy, showing high performances on large RNAs such as Xist (17 900 nucleotides; Area Under the ROC Curve AUC of 0.75 on dimethyl sulfate (DMS) experiments). We integrated CROSS in thermodynamics-based methods to predict secondary structure and observed an increase in their predictive power by up to 30%. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Engine-induced structural-borne noise in a general aviation aircraft

NASA Technical Reports Server (NTRS)

Unruh, J. F.; Scheidt, D. C.; Pomerening, D. J.

1979-01-01

Structural borne interior noise in a single engine general aviation aircraft was studied to determine the importance of engine induced structural borne noise and to determine the necessary modeling requirements for the prediction of structural borne interior noise. Engine attached/detached ground test data show that engine induced structural borne noise is a primary interior noise source for the single engine test aircraft, cabin noise is highly influenced by responses at the propeller tone, and cabin acoustic resonances can influence overall noise levels. Results from structural and acoustic finite element coupled models of the test aircraft show that wall flexibility has a strong influence on fundamental cabin acoustic resonances, the lightweight fuselage structure has a high modal density, and finite element analysis procedures are appropriate for the prediction of structural borne noise.

Internal and external relationships of the Cnidaria: implications of primary and predicted secondary structure of the 5'-end of the 23S-like rDNA.

PubMed Central

Odorico, D M; Miller, D J

1997-01-01

Since both internal (class-level) and external relationships of the Cnidaria remain unclear on the basis of analyses of 18S and (partial) 16S rDNA sequence data, we examined the informativeness of the 5'-end of the 23S-like rDNA. Here we describe analyses of both primary and predicted secondary structure data for this region from the ctenophore Bolinopsis sp., the placozoan Trichoplax adhaerens, the sponge Hymeniacidon heliophila, and representatives of all four cnidarian classes. Primary sequence analyses clearly resolved the Cnidaria from other lower Metazoa, supported sister group relationships between the Scyphozoa and Cubozoa and between the Ctenophora and the Placozoa, and confirmed the basal status of the Anthozoa within the Cnidaria. Additionally, in the ctenophore, placozoan and sponge, non-canonical base pairing is required to maintain the secondary structure of the B12 region, whereas amongst the Cnidaria this is not the case. Although the phylogenetic significance of this molecular character is unclear, our analyses do not support the close relationship between Cnidaria and Placozoa suggested by previous studies. PMID:9061962

Aromatic claw: A new fold with high aromatic content that evades structural prediction: Aromatic Claw

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sachleben, Joseph R.; Adhikari, Aashish N.; Gawlak, Grzegorz

2016-11-10

We determined the NMR structure of a highly aromatic (13%) protein of unknown function, Aq1974 from Aquifex aeolicus (PDB ID: 5SYQ). The unusual sequence of this protein has a tryptophan content five times the normal (six tryptophan residues of 114 or 5.2% while the average tryptophan content is 1.0%) with the tryptophans occurring in a WXW motif. It has no detectable sequence homology with known protein structures. Although its NMR spectrum suggested that the protein was rich in β-sheet, upon resonance assignment and solution structure determination, the protein was found to be primarily α-helical with a small two-stranded β-sheet withmore » a novel fold that we have termed an Aromatic Claw. As this fold was previously unknown and the sequence unique, we submitted the sequence to CASP10 as a target for blind structural prediction. At the end of the competition, the sequence was classified a hard template based model; the structural relationship between the template and the experimental structure was small and the predictions all failed to predict the structure. CSRosetta was found to predict the secondary structure and its packing; however, it was found that there was little correlation between CSRosetta score and the RMSD between the CSRosetta structure and the NMR determined one. This work demonstrates that even in relatively small proteins, we do not yet have the capacity to accurately predict the fold for all primary sequences. The experimental discovery of new folds helps guide the improvement of structural prediction methods.« less

Prediction of Protein Structural Classes for Low-Similarity Sequences Based on Consensus Sequence and Segmented PSSM.

PubMed

Liang, Yunyun; Liu, Sanyang; Zhang, Shengli

2015-01-01

Prediction of protein structural classes for low-similarity sequences is useful for understanding fold patterns, regulation, functions, and interactions of proteins. It is well known that feature extraction is significant to prediction of protein structural class and it mainly uses protein primary sequence, predicted secondary structure sequence, and position-specific scoring matrix (PSSM). Currently, prediction solely based on the PSSM has played a key role in improving the prediction accuracy. In this paper, we propose a novel method called CSP-SegPseP-SegACP by fusing consensus sequence (CS), segmented PsePSSM, and segmented autocovariance transformation (ACT) based on PSSM. Three widely used low-similarity datasets (1189, 25PDB, and 640) are adopted in this paper. Then a 700-dimensional (700D) feature vector is constructed and the dimension is decreased to 224D by using principal component analysis (PCA). To verify the performance of our method, rigorous jackknife cross-validation tests are performed on 1189, 25PDB, and 640 datasets. Comparison of our results with the existing PSSM-based methods demonstrates that our method achieves the favorable and competitive performance. This will offer an important complementary to other PSSM-based methods for prediction of protein structural classes for low-similarity sequences.

Metamorphic Proteins: Emergence of Dual Protein Folds from One Primary Sequence.

PubMed

Lella, Muralikrishna; Mahalakshmi, Radhakrishnan

2017-06-20

Every amino acid exhibits a different propensity for distinct structural conformations. Hence, decoding how the primary amino acid sequence undergoes the transition to a defined secondary structure and its final three-dimensional fold is presently considered predictable with reasonable certainty. However, protein sequences that defy the first principles of secondary structure prediction (they attain two different folds) have recently been discovered. Such proteins, aptly named metamorphic proteins, decrease the conformational constraint by increasing flexibility in the secondary structure and thereby result in efficient functionality. In this review, we discuss the major factors driving the conformational switch related both to protein sequence and to structure using illustrative examples. We discuss the concept of an evolutionary transition in sequence and structure, the functional impact of the tertiary fold, and the pressure of intrinsic and external factors that give rise to metamorphic proteins. We mainly focus on the major components of protein architecture, namely, the α-helix and β-sheet segments, which are involved in conformational switching within the same or highly similar sequences. These chameleonic sequences are widespread in both cytosolic and membrane proteins, and these folds are equally important for protein structure and function. We discuss the implications of metamorphic proteins and chameleonic peptide sequences in de novo peptide design.

Classifying Membrane Proteins in the Proteome by Using Artificial Neural Networks Based on the Preferential Parameters of Amino Acids

NASA Astrophysics Data System (ADS)

Bose, Subrata K.; Browne, Antony; Kazemian, Hassan; White, Kenneth

Membrane proteins (MPs) are large set of biological macromolecules that play a fundamental role in physiology and pathophysiology for survival. From a pharma-economical perspective, though it is the fact that MPs constitute ˜75% of possible targets for novel drugs but MPs are one of the most understudied groups of proteins in biochemical research. This is mainly because of the technical difficulties of obtaining structural information about trans-membrane regions (these are small sequences that crossways the bilayer lipid membrane). It is quite useful to predict the location of transmembrane segments down the sequence, since these are the elementary structural building blocks defining their topology. There have been several attempts over the last 20 years to develop tools for predicting membrane-spanning regions but current tools are far away from achieving a considerable reliability in prediction. This study aims to exploit the knowledge and current understanding in the field of artificial neural networks (ANNs) in particular data representation through the development of a system to identify and predict membrane-spanning regions by analysing primary amino acids sequence. In this paper we present a novel neural network (NNs) architecture and algorithms for predicting membrane spanning regions from primary amino acids sequences by using their preference parameters.

Effects of climate change and shifts in forest composition on forest net primary production

Treesearch

Jyh-Min Chiang; Louts [Louis] R. Iverson; Anantha Prasad; Kim J. Brown

2008-01-01

Forests are dynamic in both structure and species composition, and these dynamics are strongly influenced by climate. However, the net effects of future tree species composition on net primary production (NPP) are not well understood. The objective of this work was to model the potential range shifts of tree species (DISTRIB Model) and predict their impacts on NPP (...

A unifying theory for top-heavy ecosystem structure in the ocean.

PubMed

Woodson, C Brock; Schramski, John R; Joye, Samantha B

2018-01-02

Size generally dictates metabolic requirements, trophic level, and consequently, ecosystem structure, where inefficient energy transfer leads to bottom-heavy ecosystem structure and biomass decreases as individual size (or trophic level) increases. However, many animals deviate from simple size-based predictions by either adopting generalist predatory behavior, or feeding lower in the trophic web than predicted from their size. Here we show that generalist predatory behavior and lower trophic feeding at large body size increase overall biomass and shift ecosystems from a bottom-heavy pyramid to a top-heavy hourglass shape, with the most biomass accounted for by the largest animals. These effects could be especially dramatic in the ocean, where primary producers are the smallest components of the ecosystem. This approach makes it possible to explore and predict, in the past and in the future, the structure of ocean ecosystems without biomass extraction and other impacts.

MUFOLD-SS: New deep inception-inside-inception networks for protein secondary structure prediction.

PubMed

Fang, Chao; Shang, Yi; Xu, Dong

2018-05-01

Protein secondary structure prediction can provide important information for protein 3D structure prediction and protein functions. Deep learning offers a new opportunity to significantly improve prediction accuracy. In this article, a new deep neural network architecture, named the Deep inception-inside-inception (Deep3I) network, is proposed for protein secondary structure prediction and implemented as a software tool MUFOLD-SS. The input to MUFOLD-SS is a carefully designed feature matrix corresponding to the primary amino acid sequence of a protein, which consists of a rich set of information derived from individual amino acid, as well as the context of the protein sequence. Specifically, the feature matrix is a composition of physio-chemical properties of amino acids, PSI-BLAST profile, and HHBlits profile. MUFOLD-SS is composed of a sequence of nested inception modules and maps the input matrix to either eight states or three states of secondary structures. The architecture of MUFOLD-SS enables effective processing of local and global interactions between amino acids in making accurate prediction. In extensive experiments on multiple datasets, MUFOLD-SS outperformed the best existing methods and other deep neural networks significantly. MUFold-SS can be downloaded from http://dslsrv8.cs.missouri.edu/~cf797/MUFoldSS/download.html. © 2018 Wiley Periodicals, Inc.

Application of the Spectral Element Method to Interior Noise Problems

NASA Technical Reports Server (NTRS)

Doyle, James F.

1998-01-01

The primary effort of this research project was focused the development of analytical methods for the accurate prediction of structural acoustic noise and response. Of particular interest was the development of curved frame and shell spectral elements for the efficient computational of structural response and of schemes to match this to the surrounding fluid.

Multiple Simulated Annealing-Molecular Dynamics (MSA-MD) for Conformational Space Search of Peptide and Miniprotein

PubMed Central

Hao, Ge-Fei; Xu, Wei-Fang; Yang, Sheng-Gang; Yang, Guang-Fu

2015-01-01

Protein and peptide structure predictions are of paramount importance for understanding their functions, as well as the interactions with other molecules. However, the use of molecular simulation techniques to directly predict the peptide structure from the primary amino acid sequence is always hindered by the rough topology of the conformational space and the limited simulation time scale. We developed here a new strategy, named Multiple Simulated Annealing-Molecular Dynamics (MSA-MD) to identify the native states of a peptide and miniprotein. A cluster of near native structures could be obtained by using the MSA-MD method, which turned out to be significantly more efficient in reaching the native structure compared to continuous MD and conventional SA-MD simulation. PMID:26492886

Linking extinction-colonization dynamics to genetic structure in a salamander metapopulation.

PubMed

Cosentino, Bradley J; Phillips, Christopher A; Schooley, Robert L; Lowe, Winsor H; Douglas, Marlis R

2012-04-22

Theory predicts that founder effects have a primary role in determining metapopulation genetic structure. However, ecological factors that affect extinction-colonization dynamics may also create spatial variation in the strength of genetic drift and migration. We tested the hypothesis that ecological factors underlying extinction-colonization dynamics influenced the genetic structure of a tiger salamander (Ambystoma tigrinum) metapopulation. We used empirical data on metapopulation dynamics to make a priori predictions about the effects of population age and ecological factors on genetic diversity and divergence among 41 populations. Metapopulation dynamics of A. tigrinum depended on wetland area, connectivity and presence of predatory fish. We found that newly colonized populations were more genetically differentiated than established populations, suggesting that founder effects influenced genetic structure. However, ecological drivers of metapopulation dynamics were more important than age in predicting genetic structure. Consistent with demographic predictions from metapopulation theory, genetic diversity and divergence depended on wetland area and connectivity. Divergence was greatest in small, isolated wetlands where genetic diversity was low. Our results show that ecological factors underlying metapopulation dynamics can be key determinants of spatial genetic structure, and that habitat area and isolation may mediate the contributions of drift and migration to divergence and evolution in local populations.

From chemotaxis to the cognitive map: The function of olfaction

PubMed Central

Jacobs, Lucia F.

2012-01-01

A paradox of vertebrate brain evolution is the unexplained variability in the size of the olfactory bulb (OB), in contrast to other brain regions, which scale predictably with brain size. Such variability appears to be the result of selection for olfactory function, yet there is no obvious concordance that would predict the causal relationship between OB size and behavior. This discordance may derive from assuming the primary function of olfaction is odorant discrimination and acuity. If instead the primary function of olfaction is navigation, i.e., predicting odorant distributions in time and space, variability in absolute OB size could be ascribed and explained by variability in navigational demand. This olfactory spatial hypothesis offers a single functional explanation to account for patterns of olfactory system scaling in vertebrates, the primacy of olfaction in spatial navigation, even in visual specialists, and proposes an evolutionary scenario to account for the convergence in olfactory structure and function across protostomes and deuterostomes. In addition, the unique percepts of olfaction may organize odorant information in a parallel map structure. This could have served as a scaffold for the evolution of the parallel map structure of the mammalian hippocampus, and possibly the arthropod mushroom body, and offers an explanation for similar flexible spatial navigation strategies in arthropods and vertebrates. PMID:22723365

Multiphase flow predictions from carbonate pore space images using extracted network models

NASA Astrophysics Data System (ADS)

Al-Kharusi, Anwar S.; Blunt, Martin J.

2008-06-01

A methodology to extract networks from pore space images is used to make predictions of multiphase transport properties for subsurface carbonate samples. The extraction of the network model is based on the computation of the location and sizes of pores and throats to create a topological representation of the void space of three-dimensional (3-D) rock images, using the concept of maximal balls. In this work, we follow a multistaged workflow. We start with a 2-D thin-section image; convert it statistically into a 3-D representation of the pore space; extract a network model from this image; and finally, simulate primary drainage, waterflooding, and secondary drainage flow processes using a pore-scale simulator. We test this workflow for a reservoir carbonate rock. The network-predicted absolute permeability is similar to the core plug measured value and the value computed on the 3-D void space image using the lattice Boltzmann method. The predicted capillary pressure during primary drainage agrees well with a mercury-air experiment on a core sample, indicating that we have an adequate representation of the rock's pore structure. We adjust the contact angles in the network to match the measured waterflood and secondary drainage capillary pressures. We infer a significant degree of contact angle hysteresis. We then predict relative permeabilities for primary drainage, waterflooding, and secondary drainage that agree well with laboratory measured values. This approach can be used to predict multiphase transport properties when wettability and pore structure vary in a reservoir, where experimental data is scant or missing. There are shortfalls to this approach, however. We compare results from three networks, one of which was derived from a section of the rock containing vugs. Our method fails to predict properties reliably when an unrepresentative image is processed to construct the 3-D network model. This occurs when the image volume is not sufficient to represent the geological variations observed in a core plug sample.

A Review of the NASA Textile Composites Research

NASA Technical Reports Server (NTRS)

Poe, C. C., Jr.; Dexter, H. B.; Raju, I. S.

1997-01-01

During the past 15 years NASA has taken the lead role in exploiting the benefits of textile reinforced composite materials for application to aircraft structures. The NASA Advanced Composites Technology (ACT) program was started in 1989 to develop composite primary structures for commercial transport airplanes with costs that are competitive with metal structures. As part of this program, several contractors investigated the cost, weight, and performance attributes of textile reinforced composites. Textile composites made using resin transfer molding type processes were evaluated for numerous applications. Methods were also developed to predict resin infiltration and flow in textile preforms and to predict and measure mechanical properties of the textile composites. This paper describes the salient results of that program.

Integrated Advanced Microwave Sounding Unit-A (AMSU-A) METOP Stress Analysis Report (Qual Level Random Vibration) A1 Module

NASA Technical Reports Server (NTRS)

Mehitretter, R.

1996-01-01

Stress analysis of the primary structure of the Meteorological Satellites Project (METSAT) Advanced Microwave Sounding Units-A, A1 Module performed using the Meteorological Operational (METOP) Qualification Level 9.66 grms Random Vibration PSD Spectrum is presented. The random vibration structural margins of safety and natural frequency predictions are summarized.

Validation of Nurse Practitioner Primary Care Organizational Climate Questionnaire: A New Tool to Study Nurse Practitioner Practice Settings.

PubMed

Poghosyan, Lusine; Chaplin, William F; Shaffer, Jonathan A

2017-04-01

Favorable organizational climate in primary care settings is necessary to expand the nurse practitioner (NP) workforce and promote their practice. Only one NP-specific tool, the Nurse Practitioner Primary Care Organizational Climate Questionnaire (NP-PCOCQ), measures NP organizational climate. We confirmed NP-PCOCQ's factor structure and established its predictive validity. A crosssectional survey design was used to collect data from 314 NPs in Massachusetts in 2012. Confirmatory factor analysis and regression models were used. The 4-factor model characterized NP-PCOCQ. The NP-PCOCQ score predicted job satisfaction (beta = .36; p < .001) and intent to leave job (odds ratio = .28; p = .011). NP-PCOCQ can be used by researchers to produce new evidence and by administrators to assess organizational climate in their clinics. Further testing of NP-PCOCQ is needed.

Preliminary Analysis of the 30-m UltraBoom Flight Test

NASA Technical Reports Server (NTRS)

Agnes, Gregory S.; Abelson, Robert D.; Miyake, Robert; Lin, John K. H.; Welsh, Joe; Watson, Judith J.

2005-01-01

Future NASA missions require long, ultra-lightweight booms to enable solar sails, large sunshields, and other gossamer-type spacecraft structures. The space experiment discussed in this paper will flight validate the non-traditional ultra lightweight rigidizable, inflatable, isogrid structure utilizing graphite shape memory polymer (GR/SMP) called UltraBoom(TradeMark). The focus of this paper is the analysis of the 3-m ground test article. The primary objective of the mission is to show that a combination of ground testing and analysis can predict the on-orbit performance of an ultra lightweight boom that is scalable, predictable, and thermomechanically stable.

Exploring the Sequence-based Prediction of Folding Initiation Sites in Proteins.

PubMed

Raimondi, Daniele; Orlando, Gabriele; Pancsa, Rita; Khan, Taushif; Vranken, Wim F

2017-08-18

Protein folding is a complex process that can lead to disease when it fails. Especially poorly understood are the very early stages of protein folding, which are likely defined by intrinsic local interactions between amino acids close to each other in the protein sequence. We here present EFoldMine, a method that predicts, from the primary amino acid sequence of a protein, which amino acids are likely involved in early folding events. The method is based on early folding data from hydrogen deuterium exchange (HDX) data from NMR pulsed labelling experiments, and uses backbone and sidechain dynamics as well as secondary structure propensities as features. The EFoldMine predictions give insights into the folding process, as illustrated by a qualitative comparison with independent experimental observations. Furthermore, on a quantitative proteome scale, the predicted early folding residues tend to become the residues that interact the most in the folded structure, and they are often residues that display evolutionary covariation. The connection of the EFoldMine predictions with both folding pathway data and the folded protein structure suggests that the initial statistical behavior of the protein chain with respect to local structure formation has a lasting effect on its subsequent states.

Successive range expansion promotes diversity and accelerates evolution in spatially structured microbial populations.

PubMed

Goldschmidt, Felix; Regoes, Roland R; Johnson, David R

2017-09-01

Successive range expansions occur within all domains of life, where one population expands first (primary expansion) and one or more secondary populations then follow (secondary expansion). In general, genetic drift reduces diversity during range expansion. However, it is not clear whether the same effect applies during successive range expansion, mainly because the secondary population must expand into space occupied by the primary population. Here we used an experimental microbial model system to show that, in contrast to primary range expansion, successive range expansion promotes local population diversity. Because of mechanical constraints imposed by the presence of the primary population, the secondary population forms fractal-like dendritic structures. This divides the advancing secondary population into many small sub-populations and promotes intermixing between the primary and secondary populations. We further developed a mathematical model to simulate the formation of dendritic structures in the secondary population during succession. By introducing mutations in the primary or dendritic secondary populations, we found that mutations are more likely to accumulate in the dendritic secondary populations. Our results thus show that successive range expansion can promote intermixing over the short term and increase genetic diversity over the long term. Our results therefore have potentially important implications for predicting the ecological processes and evolutionary trajectories of microbial communities.

Test and Analysis of a Buckling-Critical Large-Scale Sandwich Composite Cylinder

NASA Technical Reports Server (NTRS)

Schultz, Marc R.; Sleight, David W.; Gardner, Nathaniel W.; Rudd, Michelle T.; Hilburger, Mark W.; Palm, Tod E.; Oldfield, Nathan J.

2018-01-01

Structural stability is an important design consideration for launch-vehicle shell structures and it is well known that the buckling response of such shell structures can be very sensitive to small geometric imperfections. As part of an effort to develop new buckling design guidelines for sandwich composite cylindrical shells, an 8-ft-diameter honeycomb-core sandwich composite cylinder was tested under pure axial compression to failure. The results from this test are compared with finite-element-analysis predictions and overall agreement was very good. In particular, the predicted buckling load was within 1% of the test and the character of the response matched well. However, it was found that the agreement could be improved by including composite material nonlinearity in the analysis, and that the predicted buckling initiation site was sensitive to the addition of small bending loads to the primary axial load in analyses.

Dynamic/Jitter Assessment of Multiple Potential HabEx Structural Designs

NASA Technical Reports Server (NTRS)

Knight, J. Brent; Stahl, H. Philip; Singleton, Andrew William; Hunt, Ronald A.; Therrell, Melissa F.; Caldwell, Mary Kathryn; Garcia, Jay Clarke

2017-01-01

The 2020 Decadal Survey in Astronomy and Astrophysics will assess candidate large missions to follow James Webb Space Telescope (JWST) and Wide Field Infrared Space Telescope (WFIRST). One candidate mission is the Habitable ExoPlanet Imaging Mission (HabEx). This presentation describes two HabEx structural designs and results from structural dynamic analyses performed to predict Primary Mirror (PM) Secondary Mirror (SM) Line of Site (LOS) stability (jitter) due to Reaction Wheel Assembly (RWA) vibrations.

Advanced composites structural concepts and materials technologies for primary aircraft structures: Structural response and failure analysis

NASA Technical Reports Server (NTRS)

Dorris, William J.; Hairr, John W.; Huang, Jui-Tien; Ingram, J. Edward; Shah, Bharat M.

1992-01-01

Non-linear analysis methods were adapted and incorporated in a finite element based DIAL code. These methods are necessary to evaluate the global response of a stiffened structure under combined in-plane and out-of-plane loading. These methods include the Arc Length method and target point analysis procedure. A new interface material model was implemented that can model elastic-plastic behavior of the bond adhesive. Direct application of this method is in skin/stiffener interface failure assessment. Addition of the AML (angle minus longitudinal or load) failure procedure and Hasin's failure criteria provides added capability in the failure predictions. Interactive Stiffened Panel Analysis modules were developed as interactive pre-and post-processors. Each module provides the means of performing self-initiated finite elements based analysis of primary structures such as a flat or curved stiffened panel; a corrugated flat sandwich panel; and a curved geodesic fuselage panel. This module brings finite element analysis into the design of composite structures without the requirement for the user to know much about the techniques and procedures needed to actually perform a finite element analysis from scratch. An interactive finite element code was developed to predict bolted joint strength considering material and geometrical non-linearity. The developed method conducts an ultimate strength failure analysis using a set of material degradation models.

Design and evaluation of a foam-filled hat-stiffened panel concept for aircraft primary structural applications

NASA Technical Reports Server (NTRS)

Ambur, Damodar R.

1993-01-01

Geodesically stiffened structures are very efficient in carrying combined bending, torsion, and pressure loading that is typical of primary aircraft structures. They are also very damage tolerant since there are multiple load paths available to redistribute loads compared to prismatically stiffened structures. Geodesically stiffened structures utilize continuous filament composite materials which make them amenable to automated manufacturing processes to reduce cost. The current practice for geodesically stiffened structures is to use a solid blade construction for the stiffener. This stiffener configuration is not an efficient concept and there is a need to identify other stiffener configurations that are more efficient but utilize the same manufacturing process as the solid blade. This paper describes a foam-filled stiffener cross section that is more efficient than a solid-blade stiffener in the load range corresponding to primary aircraft structures. A prismatic hat-stiffener panel design is then selected for structural evaluation in uni-axial compression with and without impact damage. Experimental results for both single stiffener specimens and multi-stiffener panel specimens are presented. Finite element analysis results are presented that predict the buckling and postbuckling response of the test specimens. Analytical results for both the element and panel specimens are compared with experimental results.

Prediction of response of aircraft panels subjected to acoustic and thermal loads

NASA Technical Reports Server (NTRS)

Mei, Chuh

1992-01-01

The primary effort of this research project has been focused on the development of analytical methods for the prediction of random response of structural panels subjected to combined and intense acoustic and thermal loads. The accomplishments on various acoustic fatigue research activities are described first, then followed by publications and theses. Topics covered include: transverse shear deformation; finite element models of vibrating composite laminates; large deflection vibration modeling; finite element analysis of thermal buckling; and prediction of three dimensional duct using boundary element method.

Conservation of Three-Dimensional Helix-Loop-Helix Structure through the Vertebrate Lineage Reopens the Cold Case of Gonadotropin-Releasing Hormone-Associated Peptide.

PubMed

Pérez Sirkin, Daniela I; Lafont, Anne-Gaëlle; Kamech, Nédia; Somoza, Gustavo M; Vissio, Paula G; Dufour, Sylvie

2017-01-01

GnRH-associated peptide (GAP) is the C-terminal portion of the gonadotropin-releasing hormone (GnRH) preprohormone. Although it was reported in mammals that GAP may act as a prolactin-inhibiting factor and can be co-secreted with GnRH into the hypophyseal portal blood, GAP has been practically out of the research circuit for about 20 years. Comparative studies highlighted the low conservation of GAP primary amino acid sequences among vertebrates, contributing to consider that this peptide only participates in the folding or carrying process of GnRH. Considering that the three-dimensional (3D) structure of a protein may define its function, the aim of this study was to evaluate if GAP sequences and 3D structures are conserved in the vertebrate lineage. GAP sequences from various vertebrates were retrieved from databases. Analysis of primary amino acid sequence identity and similarity, molecular phylogeny, and prediction of 3D structures were performed. Amino acid sequence comparison and phylogeny analyses confirmed the large variation of GAP sequences throughout vertebrate radiation. In contrast, prediction of the 3D structure revealed a striking conservation of the 3D structure of GAP1 (GAP associated with the hypophysiotropic type 1 GnRH), despite low amino acid sequence conservation. This GAP1 peptide presented a typical helix-loop-helix (HLH) structure in all the vertebrate species analyzed. This HLH structure could also be predicted for GAP2 in some but not all vertebrate species and in none of the GAP3 analyzed. These results allowed us to infer that selective pressures have maintained GAP1 HLH structure throughout the vertebrate lineage. The conservation of the HLH motif, known to confer biological activity to various proteins, suggests that GAP1 peptides may exert some hypophysiotropic biological functions across vertebrate radiation.

Conservation of Three-Dimensional Helix-Loop-Helix Structure through the Vertebrate Lineage Reopens the Cold Case of Gonadotropin-Releasing Hormone-Associated Peptide

PubMed Central

Pérez Sirkin, Daniela I.; Lafont, Anne-Gaëlle; Kamech, Nédia; Somoza, Gustavo M.; Vissio, Paula G.; Dufour, Sylvie

2017-01-01

GnRH-associated peptide (GAP) is the C-terminal portion of the gonadotropin-releasing hormone (GnRH) preprohormone. Although it was reported in mammals that GAP may act as a prolactin-inhibiting factor and can be co-secreted with GnRH into the hypophyseal portal blood, GAP has been practically out of the research circuit for about 20 years. Comparative studies highlighted the low conservation of GAP primary amino acid sequences among vertebrates, contributing to consider that this peptide only participates in the folding or carrying process of GnRH. Considering that the three-dimensional (3D) structure of a protein may define its function, the aim of this study was to evaluate if GAP sequences and 3D structures are conserved in the vertebrate lineage. GAP sequences from various vertebrates were retrieved from databases. Analysis of primary amino acid sequence identity and similarity, molecular phylogeny, and prediction of 3D structures were performed. Amino acid sequence comparison and phylogeny analyses confirmed the large variation of GAP sequences throughout vertebrate radiation. In contrast, prediction of the 3D structure revealed a striking conservation of the 3D structure of GAP1 (GAP associated with the hypophysiotropic type 1 GnRH), despite low amino acid sequence conservation. This GAP1 peptide presented a typical helix-loop-helix (HLH) structure in all the vertebrate species analyzed. This HLH structure could also be predicted for GAP2 in some but not all vertebrate species and in none of the GAP3 analyzed. These results allowed us to infer that selective pressures have maintained GAP1 HLH structure throughout the vertebrate lineage. The conservation of the HLH motif, known to confer biological activity to various proteins, suggests that GAP1 peptides may exert some hypophysiotropic biological functions across vertebrate radiation. PMID:28878737

Modeling the effect of 3 missense AGXT mutations on dimerization of the AGT enzyme in primary hyperoxaluria type 1.

PubMed

Robbiano, Angela; Frecer, Vladimir; Miertus, Jan; Zadro, Cristina; Ulivi, Sheila; Bevilacqua, Elena; Mandrile, Giorgia; De Marchi, Mario; Miertus, Stanislav; Amoroso, Antonio

2010-01-01

Mutations of the AGXT gene encoding the alanine:glyoxylate aminotransferase liver enzyme (AGT) cause primary hyperoxaluria type 1 (PH1). Here we report a molecular modeling study of selected missense AGXT mutations: the common Gly170Arg and the recently described Gly47Arg and Ser81Leu variants, predicted to be pathogenic using standard criteria. Taking advantage of the refined 3D structure of AGT, we computed the dimerization energy of the wild-type and mutated proteins. Molecular modeling predicted that Gly47Arg affects dimerization with a similar effect to that shown previously for Gly170Arg through classical biochemical approaches. In contrast, no effect on dimerization was predicted for Ser81Leu. Therefore, this probably demonstrates pathogenic properties via a different mechanism, similar to that described for the adjacent Gly82Glu mutation that affects pyridoxine binding. This study shows that the molecular modeling approach can contribute to evaluating the pathogenicity of some missense variants that affect dimerization. However, in silico studies--aimed to assess the relationship between structural change and biological effects--require the integrated use of more than 1 tool.

Enniatin and Beauvericin Biosynthesis in Fusarium Species: Production Profiles and Structural Determinant Prediction.

PubMed

Liuzzi, Vania C; Mirabelli, Valentina; Cimmarusti, Maria Teresa; Haidukowski, Miriam; Leslie, John F; Logrieco, Antonio F; Caliandro, Rocco; Fanelli, Francesca; Mulè, Giuseppina

2017-01-25

Members of the fungal genus Fusarium can produce numerous secondary metabolites, including the nonribosomal mycotoxins beauvericin (BEA) and enniatins (ENNs). Both mycotoxins are synthesized by the multifunctional enzyme enniatin synthetase (ESYN1) that contains both peptide synthetase and S-adenosyl-l-methionine-dependent N -methyltransferase activities. Several Fusarium species can produce ENNs, BEA or both, but the mechanism(s) enabling these differential metabolic profiles is unknown. In this study, we analyzed the primary structure of ESYN1 by sequencing esyn1 transcripts from different Fusarium species. We measured ENNs and BEA production by ultra-performance liquid chromatography coupled with photodiode array and Acquity QDa mass detector (UPLC-PDA-QDa) analyses. We predicted protein structures, compared the predictions by multivariate analysis methods and found a striking correlation between BEA/ENN-producing profiles and ESYN1 three-dimensional structures. Structural differences in the β strand's Asn789-Ala793 and His797-Asp802 portions of the amino acid adenylation domain can be used to distinguish BEA/ENN-producing Fusarium isolates from those that produce only ENN.

Predicting residue-wise contact orders in proteins by support vector regression.

PubMed

Song, Jiangning; Burrage, Kevin

2006-10-03

The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences.

First Principles Predictions of the Structure and Function of G-Protein-Coupled Receptors: Validation for Bovine Rhodopsin

PubMed Central

Trabanino, Rene J.; Hall, Spencer E.; Vaidehi, Nagarajan; Floriano, Wely B.; Kam, Victor W. T.; Goddard, William A.

2004-01-01

G-protein-coupled receptors (GPCRs) are involved in cell communication processes and with mediating such senses as vision, smell, taste, and pain. They constitute a prominent superfamily of drug targets, but an atomic-level structure is available for only one GPCR, bovine rhodopsin, making it difficult to use structure-based methods to design receptor-specific drugs. We have developed the MembStruk first principles computational method for predicting the three-dimensional structure of GPCRs. In this article we validate the MembStruk procedure by comparing its predictions with the high-resolution crystal structure of bovine rhodopsin. The crystal structure of bovine rhodopsin has the second extracellular (EC-II) loop closed over the transmembrane regions by making a disulfide linkage between Cys-110 and Cys-187, but we speculate that opening this loop may play a role in the activation process of the receptor through the cysteine linkage with helix 3. Consequently we predicted two structures for bovine rhodopsin from the primary sequence (with no input from the crystal structure)—one with the EC-II loop closed as in the crystal structure, and the other with the EC-II loop open. The MembStruk-predicted structure of bovine rhodopsin with the closed EC-II loop deviates from the crystal by 2.84 Å coordinate root mean-square (CRMS) in the transmembrane region main-chain atoms. The predicted three-dimensional structures for other GPCRs can be validated only by predicting binding sites and energies for various ligands. For such predictions we developed the HierDock first principles computational method. We validate HierDock by predicting the binding site of 11-cis-retinal in the crystal structure of bovine rhodopsin. Scanning the whole protein without using any prior knowledge of the binding site, we find that the best scoring conformation in rhodopsin is 1.1 Å CRMS from the crystal structure for the ligand atoms. This predicted conformation has the carbonyl O only 2.82 Å from the N of Lys-296. Making this Schiff base bond and minimizing leads to a final conformation only 0.62 Å CRMS from the crystal structure. We also used HierDock to predict the binding site of 11-cis-retinal in the MembStruk-predicted structure of bovine rhodopsin (closed loop). Scanning the whole protein structure leads to a structure in which the carbonyl O is only 2.85 Å from the N of Lys-296. Making this Schiff base bond and minimizing leads to a final conformation only 2.92 Å CRMS from the crystal structure. The good agreement of the ab initio-predicted protein structures and ligand binding site with experiment validates the use of the MembStruk and HierDock first principles' methods. Since these methods are generic and applicable to any GPCR, they should be useful in predicting the structures of other GPCRs and the binding site of ligands to these proteins. PMID:15041637

Tertiary structure-based analysis of microRNA–target interactions

PubMed Central

Gan, Hin Hark; Gunsalus, Kristin C.

2013-01-01

Current computational analysis of microRNA interactions is based largely on primary and secondary structure analysis. Computationally efficient tertiary structure-based methods are needed to enable more realistic modeling of the molecular interactions underlying miRNA-mediated translational repression. We incorporate algorithms for predicting duplex RNA structures, ionic strength effects, duplex entropy and free energy, and docking of duplex–Argonaute protein complexes into a pipeline to model and predict miRNA–target duplex binding energies. To ensure modeling accuracy and computational efficiency, we use an all-atom description of RNA and a continuum description of ionic interactions using the Poisson–Boltzmann equation. Our method predicts the conformations of two constructs of Caenorhabditis elegans let-7 miRNA–target duplexes to an accuracy of ∼3.8 Å root mean square distance of their NMR structures. We also show that the computed duplex formation enthalpies, entropies, and free energies for eight miRNA–target duplexes agree with titration calorimetry data. Analysis of duplex–Argonaute docking shows that structural distortions arising from single-base-pair mismatches in the seed region influence the activity of the complex by destabilizing both duplex hybridization and its association with Argonaute. Collectively, these results demonstrate that tertiary structure-based modeling of miRNA interactions can reveal structural mechanisms not accessible with current secondary structure-based methods. PMID:23417009

Sources of Uncertainty in Predicting Land Surface Fluxes Using Diverse Data and Models

NASA Technical Reports Server (NTRS)

Dungan, Jennifer L.; Wang, Weile; Michaelis, Andrew; Votava, Petr; Nemani, Ramakrishma

2010-01-01

In the domain of predicting land surface fluxes, models are used to bring data from large observation networks and satellite remote sensing together to make predictions about present and future states of the Earth. Characterizing the uncertainty about such predictions is a complex process and one that is not yet fully understood. Uncertainty exists about initialization, measurement and interpolation of input variables; model parameters; model structure; and mixed spatial and temporal supports. Multiple models or structures often exist to describe the same processes. Uncertainty about structure is currently addressed by running an ensemble of different models and examining the distribution of model outputs. To illustrate structural uncertainty, a multi-model ensemble experiment we have been conducting using the Terrestrial Observation and Prediction System (TOPS) will be discussed. TOPS uses public versions of process-based ecosystem models that use satellite-derived inputs along with surface climate data and land surface characterization to produce predictions of ecosystem fluxes including gross and net primary production and net ecosystem exchange. Using the TOPS framework, we have explored the uncertainty arising from the application of models with different assumptions, structures, parameters, and variable definitions. With a small number of models, this only begins to capture the range of possible spatial fields of ecosystem fluxes. Few attempts have been made to systematically address the components of uncertainty in such a framework. We discuss the characterization of uncertainty for this approach including both quantifiable and poorly known aspects.

Rachis morphology cannot accurately predict the mechanical performance of primary feathers in extant (and therefore fossil) feathered flyers

NASA Astrophysics Data System (ADS)

Lees, John; Garner, Terence; Cooper, Glen; Nudds, Robert

2017-02-01

It was previously suggested that the flight ability of feathered fossils could be hypothesized from the diameter of their feather rachises. Central to the idea is the unvalidated assumption that the strength of a primary flight feather (i.e. its material and structural properties) may be consistently calculated from the external diameter of the feather rachis, which is the only dimension that is likely to relate to structural properties available from fossils. Here, using three-point bending tests, the relationship between feather structural properties (maximum bending moment, Mmax and Young's modulus, Ebend) and external morphological parameters (primary feather rachis length, diameter and second moment of area at the calamus) in 180 primary feathers from four species of bird of differing flight style was investigated. Intraspecifically, both Ebend and Mmax were strongly correlated with morphology, decreasing and increasing, respectively, with all three morphological measures. Without accounting for species, however, external morphology was a poor predictor of rachis structural properties, meaning that precise determination of aerial performance in extinct, feathered species from external rachis dimensions alone is not possible. Even if it were possible to calculate the second moment of area of the rachis, our data suggest that feather strength could still not be reliably estimated.

Fatigue as a cause, not a consequence of depression and daytime sleepiness: a cross-lagged analysis.

PubMed

Schönberger, Michael; Herrberg, Marlene; Ponsford, Jennie

2014-01-01

To examine the temporal relation between fatigue, depression, and daytime sleepiness after traumatic brain injury. Fatigue is a frequent and disabling consequence of traumatic brain injury (TBI). However, it is unclear whether fatigue is a primary consequence of the structural brain injury or a secondary consequence of injury-related sequelae such as depression and daytime sleepiness. Eighty-eight adults with complicated mild-severe TBI (69% male). Fatigue Severity Scale; depression subscale of the Hospital Anxiety and Depression Scale; Epworth Sleepiness scale at baseline and 6-month follow-up. A cross-lagged path analysis computed within a structural equation modeling framework revealed that fatigue was predictive of depression (β = .20, P < .05) and sleepiness (β = .25, P < .05). However, depression and sleepiness did not predict fatigue (P > .05). The results support the view of fatigue after TBI as "primary fatigue"-that is, a consequence of the structural brain injury rather than a secondary consequence of depression or daytime sleepiness. A rehabilitation approach that assists individuals with brain injury in learning to cope with their neuropsychological and physical limitations in everyday life might attenuate their experience with fatigue.

Computational study of β-N-acetylhexosaminidase from Talaromyces flavus, a glycosidase with high substrate flexibility.

PubMed

Kulik, Natallia; Slámová, Kristýna; Ettrich, Rüdiger; Křen, Vladimír

2015-01-28

β-N-Acetylhexosaminidase (GH20) from the filamentous fungus Talaromyces flavus, previously identified as a prominent enzyme in the biosynthesis of modified glycosides, lacks a high resolution three-dimensional structure so far. Despite of high sequence identity to previously reported Aspergillus oryzae and Penicilluim oxalicum β-N-acetylhexosaminidases, this enzyme tolerates significantly better substrate modification. Understanding of key structural features, prediction of effective mutants and potential substrate characteristics prior to their synthesis are of general interest. Computational methods including homology modeling and molecular dynamics simulations were applied to shad light on the structure-activity relationship in the enzyme. Primary sequence analysis revealed some variable regions able to influence difference in substrate affinity of hexosaminidases. Moreover, docking in combination with consequent molecular dynamics simulations of C-6 modified glycosides enabled us to identify the structural features required for accommodation and processing of these bulky substrates in the active site of hexosaminidase from T. flavus. To access the reliability of predictions on basis of the reported model, all results were confronted with available experimental data that demonstrated the principal correctness of the predictions as well as the model. The main variable regions in β-N-acetylhexosaminidases determining difference in modified substrate affinity are located close to the active site entrance and engage two loops. Differences in primary sequence and the spatial arrangement of these loops and their interplay with active site amino acids, reflected by interaction energies and dynamics, account for the different catalytic activity and substrate specificity of the various fungal and bacterial β-N-acetylhexosaminidases.

Modelling the effect of structural QSAR parameters on skin penetration using genetic programming

NASA Astrophysics Data System (ADS)

Chung, K. K.; Do, D. Q.

2010-09-01

In order to model relationships between chemical structures and biological effects in quantitative structure-activity relationship (QSAR) data, an alternative technique of artificial intelligence computing—genetic programming (GP)—was investigated and compared to the traditional method—statistical. GP, with the primary advantage of generating mathematical equations, was employed to model QSAR data and to define the most important molecular descriptions in QSAR data. The models predicted by GP agreed with the statistical results, and the most predictive models of GP were significantly improved when compared to the statistical models using ANOVA. Recently, artificial intelligence techniques have been applied widely to analyse QSAR data. With the capability of generating mathematical equations, GP can be considered as an effective and efficient method for modelling QSAR data.

Four structural risk factors identify most fibril-forming kappa light chains.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stevens, F. J.; Biosciences Division

2000-09-01

Antibody light chains (LCs) comprise the most structurally diverse family of proteins involved in amyloidosis. Many antibody LCs incorporate structural features that impair their stability and solubility, leading to their assembly into fibrils and to their subsequent pathological deposition when produced in excess during multiple myeloma and primary amyloidosis. The particular amino acid variations in antibody LCs that account for fibril formation and amyloidogenesis have not been identified. This study focuses on amyloidogenesis within the Kl family of human LCs. Reanalysis of the current database of primary structures of proteins from more than 100 patients who produced Kl LCS, 37more » of which were amyloidogenic, reveals apparent structural features that may contribute to amyloidosis. These features include loss of conserved residues or the gain of particular residues through mutation at sites involving a repertoire of approximately 20% of the amino acid positions in the light chain variable domain (V{sub L}). Moreover, 80% of all K1 amyloidogenic V{sub L}s are identifiable by the presence of at least one of three single-site substitutions or the acquisition of an N-linked glycosylation site through mutations. These findings suggest that it is feasible to predict fibril propensity by analysis of primary structure.« less

Kinact: a computational approach for predicting activating missense mutations in protein kinases.

PubMed

Rodrigues, Carlos H M; Ascher, David B; Pires, Douglas E V

2018-05-21

Protein phosphorylation is tightly regulated due to its vital role in many cellular processes. While gain of function mutations leading to constitutive activation of protein kinases are known to be driver events of many cancers, the identification of these mutations has proven challenging. Here we present Kinact, a novel machine learning approach for predicting kinase activating missense mutations using information from sequence and structure. By adapting our graph-based signatures, Kinact represents both structural and sequence information, which are used as evidence to train predictive models. We show the combination of structural and sequence features significantly improved the overall accuracy compared to considering either primary or tertiary structure alone, highlighting their complementarity. Kinact achieved a precision of 87% and 94% and Area Under ROC Curve of 0.89 and 0.92 on 10-fold cross-validation, and on blind tests, respectively, outperforming well established tools (P < 0.01). We further show that Kinact performs equally well on homology models built using templates with sequence identity as low as 33%. Kinact is freely available as a user-friendly web server at http://biosig.unimelb.edu.au/kinact/.

Chemical Structural Novelty: On-Targets and Off-Targets

PubMed Central

Yera, Emmanuel R.; Cleves, Ann. E.; Jain, Ajay N.

2011-01-01

Drug structures may be quantitatively compared based on 2D topological structural considerations and based on 3D characteristics directly related to binding. A framework for combining multiple similarity computations is presented along with its systematic application to 358 drugs with overlapping pharmacology. Given a new molecule along with a set of molecules sharing some biological effect, a single score based on comparison to the known set is produced, reflecting either 2D similarity, 3D similarity, or their combination. For prediction of primary targets, the benefit of 3D over 2D was relatively small, but for prediction of off-targets, the added benefit was large. In addition to assessing prediction, the relationship between chemical similarity and pharmacological novelty was studied. Drug pairs that shared high 3D similarity but low 2D similarity (i.e. a novel scaffold) were shown to be much more likely to exhibit pharmacologically relevant differences in terms of specific protein target modulation. PMID:21916467

Geometrically Nonlinear Static Analysis of 3D Trusses Using the Arc-Length Method

NASA Technical Reports Server (NTRS)

Hrinda, Glenn A.

2006-01-01

Rigorous analysis of geometrically nonlinear structures demands creating mathematical models that accurately include loading and support conditions and, more importantly, model the stiffness and response of the structure. Nonlinear geometric structures often contain critical points with snap-through behavior during the response to large loads. Studying the post buckling behavior during a portion of a structure's unstable load history may be necessary. Primary structures made from ductile materials will stretch enough prior to failure for loads to redistribute producing sudden and often catastrophic collapses that are difficult to predict. The responses and redistribution of the internal loads during collapses and possible sharp snap-back of structures have frequently caused numerical difficulties in analysis procedures. The presence of critical stability points and unstable equilibrium paths are major difficulties that numerical solutions must pass to fully capture the nonlinear response. Some hurdles still exist in finding nonlinear responses of structures under large geometric changes. Predicting snap-through and snap-back of certain structures has been difficult and time consuming. Also difficult is finding how much load a structure may still carry safely. Highly geometrically nonlinear responses of structures exhibiting complex snap-back behavior are presented and analyzed with a finite element approach. The arc-length method will be reviewed and shown to predict the proper response and follow the nonlinear equilibrium path through limit points.

SMARTIV: combined sequence and structure de-novo motif discovery for in-vivo RNA binding data.

PubMed

Polishchuk, Maya; Paz, Inbal; Yakhini, Zohar; Mandel-Gutfreund, Yael

2018-05-25

Gene expression regulation is highly dependent on binding of RNA-binding proteins (RBPs) to their RNA targets. Growing evidence supports the notion that both RNA primary sequence and its local secondary structure play a role in specific Protein-RNA recognition and binding. Despite the great advance in high-throughput experimental methods for identifying sequence targets of RBPs, predicting the specific sequence and structure binding preferences of RBPs remains a major challenge. We present a novel webserver, SMARTIV, designed for discovering and visualizing combined RNA sequence and structure motifs from high-throughput RNA-binding data, generated from in-vivo experiments. The uniqueness of SMARTIV is that it predicts motifs from enriched k-mers that combine information from ranked RNA sequences and their predicted secondary structure, obtained using various folding methods. Consequently, SMARTIV generates Position Weight Matrices (PWMs) in a combined sequence and structure alphabet with assigned P-values. SMARTIV concisely represents the sequence and structure motif content as a single graphical logo, which is informative and easy for visual perception. SMARTIV was examined extensively on a variety of high-throughput binding experiments for RBPs from different families, generated from different technologies, showing consistent and accurate results. Finally, SMARTIV is a user-friendly webserver, highly efficient in run-time and freely accessible via http://smartiv.technion.ac.il/.

Extending (Q)SARs to incorporate proprietary knowledge for regulatory purposes: A case study using aromatic amine mutagenicity.

PubMed

Ahlberg, Ernst; Amberg, Alexander; Beilke, Lisa D; Bower, David; Cross, Kevin P; Custer, Laura; Ford, Kevin A; Van Gompel, Jacky; Harvey, James; Honma, Masamitsu; Jolly, Robert; Joossens, Elisabeth; Kemper, Raymond A; Kenyon, Michelle; Kruhlak, Naomi; Kuhnke, Lara; Leavitt, Penny; Naven, Russell; Neilan, Claire; Quigley, Donald P; Shuey, Dana; Spirkl, Hans-Peter; Stavitskaya, Lidiya; Teasdale, Andrew; White, Angela; Wichard, Joerg; Zwickl, Craig; Myatt, Glenn J

2016-06-01

Statistical-based and expert rule-based models built using public domain mutagenicity knowledge and data are routinely used for computational (Q)SAR assessments of pharmaceutical impurities in line with the approach recommended in the ICH M7 guideline. Knowledge from proprietary corporate mutagenicity databases could be used to increase the predictive performance for selected chemical classes as well as expand the applicability domain of these (Q)SAR models. This paper outlines a mechanism for sharing knowledge without the release of proprietary data. Primary aromatic amine mutagenicity was selected as a case study because this chemical class is often encountered in pharmaceutical impurity analysis and mutagenicity of aromatic amines is currently difficult to predict. As part of this analysis, a series of aromatic amine substructures were defined and the number of mutagenic and non-mutagenic examples for each chemical substructure calculated across a series of public and proprietary mutagenicity databases. This information was pooled across all sources to identify structural classes that activate or deactivate aromatic amine mutagenicity. This structure activity knowledge, in combination with newly released primary aromatic amine data, was incorporated into Leadscope's expert rule-based and statistical-based (Q)SAR models where increased predictive performance was demonstrated. Copyright © 2016 Elsevier Inc. All rights reserved.

Density functional theory in the solid state

PubMed Central

Hasnip, Philip J.; Refson, Keith; Probert, Matt I. J.; Yates, Jonathan R.; Clark, Stewart J.; Pickard, Chris J.

2014-01-01

Density functional theory (DFT) has been used in many fields of the physical sciences, but none so successfully as in the solid state. From its origins in condensed matter physics, it has expanded into materials science, high-pressure physics and mineralogy, solid-state chemistry and more, powering entire computational subdisciplines. Modern DFT simulation codes can calculate a vast range of structural, chemical, optical, spectroscopic, elastic, vibrational and thermodynamic phenomena. The ability to predict structure–property relationships has revolutionized experimental fields, such as vibrational and solid-state NMR spectroscopy, where it is the primary method to analyse and interpret experimental spectra. In semiconductor physics, great progress has been made in the electronic structure of bulk and defect states despite the severe challenges presented by the description of excited states. Studies are no longer restricted to known crystallographic structures. DFT is increasingly used as an exploratory tool for materials discovery and computational experiments, culminating in ex nihilo crystal structure prediction, which addresses the long-standing difficult problem of how to predict crystal structure polymorphs from nothing but a specified chemical composition. We present an overview of the capabilities of solid-state DFT simulations in all of these topics, illustrated with recent examples using the CASTEP computer program. PMID:24516184

Structural design methodologies for ceramic-based material systems

NASA Technical Reports Server (NTRS)

Duffy, Stephen F.; Chulya, Abhisak; Gyekenyesi, John P.

1991-01-01

One of the primary pacing items for realizing the full potential of ceramic-based structural components is the development of new design methods and protocols. The focus here is on low temperature, fast-fracture analysis of monolithic, whisker-toughened, laminated, and woven ceramic composites. A number of design models and criteria are highlighted. Public domain computer algorithms, which aid engineers in predicting the fast-fracture reliability of structural components, are mentioned. Emphasis is not placed on evaluating the models, but instead is focused on the issues relevant to the current state of the art.

Factors affecting the estimate of primary production from space

NASA Technical Reports Server (NTRS)

Balch, W. M.; Byrne, C. F.

1994-01-01

Remote sensing of primary production in the euphotic zone has been based mostly on visible-band and water-leaving radiance measured with the coastal zone color scanner. There are some robust, simple relationships for calculating integral production based on surface measurements, but they also require knowledge for photoadaptive parameters such as maximum photosynthesis which currently cannot be obtained from spave. A 17,000-station data set is used to show that space-based estimates of maximum photosynthesis could improve predictions of psi, the water column light utiliztion index, which is an important term in many primary productivity models. Temperature is also examined as a factor for predicting hydrographic structure and primary production. A simple model is used to relate temperature and maximum photosynthesis; the model incorporates (1) the positive relationship between maximum photosynthesis and temperature and (2) the strongly negative relationship between temperature and nitrate in the ocean (which directly affects maximum growth rates via nitrogen limitation). Since these two factors relate to carbon and nitrogen, 'balanced carbon/nitrogen assimilation' was calculated using the Redfield ratio, It is expected that the relationship between maximum balanced carbon assimilation versus temperature is concave-down, with the peak dependent on nitrate uptake kinetics, temperature-nitrate relationships,a nd the carbon chlorophyll ration. These predictions were compared with the sea truth data. The minimum turnover time for nitrate was also calculated using this approach. Lastly, sea surface temperature gradients were used to predict the slope of isotherms (a proxy for the slope of isopycnals in many waters). Sea truth data show that at size scales of several hundred kilometers, surface temperature gradients can provide information on the slope of isotherms in the top 200 m of the water column. This is directly relevant to the supply of nutrients into the surface mixed layer, which is useful for predicting integral biomass and primary production.

Learning the Relationship between the Primary Structure of HIV Envelope Glycoproteins and Neutralization Activity of Particular Antibodies by Using Artificial Neural Networks

PubMed Central

Buiu, Cătălin; Putz, Mihai V.; Avram, Speranta

2016-01-01

The dependency between the primary structure of HIV envelope glycoproteins (ENV) and the neutralization data for given antibodies is very complicated and depends on a large number of factors, such as the binding affinity of a given antibody for a given ENV protein, and the intrinsic infection kinetics of the viral strain. This paper presents a first approach to learning these dependencies using an artificial feedforward neural network which is trained to learn from experimental data. The results presented here demonstrate that the trained neural network is able to generalize on new viral strains and to predict reliable values of neutralizing activities of given antibodies against HIV-1. PMID:27727189

Trophic structure of coastal Antarctic food webs associated with changes in sea ice and food supply.

PubMed

Norkko, A; Thrush, S F; Cummings, V J; Gibbs, M M; Andrew, N L; Norkko, J; Schwarz, A M

2007-11-01

Predicting the dynamics of ecosystems requires an understanding of how trophic interactions respond to environmental change. In Antarctic marine ecosystems, food web dynamics are inextricably linked to sea ice conditions that affect the nature and magnitude of primary food sources available to higher trophic levels. Recent attention on the changing sea ice conditions in polar seas highlights the need to better understand how marine food webs respond to changes in such broad-scale environmental drivers. This study investigated the importance of sea ice and advected primary food sources to the structure of benthic food webs in coastal Antarctica. We compared the isotopic composition of several seafloor taxa (including primary producers and invertebrates with a variety of feeding modes) that are widely distributed in the Antarctic. We assessed shifts in the trophic role of numerically dominant benthic omnivores at five coastal Ross Sea locations. These locations vary in primary productivity and food availability, due to their different levels of sea ice cover, and proximity to polynyas and advected primary production. The delta15N signatures and isotope mixing model results for the bivalves Laternula elliptica and Adamussium colbecki and the urchin Sterechinus neumeyeri indicate a shift from consumption of a higher proportion of detritus at locations with more permanent sea ice in the south to more freshly produced algal material associated with proximity to ice-free water in the north and east. The detrital pathways utilized by many benthic species may act to dampen the impacts of large seasonal fluctuations in the availability of primary production. The limiting relationship between sea ice distribution and in situ primary productivity emphasizes the role of connectivity and spatial subsidies of organic matter in fueling the food web. Our results begin to provide a basis for predicting how benthic ecosystems will respond to changes in sea ice persistence and extent along environmental gradients in the high Antarctic.

Prediction of redox-sensitive cysteines using sequential distance and other sequence-based features.

PubMed

Sun, Ming-An; Zhang, Qing; Wang, Yejun; Ge, Wei; Guo, Dianjing

2016-08-24

Reactive oxygen species can modify the structure and function of proteins and may also act as important signaling molecules in various cellular processes. Cysteine thiol groups of proteins are particularly susceptible to oxidation. Meanwhile, their reversible oxidation is of critical roles for redox regulation and signaling. Recently, several computational tools have been developed for predicting redox-sensitive cysteines; however, those methods either only focus on catalytic redox-sensitive cysteines in thiol oxidoreductases, or heavily depend on protein structural data, thus cannot be widely used. In this study, we analyzed various sequence-based features potentially related to cysteine redox-sensitivity, and identified three types of features for efficient computational prediction of redox-sensitive cysteines. These features are: sequential distance to the nearby cysteines, PSSM profile and predicted secondary structure of flanking residues. After further feature selection using SVM-RFE, we developed Redox-Sensitive Cysteine Predictor (RSCP), a SVM based classifier for redox-sensitive cysteine prediction using primary sequence only. Using 10-fold cross-validation on RSC758 dataset, the accuracy, sensitivity, specificity, MCC and AUC were estimated as 0.679, 0.602, 0.756, 0.362 and 0.727, respectively. When evaluated using 10-fold cross-validation with BALOSCTdb dataset which has structure information, the model achieved performance comparable to current structure-based method. Further validation using an independent dataset indicates it is robust and of relatively better accuracy for predicting redox-sensitive cysteines from non-enzyme proteins. In this study, we developed a sequence-based classifier for predicting redox-sensitive cysteines. The major advantage of this method is that it does not rely on protein structure data, which ensures more extensive application compared to other current implementations. Accurate prediction of redox-sensitive cysteines not only enhances our understanding about the redox sensitivity of cysteine, it may also complement the proteomics approach and facilitate further experimental investigation of important redox-sensitive cysteines.

Veering and nonlinear interactions of a clamped beam in bending and torsion

NASA Astrophysics Data System (ADS)

Ehrhardt, David A.; Hill, Thomas L.; Neild, Simon A.; Cooper, Jonathan E.

2018-03-01

Understanding the linear and nonlinear dynamic behaviour of beams is critical for the design of many engineering structures such as spacecraft antennae, aircraft wings, and turbine blades. When the eigenvalues of such structures are closely-spaced, nonlinearity may lead to interactions between the underlying linear normal modes (LNMs). This work considers a clamped-clamped beam which exhibits nonlinear behaviour due to axial tension from large amplitudes of deformation. An additional cross-beam, mounted transversely and with a movable mass at each tip, allows tuning of the primary torsion LNM such that it is close to the primary bending LNM. Perturbing the location of one mass relative to that of the other leads to veering between the eigenvalues of the bending and torsion LNMs. For a number of selected geometries in the region of veering, a nonlinear reduced order model (NLROM) is created and the nonlinear normal modes (NNMs) are used to describe the underlying nonlinear behaviour of the structure. The relationship between the 'closeness' of the eigenvalues and the nonlinear dynamic behaviour is demonstrated in the NNM backbone curves, and veering-like behaviour is observed. Finally, the forced and damped dynamics of the structure are predicted using several analytical and numerical tools and are compared to experimental measurements. As well as showing a good agreement between the predicted and measured responses, phenomena such as a 1:1 internal resonance and quasi-periodic behaviour are identified.

Long-term bed degradation in Maryland streams (Phase III, Part 2) : urban streams in the Piedmont Plateau Province : research summary.

DOT National Transportation Integrated Search

2017-02-01

The purpose of this study was to improve predictions of LTBD in Maryland streams through the measurement and analysis of stream bed and waterway structure survey data and bridge plans. A primary objective was the development of equations for estimati...

Dutch outcome in implantable cardioverter-defibrillator therapy (DO-IT): registry design and baseline characteristics of a prospective observational cohort study to predict appropriate indication for implantable cardioverter-defibrillator.

PubMed

van Barreveld, M; Dijkgraaf, M G W; Hulleman, M; Boersma, L V A; Delnoy, P P H M; Meine, M; Tuinenburg, A E; Theuns, D A M J; van der Voort, P H; Kimman, G P; Buskens, E; Tijssen, J P G; Bruinsma, N; Verstraelen, T E; Zwinderman, A H; van Dessel, P H F M; Wilde, A A M

2017-10-01

Implantable cardioverter-defibrillators (ICDs) are widely used for the prevention of sudden cardiac death. At present, both clinical benefit and cost-effectiveness of ICD therapy in primary prevention patients are topics of discussion, as only a minority of these patients will eventually receive appropriate ICD therapy. The DO-IT Registry is a nationwide prospective cohort with a target enrolment of 1,500 primary prevention ICD patients with reduced left ventricular function in a setting of structural heart disease. The primary outcome measures are death and appropriate ICD therapy for ventricular tachyarrhythmias. Secondary outcome measures are inappropriate ICD therapy, death of any cause, hospitalisation for ICD related complications and for cardiovascular reasons. As of December 2016, data on demographic, clinical, and ICD characteristics of 1,468 patients have been collected. Follow-up will continue up to 24 months after inclusion of the last patient. During follow-up, clinical and ICD data are collected based on the normal follow-up of these patients, assuming ICD interrogations take place every six months and clinical follow-up is once a year. At baseline, the mean age was 66 (standard deviation [SD] 10) years and 27% were women. The DO-IT Registry represents a real-world nationwide cohort of patients receiving ICDs for primary prevention of sudden cardiac death with reduced left ventricular function in a setting of structural heart disease. The registry investigates the efficacy of the current practice and aims to develop prediction rules to identify subgroups who will not (sufficiently) benefit from ICD implantation and to provide results regarding costs and budget impact of targeted supply of primary preventions ICDs.

Implementation of brief alcohol interventions by nurses in primary care: do non-clinical factors influence practice?

PubMed

Lock, Catherine A; Kaner, Eileen F S

2004-06-01

In the UK, GPs and practice nurses selectively provide brief alcohol interventions to risk drinkers. GPs' provision of a brief alcohol intervention can be predicted by patient characteristics, practitioner characteristics and structural factors such as the features of the practice and how it is organized. However, much less is known about possible modifiers of nurse practice. Our aim was to investigate if patient characteristics, nurse characteristics and practice factors influence provision of a brief alcohol intervention by practice nurses in primary health care. One hundred and twenty-eight practice nurses who had implemented a brief alcohol intervention programme in a previous trial based in the North of England were requested to screen adults presenting to their surgery and follow a structured protocol to give a brief intervention (5 min of advice plus an information booklet) to all 'risk' drinkers. Anonymized carbon copies of 5541 completed Alcohol Use Disorders Identification Test (AUDIT) screening questionnaires were collected after a 3-month implementation period and analysed by logistic regression analysis. Although AUDIT identified 1500 'risk' drinkers, only 926 (62%) received a brief intervention. Logistic regression modelling showed that patients' risk status as measured by AUDIT score was the most influential predictor of a brief intervention by practice nurses. However, risk drinkers who were most likely to receive a brief intervention were male. Patients' age or social class did not independently predict a brief intervention. The multilevel model was unable to identify any independent nurse characteristics that could predict a brief intervention, but indicated significant variation between nurses in their tendency to offer the intervention to patients. No structural factors were found to be positively associated with selective provision. Patient and nurse factors contributed to the selective provision of a brief intervention in primary care. If patients are to experience the beneficial effects of a brief alcohol intervention, then there is a need to improve the accuracy of delivery.

Multidisciplinary Modeling Software for Analysis, Design, and Optimization of HRRLS Vehicles

NASA Technical Reports Server (NTRS)

Spradley, Lawrence W.; Lohner, Rainald; Hunt, James L.

2011-01-01

The concept for Highly Reliable Reusable Launch Systems (HRRLS) under the NASA Hypersonics project is a two-stage-to-orbit, horizontal-take-off / horizontal-landing, (HTHL) architecture with an air-breathing first stage. The first stage vehicle is a slender body with an air-breathing propulsion system that is highly integrated with the airframe. The light weight slender body will deflect significantly during flight. This global deflection affects the flow over the vehicle and into the engine and thus the loads and moments on the vehicle. High-fidelity multi-disciplinary analyses that accounts for these fluid-structures-thermal interactions are required to accurately predict the vehicle loads and resultant response. These predictions of vehicle response to multi physics loads, calculated with fluid-structural-thermal interaction, are required in order to optimize the vehicle design over its full operating range. This contract with ResearchSouth addresses one of the primary objectives of the Vehicle Technology Integration (VTI) discipline: the development of high-fidelity multi-disciplinary analysis and optimization methods and tools for HRRLS vehicles. The primary goal of this effort is the development of an integrated software system that can be used for full-vehicle optimization. This goal was accomplished by: 1) integrating the master code, FEMAP, into the multidiscipline software network to direct the coupling to assure accurate fluid-structure-thermal interaction solutions; 2) loosely-coupling the Euler flow solver FEFLO to the available and proven aeroelasticity and large deformation (FEAP) code; 3) providing a coupled Euler-boundary layer capability for rapid viscous flow simulation; 4) developing and implementing improved Euler/RANS algorithms into the FEFLO CFD code to provide accurate shock capturing, skin friction, and heat-transfer predictions for HRRLS vehicles in hypersonic flow, 5) performing a Reynolds-averaged Navier-Stokes computation on an HRRLS configuration; 6) integrating the RANS solver with the FEAP code for coupled fluid-structure-thermal capability; and 7) integrating the existing NASA SRGULL propulsion flow path prediction software with the FEFLO software for quasi-3D propulsion flow path predictions, 8) improving and integrating into the network, an existing adjoint-based design optimization code.

Strength of figure-ground activity in monkey primary visual cortex predicts saccadic reaction time in a delayed detection task.

PubMed

Supèr, Hans; Lamme, Victor A F

2007-06-01

When and where are decisions made? In the visual system a saccade, which is a fast shift of gaze toward a target in the visual scene, is the behavioral outcome of a decision. Current neurophysiological data and reaction time models show that saccadic reaction times are determined by a build-up of activity in motor-related structures, such as the frontal eye fields. These structures depend on the sensory evidence of the stimulus. Here we use a delayed figure-ground detection task to show that late modulated activity in the visual cortex (V1) predicts saccadic reaction time. This predictive activity is part of the process of figure-ground segregation and is specific for the saccade target location. These observations indicate that sensory signals are directly involved in the decision of when and where to look.

Neuroendocrine mechanisms underlying behavioral stability: implications for the evolutionary origin of personality.

PubMed

Duckworth, Renée A

2015-12-01

Personality traits are behaviors that show limited flexibility over time and across contexts, and thus understanding their origin requires an understanding of what limits behavioral flexibility. Here, I suggest that insight into the evolutionary origin of personality traits requires determining the relative importance of selection and constraint in producing limits to behavioral flexibility. Natural selection as the primary cause of limits to behavioral flexibility assumes that the default state of behavior is one of high flexibility and predicts that personality variation arises through evolution of buffering mechanisms to stabilize behavioral expression, whereas the constraint hypothesis assumes that the default state is one of limited flexibility and predicts that the neuroendocrine components that underlie personality variation are those most constrained in flexibility. Using recent work on the neurobiology of sensitive periods and maternal programming of offspring behavior, I show that some of the most stable aspects of the neuroendocrine system are structural components and maternally induced epigenetic effects. Evidence of numerous constraints to changes in structural features of the neuroendocrine system and far fewer constraints to flexibility of epigenetic systems suggests that structural constraints play a primary role in the origin of behavioral stability and that epigenetic programming may be more important in generating adaptive variation among individuals. © 2015 New York Academy of Sciences.

TANGLE: Two-Level Support Vector Regression Approach for Protein Backbone Torsion Angle Prediction from Primary Sequences

PubMed Central

Song, Jiangning; Tan, Hao; Wang, Mingjun; Webb, Geoffrey I.; Akutsu, Tatsuya

2012-01-01

Protein backbone torsion angles (Phi) and (Psi) involve two rotation angles rotating around the Cα-N bond (Phi) and the Cα-C bond (Psi). Due to the planarity of the linked rigid peptide bonds, these two angles can essentially determine the backbone geometry of proteins. Accordingly, the accurate prediction of protein backbone torsion angle from sequence information can assist the prediction of protein structures. In this study, we develop a new approach called TANGLE (Torsion ANGLE predictor) to predict the protein backbone torsion angles from amino acid sequences. TANGLE uses a two-level support vector regression approach to perform real-value torsion angle prediction using a variety of features derived from amino acid sequences, including the evolutionary profiles in the form of position-specific scoring matrices, predicted secondary structure, solvent accessibility and natively disordered region as well as other global sequence features. When evaluated based on a large benchmark dataset of 1,526 non-homologous proteins, the mean absolute errors (MAEs) of the Phi and Psi angle prediction are 27.8° and 44.6°, respectively, which are 1% and 3% respectively lower than that using one of the state-of-the-art prediction tools ANGLOR. Moreover, the prediction of TANGLE is significantly better than a random predictor that was built on the amino acid-specific basis, with the p-value<1.46e-147 and 7.97e-150, respectively by the Wilcoxon signed rank test. As a complementary approach to the current torsion angle prediction algorithms, TANGLE should prove useful in predicting protein structural properties and assisting protein fold recognition by applying the predicted torsion angles as useful restraints. TANGLE is freely accessible at http://sunflower.kuicr.kyoto-u.ac.jp/~sjn/TANGLE/. PMID:22319565

Spray formation processes of impinging jet injectors

NASA Technical Reports Server (NTRS)

Anderson, W. E.; Ryan, H. M.; Pal, S.; Santoro, R. J.

1993-01-01

A study examining impinging liquid jets has been underway to determine physical mechanisms responsible for combustion instabilities in liquid bi-propellant rocket engines. Primary atomization has been identified as an important process. Measurements of atomization length, wave structure, and drop size and velocity distribution were made under various ambient conditions. Test parameters included geometric effects and flow effects. It was observed that pre-impingement jet conditions, specifically whether they were laminar or turbulent, had the major effect on primary atomization. Comparison of the measurements with results from a two dimensional linear aerodynamic stability model of a thinning, viscous sheet were made. Measured turbulent impinging jet characteristics were contrary to model predictions; the structure of waves generated near the point of jet impingement were dependent primarily on jet diameter and independent of jet velocity. It has been postulated that these impact waves are related to pressure and momentum fluctuations near the impingement region and control the eventual disintegration of the liquid sheet into ligaments. Examination of the temporal characteristics of primary atomization (ligament shedding frequency) strongly suggests that the periodic nature of primary atomization is a key process in combustion instability.

Predicting recreational fishing use of offshore petroleum platforms in the Central Gulf of Mexico

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gordon, W.R. Jr.

1987-01-01

This study is based on the premise that properly sited artificial reefs for optimal human recreational use, a predictive model based upon the marine travel patterns and behavior of marine recreational fishermen, is needed. This research used data gathered from a previous study that addressed the recreational fishing use of offshore oil and gas structures (Ditton and Auyong 1984); on-site data were also collected. The primary research objective was to generate a predictive model that can be applied to artificial-reef development efforts elsewhere. This study investigated the recreational-user patterns of selected petroleum platforms structures in the Central Gulf of Mexico.more » The petroleum structures offshore from the Louisiana coastline provide a unique research tool. Although intended to facilitate the exploration and recovery of hydrocarbons, petroleum platforms also serve as defacto artificial reefs, providing habitat for numerous species of fish and other marine life. Petroleum platforms were found to be the principal fishing destinations within the study area. On-site findings reveal that marine recreational fishermen were as mobile on water, as they are on land. On-site findings were used to assist in the development of a predictive model.« less

Higher impact of female than male migration on population structure in large mammals.

PubMed

Tiedemann, R; Hardy, O; Vekemans, X; Milinkovitch, M C

2000-08-01

We simulated large mammal populations using an individual-based stochastic model under various sex-specific migration schemes and life history parameters from the blue whale and the Asian elephant. Our model predicts that genetic structure at nuclear loci is significantly more influenced by female than by male migration. We identified requisite comigration of mother and offspring during gravidity and lactation as the primary cause of this phenomenon. In addition, our model predicts that the common assumption that geographical patterns of mitochondrial DNA (mtDNA) could be translated into female migration rates (Nmf) will cause biased estimates of maternal gene flow when extensive male migration occurs and male mtDNA haplotypes are included in the analysis.

Energy efficient engine fan component detailed design report

NASA Technical Reports Server (NTRS)

Halle, J. E.; Michael, C. J.

1981-01-01

The fan component which was designed for the energy efficient engine is an advanced high performance, single stage system and is based on technology advancements in aerodynamics and structure mechanics. Two fan components were designed, both meeting the integrated core/low spool engine efficiency goal of 84.5%. The primary configuration, envisioned for a future flight propulsion system, features a shroudless, hollow blade and offers a predicted efficiency of 87.3%. A more conventional blade was designed, as a back up, for the integrated core/low spool demonstrator engine. The alternate blade configuration has a predicted efficiency of 86.3% for the future flight propulsion system. Both fan configurations meet goals established for efficiency surge margin, structural integrity and durability.

Development of design and analysis methodology for composite bolted joints

NASA Astrophysics Data System (ADS)

Grant, Peter; Sawicki, Adam

1991-05-01

This paper summarizes work performed to develop composite joint design methodology for use on rotorcraft primary structure, determine joint characteristics which affect joint bearing and bypass strength, and develop analytical methods for predicting the effects of such characteristics in structural joints. Experimental results have shown that bearing-bypass interaction allowables cannot be defined using a single continuous function due to variance of failure modes for different bearing-bypass ratios. Hole wear effects can be significant at moderate stress levels and should be considered in the development of bearing allowables. A computer program has been developed and has successfully predicted bearing-bypass interaction effects for the (0/+/-45/90) family of laminates using filled hole and unnotched test data.

Bipolar radiofrequency ablation of spinal tumors: predictability, safety and outcome.

PubMed

Gazis, Angelos N; Beuing, Oliver; Franke, Jörg; Jöllenbeck, Boris; Skalej, Martin

2014-04-01

Bone metastases are often the cause of tumor-associated pain and reduction of quality of life. For patients that cannot be treated by surgery, a local minimally invasive therapy such as radiofrequency ablation can be a useful option. In cases in which tumorous masses are adjacent to vulnerable structures, the monopolar radiofrequency can cause severe neuronal damage because of the unpredictability of current flow. The aim of this study is to show that the bipolar radiofrequency ablation provides an opportunity to safely treat such spinal lesions because of precise predictability of the emerging ablation zone. Prospective cohort study of 36 patients undergoing treatment at a single institution. Thirty-six patients in advanced tumor stage with primary or secondary tumor involvement of spine undergoing radiofrequency ablation. Prediction of emerging ablation zone. Clinical outcome of treated patients. X-ray-controlled treatment of 39 lesions by bipolar radiofrequency ablation. Magnetic resonance imaging was performed pre- and postinterventionally. Patients were observed clinically during their postinterventional stay. The extent of the ablation zones was predictable to the millimeter because it did not cross the peri-interventional planned dorsal and ventral boundaries in any case. No complications were observed. Ablation of tumorous masses adjacent to vulnerable structures is feasible and predictable by using the bipolar radiofrequency ablation. Damage of neuronal structures can be avoided through precise prediction of the ablation area. Copyright © 2014 Elsevier Inc. All rights reserved.

Structural parameterization and functional prediction of antigenic polypeptome sequences with biological activity through quantitative sequence-activity models (QSAM) by molecular electronegativity edge-distance vector (VMED).

PubMed

Li, ZhiLiang; Wu, ShiRong; Chen, ZeCong; Ye, Nancy; Yang, ShengXi; Liao, ChunYang; Zhang, MengJun; Yang, Li; Mei, Hu; Yang, Yan; Zhao, Na; Zhou, Yuan; Zhou, Ping; Xiong, Qing; Xu, Hong; Liu, ShuShen; Ling, ZiHua; Chen, Gang; Li, GenRong

2007-10-01

Only from the primary structures of peptides, a new set of descriptors called the molecular electronegativity edge-distance vector (VMED) was proposed and applied to describing and characterizing the molecular structures of oligopeptides and polypeptides, based on the electronegativity of each atom or electronic charge index (ECI) of atomic clusters and the bonding distance between atom-pairs. Here, the molecular structures of antigenic polypeptides were well expressed in order to propose the automated technique for the computerized identification of helper T lymphocyte (Th) epitopes. Furthermore, a modified MED vector was proposed from the primary structures of polypeptides, based on the ECI and the relative bonding distance of the fundamental skeleton groups. The side-chains of each amino acid were here treated as a pseudo-atom. The developed VMED was easy to calculate and able to work. Some quantitative model was established for 28 immunogenic or antigenic polypeptides (AGPP) with 14 (1-14) A(d) and 14 other restricted activities assigned as "1"(+) and "0"(-), respectively. The latter comprised 6 A(b)(15-20), 3 A(k)(21-23), 2 E(k)(24-26), 2 H-2(k)(27 and 28) restricted sequences. Good results were obtained with 90% correct classification (only 2 wrong ones for 20 training samples) and 100% correct prediction (none wrong for 8 testing samples); while contrastively 100% correct classification (none wrong for 20 training samples) and 88% correct classification (1 wrong for 8 testing samples). Both stochastic samplings and cross validations were performed to demonstrate good performance. The described method may also be suitable for estimation and prediction of classes I and II for major histocompatibility antigen (MHC) epitope of human. It will be useful in immune identification and recognition of proteins and genes and in the design and development of subunit vaccines. Several quantitative structure activity relationship (QSAR) models were developed for various oligopeptides and polypeptides including 58 dipeptides and 31 pentapeptides with angiotensin converting enzyme (ACE) inhibition by multiple linear regression (MLR) method. In order to explain the ability to characterize molecular structure of polypeptides, a molecular modeling investigation on QSAR was performed for functional prediction of polypeptide sequences with antigenic activity and heptapeptide sequences with tachykinin activity through quantitative sequence-activity models (QSAMs) by the molecular electronegativity edge-distance vector (VMED). The results showed that VMED exhibited both excellent structural selectivity and good activity prediction. Moreover, the results showed that VMED behaved quite well for both QSAR and QSAM of poly-and oligopeptides, which exhibited both good estimation ability and prediction power, equal to or better than those reported in the previous references. Finally, a preliminary conclusion was drawn: both classical and modified MED vectors were very useful structural descriptors. Some suggestions were proposed for further studies on QSAR/QSAM of proteins in various fields.

Computational modeling of RNA 3D structures, with the aid of experimental restraints

PubMed Central

Magnus, Marcin; Matelska, Dorota; Łach, Grzegorz; Chojnowski, Grzegorz; Boniecki, Michal J; Purta, Elzbieta; Dawson, Wayne; Dunin-Horkawicz, Stanislaw; Bujnicki, Janusz M

2014-01-01

In addition to mRNAs whose primary function is transmission of genetic information from DNA to proteins, numerous other classes of RNA molecules exist, which are involved in a variety of functions, such as catalyzing biochemical reactions or performing regulatory roles. In analogy to proteins, the function of RNAs depends on their structure and dynamics, which are largely determined by the ribonucleotide sequence. Experimental determination of high-resolution RNA structures is both laborious and difficult, and therefore, the majority of known RNAs remain structurally uncharacterized. To address this problem, computational structure prediction methods were developed that simulate either the physical process of RNA structure formation (“Greek science” approach) or utilize information derived from known structures of other RNA molecules (“Babylonian science” approach). All computational methods suffer from various limitations that make them generally unreliable for structure prediction of long RNA sequences. However, in many cases, the limitations of computational and experimental methods can be overcome by combining these two complementary approaches with each other. In this work, we review computational approaches for RNA structure prediction, with emphasis on implementations (particular programs) that can utilize restraints derived from experimental analyses. We also list experimental approaches, whose results can be relatively easily used by computational methods. Finally, we describe case studies where computational and experimental analyses were successfully combined to determine RNA structures that would remain out of reach for each of these approaches applied separately. PMID:24785264

Features of Inner Structure of Placer Gold of the North-Eastern Part Siberian Platform

NASA Astrophysics Data System (ADS)

Gerasimov, Boris; Zhuravlev, Anatolii; Ivanov, Alexey

2017-12-01

Mineral and raw material base of placer and ore gold is based on prognosis evaluation, which allows to define promising areas regarding gold-bearing deposit prospecting. But there are some difficulties in gold primary source predicting and prospecting at the North-east Siberian platform, because the studied area is overlapped by thick cover of the Cenozoic deposits, where traditional methods of gold deposit prospecting are ineffective. In this connection, detailed study of typomorphic features of placer gold is important, because it contains key genetic information, necessary for development of mineralogical criteria of prognosis evaluation of ore gold content. Authors studied mineralogical-geochemical features of placer gold of the Anabar placer area for 15 years, with a view to identify indicators of gold, typical for different formation types of primary sources. This article presents results of these works. In placer regions, where primary sources of gold are not identified, there is need to study typomorphic features of placer gold, because it contains important genetic information, necessary for the development of mineralogical criteria of prognosis evaluation of ore gold content. Inner structures of gold from the Anabar placer region are studied, as one of the diagnostic typomorphic criteria as described in prominent method, developed by N.V. Petrovskaya [1980]. Etching of gold was carried out using reagent: HCl + HNO3 + FeCl3 × 6H2O + CrO3 +thioureat + water. Identified inner structures wer studied in details by means of scanning electron microscope JEOL JSM-6480LV. Two types of gold are identified according to the features of inner structure of placer gold of the Anabar region. First type - medium-high karat fine, well processed gold with significantly changed inner structure. This gold is allochthonous, which was redeposited many times from ancient intermediate reservoirs to younger deposits. Second type - low-medium karat, poorly rounded gold with unchanged inner structure. Poor roundness of gold particles and preservation of their primary inner structures indicate close proximity of primary source.

Acyl carrier protein structural classification and normal mode analysis

PubMed Central

Cantu, David C; Forrester, Michael J; Charov, Katherine; Reilly, Peter J

2012-01-01

All acyl carrier protein primary and tertiary structures were gathered into the ThYme database. They are classified into 16 families by amino acid sequence similarity, with members of the different families having sequences with statistically highly significant differences. These classifications are supported by tertiary structure superposition analysis. Tertiary structures from a number of families are very similar, suggesting that these families may come from a single distant ancestor. Normal vibrational mode analysis was conducted on experimentally determined freestanding structures, showing greater fluctuations at chain termini and loops than in most helices. Their modes overlap more so within families than between different families. The tertiary structures of three acyl carrier protein families that lacked any known structures were predicted as well. PMID:22374859

A structural equation modeling of executive functions, IQ and mathematical skills in primary students: Differential effects on number production, mental calculus and arithmetical problems.

PubMed

Arán Filippetti, Vanessa; Richaud, María Cristina

2017-10-01

Though the relationship between executive functions (EFs) and mathematical skills has been well documented, little is known about how both EFs and IQ differentially support diverse math domains in primary students. Inconsistency of results may be due to the statistical techniques employed, specifically, if the analysis is conducted with observed variables, i.e., regression analysis, or at the latent level, i.e., structural equation modeling (SEM). The current study explores the contribution of both EFs and IQ in mathematics through an SEM approach. A total of 118 8- to 12-year-olds were administered measures of EFs, crystallized (Gc) and fluid (Gf) intelligence, and math abilities (i.e., number production, mental calculus and arithmetical problem-solving). Confirmatory factor analysis (CFA) offered support for the three-factor solution of EFs: (1) working memory (WM), (2) shifting, and (3) inhibition. Regarding the relationship among EFs, IQ and math abilities, the results of the SEM analysis showed that (i) WM and age predict number production and mental calculus, and (ii) shifting and sex predict arithmetical problem-solving. In all of the SEM models, EFs partially or totally mediated the relationship between IQ, age and math achievement. These results suggest that EFs differentially supports math abilities in primary-school children and is a more significant predictor of math achievement than IQ level.

Distribution of cavity trees in midwestern old-growth and second-growth forests

Treesearch

Zhaofei Fan; Stephen R. Shifley; Martin A. Spetich; Frank R. Thompson; David R. Larsen

2003-01-01

We used classification and regression tree analysis to determine the primary variables associated with the occurrence of cavity trees and the hierarchical structure among those variables. We applied that information to develop logistic models predicting cavity tree probability as a function of diameter, species group, and decay class. Inventories of cavity abundance in...

Distribution of cavity trees in midwesternold-growth and second-growth forests

Treesearch

Zhaofei Fan; Stephen R. Shifley; Martin A. Spetich; Frank R., III Thompson; David R. Larsen

2003-01-01

We used classification and regression tree analysis to determine the primary variables associated with the occurrence of cavity trees and the hierarchical structure among those variables. We applied that information to develop logistic models predicting cavity tree probability as a function of diameter, species group, and decay class. Inventories of cavity abundance in...

Discrete return lidar-based prediction of leaf area index in two conifer forests

Treesearch

Jennifer L. R. Jensen; Karen S. Humes; Lee A. Vierling; Andrew T. Hudak

2008-01-01

Leaf area index (LAI) is a key forest structural characteristic that serves as a primary control for exchanges of mass and energy within a vegetated ecosystem. Most previous attempts to estimate LAI from remotely sensed data have relied on empirical relationships between field-measured observations and various spectral vegetation indices (SVIs) derived from optical...

R-chie: a web server and R package for visualizing RNA secondary structures

PubMed Central

Lai, Daniel; Proctor, Jeff R.; Zhu, Jing Yun A.; Meyer, Irmtraud M.

2012-01-01

Visually examining RNA structures can greatly aid in understanding their potential functional roles and in evaluating the performance of structure prediction algorithms. As many functional roles of RNA structures can already be studied given the secondary structure of the RNA, various methods have been devised for visualizing RNA secondary structures. Most of these methods depict a given RNA secondary structure as a planar graph consisting of base-paired stems interconnected by roundish loops. In this article, we present an alternative method of depicting RNA secondary structure as arc diagrams. This is well suited for structures that are difficult or impossible to represent as planar stem-loop diagrams. Arc diagrams can intuitively display pseudo-knotted structures, as well as transient and alternative structural features. In addition, they facilitate the comparison of known and predicted RNA secondary structures. An added benefit is that structure information can be displayed in conjunction with a corresponding multiple sequence alignments, thereby highlighting structure and primary sequence conservation and variation. We have implemented the visualization algorithm as a web server R-chie as well as a corresponding R package called R4RNA, which allows users to run the software locally and across a range of common operating systems. PMID:22434875

Characterizing primary refractory neuroblastoma: prediction of outcome by microscopic image analysis

NASA Astrophysics Data System (ADS)

Niazi, M. Khalid Khan; Weiser, Daniel A.; Pawel, Bruce R.; Gurcan, Metin N.

2015-03-01

Neuroblastoma is a childhood cancer that starts in very early forms of nerve cells found in an embryo or fetus. It is a highly lethal cancer of sympathetic nervous system that commonly affects children of age five or younger. It accounts for a disproportionate number of childhood cancer deaths and remains a difficult cancer to eradicate despite intensive treatment that includes chemotherapy, surgery, hematopoietic stem cell transplantation, radiation therapy and immunotherapy. A poorly characterized group of patients are the 15% with primary refractory neuroblastoma (PRN) which is uniformly lethal due to de novo chemotherapy resistance. The lack of response to therapy is currently assessed after multiple months of cytotoxic therapy, driving the critical need to develop pretreatment clinic-biological biomarkers that can guide precise and effective therapeutic strategies. Therefore, our guiding hypothesis is that PRN has distinct biological features present at diagnosis that can be identified for prediction modeling. During a visual analysis of PRN slides, stained with hematoxylin and eosin, we observed that patients who survived for less than three years contained large eosin-stained structures as compared to those who survived for greater than three years. So, our hypothesis is that the size of eosin stained structures can be used as a differentiating feature to characterize recurrence in neuroblastoma. To test this hypothesis, we developed an image analysis method that performs stain separation, followed by the detection of large structures stained with Eosin. On a set of 21 PRN slides, stained with hematoxylin and eosin, our image analysis method predicted the outcome with 85.7% accuracy.

HART-II Acoustic Predictions using a Coupled CFD/CSD Method

NASA Technical Reports Server (NTRS)

Boyd, D. Douglas, Jr.

2009-01-01

This paper documents results to date from the Rotorcraft Acoustic Characterization and Mitigation activity under the NASA Subsonic Rotary Wing Project. The primary goal of this activity is to develop a NASA rotorcraft impulsive noise prediction capability which uses first principles fluid dynamics and structural dynamics. During this effort, elastic blade motion and co-processing capabilities have been included in a recent version of the computational fluid dynamics code (CFD). The CFD code is loosely coupled to computational structural dynamics (CSD) code using new interface codes. The CFD/CSD coupled solution is then used to compute impulsive noise on a plane under the rotor using the Ffowcs Williams-Hawkings solver. This code system is then applied to a range of cases from the Higher Harmonic Aeroacoustic Rotor Test II (HART-II) experiment. For all cases presented, the full experimental configuration (i.e., rotor and wind tunnel sting mount) are used in the coupled CFD/CSD solutions. Results show good correlation between measured and predicted loading and loading time derivative at the only measured radial station. A contributing factor for a typically seen loading mean-value offset between measured data and predictions data is examined. Impulsive noise predictions on the measured microphone plane under the rotor compare favorably with measured mid-frequency noise for all cases. Flow visualization of the BL and MN cases shows that vortex structures generated in the prediction method are consist with measurements. Future application of the prediction method is discussed.

Isolation and in silico analysis of a novel H+-pyrophosphatase gene orthologue from the halophytic grass Leptochloa fusca

NASA Astrophysics Data System (ADS)

Rauf, Muhammad; Saeed, Nasir A.; Habib, Imran; Ahmed, Moddassir; Shahzad, Khurram; Mansoor, Shahid; Ali, Rashid

2017-02-01

Structure prediction can provide information about function and active sites of protein which helps to design new functional proteins. H+-pyrophosphatase is transmembrane protein involved in establishing proton motive force for active transport of Na+ across membrane by Na+/H+ antiporters. A full length novel H+-pyrophosphatase gene was isolated from halophytic grass Leptochloa fusca using RT-PCR and RACE method. Full length LfVP1 gene sequence of 2292 nucleotides encodes protein of 764 amino acids. DNA and protein sequences were used for characterization using bioinformatics tools. Various important potential sites were predicted by PROSITE webserver. Primary structural analysis showed LfVP1 as stable protein and Grand average hydropathy (GRAVY) indicated that LfVP1 protein has good hydrosolubility. Secondary structure analysis showed that LfVP1 protein sequence contains significant proportion of alpha helix and random coil. Protein membrane topology suggested the presence of 14 transmembrane domains and presence of catalytic domain in TM3. Three dimensional structure from LfVP1 protein sequence also indicated the presence of 14 transmembrane domains and hydrophobicity surface model showed amino acid hydrophobicity. Ramachandran plot showed that 98% amino acid residues were predicted in the favored region.

Predicting Spike Occurrence and Neuronal Responsiveness from LFPs in Primary Somatosensory Cortex

PubMed Central

Storchi, Riccardo; Zippo, Antonio G.; Caramenti, Gian Carlo; Valente, Maurizio; Biella, Gabriele E. M.

2012-01-01

Local Field Potentials (LFPs) integrate multiple neuronal events like synaptic inputs and intracellular potentials. LFP spatiotemporal features are particularly relevant in view of their applications both in research (e.g. for understanding brain rhythms, inter-areal neural communication and neronal coding) and in the clinics (e.g. for improving invasive Brain-Machine Interface devices). However the relation between LFPs and spikes is complex and not fully understood. As spikes represent the fundamental currency of neuronal communication this gap in knowledge strongly limits our comprehension of neuronal phenomena underlying LFPs. We investigated the LFP-spike relation during tactile stimulation in primary somatosensory (S-I) cortex in the rat. First we quantified how reliably LFPs and spikes code for a stimulus occurrence. Then we used the information obtained from our analyses to design a predictive model for spike occurrence based on LFP inputs. The model was endowed with a flexible meta-structure whose exact form, both in parameters and structure, was estimated by using a multi-objective optimization strategy. Our method provided a set of nonlinear simple equations that maximized the match between models and true neurons in terms of spike timings and Peri Stimulus Time Histograms. We found that both LFPs and spikes can code for stimulus occurrence with millisecond precision, showing, however, high variability. Spike patterns were predicted significantly above chance for 75% of the neurons analysed. Crucially, the level of prediction accuracy depended on the reliability in coding for the stimulus occurrence. The best predictions were obtained when both spikes and LFPs were highly responsive to the stimuli. Spike reliability is known to depend on neuron intrinsic properties (i.e. on channel noise) and on spontaneous local network fluctuations. Our results suggest that the latter, measured through the LFP response variability, play a dominant role. PMID:22586452

Predicting spike occurrence and neuronal responsiveness from LFPs in primary somatosensory cortex.

PubMed

Storchi, Riccardo; Zippo, Antonio G; Caramenti, Gian Carlo; Valente, Maurizio; Biella, Gabriele E M

2012-01-01

Local Field Potentials (LFPs) integrate multiple neuronal events like synaptic inputs and intracellular potentials. LFP spatiotemporal features are particularly relevant in view of their applications both in research (e.g. for understanding brain rhythms, inter-areal neural communication and neuronal coding) and in the clinics (e.g. for improving invasive Brain-Machine Interface devices). However the relation between LFPs and spikes is complex and not fully understood. As spikes represent the fundamental currency of neuronal communication this gap in knowledge strongly limits our comprehension of neuronal phenomena underlying LFPs. We investigated the LFP-spike relation during tactile stimulation in primary somatosensory (S-I) cortex in the rat. First we quantified how reliably LFPs and spikes code for a stimulus occurrence. Then we used the information obtained from our analyses to design a predictive model for spike occurrence based on LFP inputs. The model was endowed with a flexible meta-structure whose exact form, both in parameters and structure, was estimated by using a multi-objective optimization strategy. Our method provided a set of nonlinear simple equations that maximized the match between models and true neurons in terms of spike timings and Peri Stimulus Time Histograms. We found that both LFPs and spikes can code for stimulus occurrence with millisecond precision, showing, however, high variability. Spike patterns were predicted significantly above chance for 75% of the neurons analysed. Crucially, the level of prediction accuracy depended on the reliability in coding for the stimulus occurrence. The best predictions were obtained when both spikes and LFPs were highly responsive to the stimuli. Spike reliability is known to depend on neuron intrinsic properties (i.e. on channel noise) and on spontaneous local network fluctuations. Our results suggest that the latter, measured through the LFP response variability, play a dominant role.

The Infant with Aortic Arch Hypoplasia and Small Left Heart Structures: Echocardiographic Indices of Mitral and Aortic Hypoplasia Predicting Successful Biventricular Repair.

PubMed

Plymale, Jennifer M; Frommelt, Peter C; Nugent, Melodee; Simpson, Pippa; Tweddell, James S; Shillingford, Amanda J

2017-08-01

In infants with aortic arch hypoplasia and small left-sided cardiac structures, successful biventricular repair is dependent on the adequacy of the left-sided structures. Defining accurate thresholds of echocardiographic indices predictive of successful biventricular repair is paramount to achieving optimal outcomes. We sought to identify pre-operative echocardiographic indices of left heart size that predict intervention-free survival in infants with small left heart structures undergoing primary aortic arch repair to establish biventricular circulation (BVC). Infants ≤2 months undergoing aortic arch repair from 1999 to 2010 with aortic and/or mitral valve hypoplasia, (Z-score ≤-2) were included. Pre-operative and follow-up echocardiograms were reviewed. Primary outcome was successful biventricular circulation (BVC), defined as freedom from death, transplant, or single ventricular conversion at 1 year. Need for catheter based or surgical re-intervention (RI), valve annular growth, and significant late aortic or mitral valve obstruction were additional outcomes. Fifty one of 73 subjects (79%) had successful BVC and were free of RI at 1 year. Seven subjects failed BVC; four of those died. The overall 1 year survival for the cohort was 95%. Fifteen subjects underwent a RI but maintained BVC. In univariate analysis, larger transverse aorta (p = 0.006) and aortic valve (p = 0.02) predicted successful BVC without RI. In CART analysis, the combination of mitral valve (MV) to tricuspid valve (TV) ratio ≤0.66 with an aortic valve (AV) annulus Z-score ≤-3 had the greatest power to predict BVC failure (sensitivity 71%, specificity 94%). In those with successful BVC, the combination of both AV and MV Z-score ≤-2.5 increased the odds of RI (OR 3.8; CI 1.3-11.4). Follow-up of non-RI subjects revealed improvement in AV and MV Z-score (median AV annulus changed over time from -2.34 to 0.04 (p < 0.001) and MV changed from -2.88 to -1.41 (p < 0.001), but residual mitral valve stenosis and aortic arch obstruction were present in one-third of subjects. In this cohort of infants requiring initial aortic arch repair with concomitant small left heart structures, successful BVC can be predicted from combined echocardiographic indices. In this complex population, 1 year survival is high, but the need for RI and the presence of residual lesions are common.

Spatial Patterns and Temperature Predictions of Tuna Fatty Acids: Tracing Essential Nutrients and Changes in Primary Producers

PubMed Central

Pethybridge, Heidi R.; Parrish, Christopher C.; Morrongiello, John; Young, Jock W.; Farley, Jessica H.; Gunasekera, Rasanthi M.; Nichols, Peter D.

2015-01-01

Fatty acids are among the least understood nutrients in marine environments, despite their profile as key energy components of food webs and that they are essential to all life forms. Presented here is a novel approach to predict the spatial-temporal distributions of fatty acids in marine resources using generalized additive mixed models. Fatty acid tracers (FAT) of key primary producers, nutritional condition indices and concentrations of two essential long-chain (≥C20) omega-3 fatty acids (EFA) measured in muscle of albacore tuna, Thunnus alalunga, sampled in the south-west Pacific Ocean were response variables. Predictive variables were: location, time, sea surface temperature (SST) and chlorophyll-a (Chla), and phytoplankton biomass at time of catch and curved fork length. The best model fit for all fatty acid parameters included fish length and SST. The first oceanographic contour maps of EFA and FAT (FATscapes) were produced and demonstrated clear geographical gradients in the study region. Predicted changes in all fatty acid parameters reflected shifts in the size-structure of dominant primary producers. Model projections show that the supply and availability of EFA are likely to be negatively affected by increases in SST especially in temperate waters where a 12% reduction in both total fatty acid content and EFA proportions are predicted. Such changes will have large implications for the availability of energy and associated health benefits to high-order consumers. Results convey new concerns on impacts of projected climate change on fish-derived EFA in marine systems. PMID:26135308

The cost of doing business: cost structure of electronic immunization registries.

PubMed

Fontanesi, John M; Flesher, Don S; De Guire, Michelle; Lieberthal, Allan; Holcomb, Kathy

2002-10-01

To predict the true cost of developing and maintaining an electronic immunization registry, and to set the framework for developing future cost-effective and cost-benefit analysis. Primary data collected at three immunization registries located in California, accounting for 90 percent of all immunization records in registries in the state during the study period. A parametric cost analysis compared registry development and maintenance expenditures to registry performance requirements. Data were collected at each registry through interviews, reviews of expenditure records, technical accomplishments development schedules, and immunization coverage rates. The cost of building immunization registries is predictable and independent of the hardware/software combination employed. The effort requires four man-years of technical effort or approximately $250,000 in 1998 dollars. Costs for maintaining a registry were approximately $5,100 per end user per three-year period. There is a predictable cost structure for both developing and maintaining immunization registries. The cost structure can be used as a framework for examining the cost-effectiveness and cost-benefits of registries. The greatest factor effecting improvement in coverage rates was ongoing, user-based administrative investment.

Structural details (kinks and non-alpha conformations) in transmembrane helices are intrahelically determined and can be predicted by sequence pattern descriptors.

PubMed

Rigoutsos, Isidore; Riek, Peter; Graham, Robert M; Novotny, Jiri

2003-08-01

One of the promising methods of protein structure prediction involves the use of amino acid sequence-derived patterns. Here we report on the creation of non-degenerate motif descriptors derived through data mining of training sets of residues taken from the transmembrane-spanning segments of polytopic proteins. These residues correspond to short regions in which there is a deviation from the regular alpha-helical character (i.e. pi-helices, 3(10)-helices and kinks). A 'search engine' derived from these motif descriptors correctly identifies, and discriminates amongst instances of the above 'non-canonical' helical motifs contained in the SwissProt/TrEMBL database of protein primary structures. Our results suggest that deviations from alpha-helicity are encoded locally in sequence patterns only about 7-9 residues long and can be determined in silico directly from the amino acid sequence. Delineation of such variations in helical habit is critical to understanding the complex structure-function relationships of polytopic proteins and for drug discovery. The success of our current methodology foretells development of similar prediction tools capable of identifying other structural motifs from sequence alone. The method described here has been implemented and is available on the World Wide Web at http://cbcsrv.watson.ibm.com/Ttkw.html.

Structural and functional bases of inhibited temperament.

PubMed

Clauss, Jacqueline A; Seay, April L; VanDerKlok, Ross M; Avery, Suzanne N; Cao, Aize; Cowan, Ronald L; Benningfield, Margaret M; Blackford, Jennifer Urbano

2014-12-01

Children born with an inhibited temperament are at heightened risk for developing anxiety, depression and substance use. Inhibited temperament is believed to have a biological basis; however, little is known about the structural brain basis of this vulnerability trait. Structural MRI scans were obtained from 84 (44 inhibited, 40 uninhibited) young adults. Given previous findings of amygdala hyperactivity in inhibited individuals, groups were compared on three measures of amygdala structure. To identify novel substrates of inhibited temperament, a whole brain analysis was performed. Functional activation and connectivity were examined across both groups. Inhibited adults had larger amygdala and caudate volume and larger volume predicted greater activation to neutral faces. In addition, larger amygdala volume predicted greater connectivity with subcortical and higher order visual structures. Larger caudate volume predicted greater connectivity with the basal ganglia, and less connectivity with primary visual and auditory cortex. We propose that larger volume in these salience detection regions may result in increased activation and enhanced connectivity in response to social stimuli. Given the strong link between inhibited temperament and risk for psychiatric illness, novel therapeutics that target these brain regions and related neural circuits have the potential to reduce rates of illness in vulnerable individuals. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Using Scavenger Hunts to Familiarize Students with Scientific Journal Articles.

PubMed

Lijek, Rebeccah S; Fankhauser, Sarah C

2016-03-01

Primary scientific literature can be difficult to navigate for anyone unfamiliar with its foreign, formal structure. We sought to create a fun, easy learning tool to help familiarize students of all ages with the structure of a scientific article. Our main learning objective was for the student to realize that science writing is formulaic-that specific information is found in predictable locations within an article-and that, with an understanding of the formula, anyone can comfortably navigate any journal article and accurately predict what to expect to find in each section. To this end, we designed a Journal Article Scavenger Hunt that requires the user to find and identify a series of commonplace features of a primary research article. The scavenger hunt activity is quick and easy to implement, and is adaptable to various ages and settings, including the classroom, lab, and at outreach events. The questions in the scavenger hunt can be scaled in difficulty and specificity to suit the instructor's needs. Over many years of using this activity, we have received positive feedback from students of all ages, from elementary school students to lay adult-learners as well as science teachers themselves. By making the unknown seem predictable and approachable, the scavenger hunt helps a variety of audiences feel more comfortable with science and more confident in their ability to engage directly with the scientific literature. Journal of Microbiology & Biology Education.

Evaluation and comparison of the ability of online available prediction programs to predict true linear B-cell epitopes.

PubMed

Costa, Juan G; Faccendini, Pablo L; Sferco, Silvano J; Lagier, Claudia M; Marcipar, Iván S

2013-06-01

This work deals with the use of predictors to identify useful B-cell linear epitopes to develop immunoassays. Experimental techniques to meet this goal are quite expensive and time consuming. Therefore, we tested 5 free, online prediction methods (AAPPred, ABCpred, BcePred, BepiPred and Antigenic) widely used for predicting linear epitopes, using the primary structure of the protein as the only input. We chose a set of 65 experimentally well documented epitopes obtained by the most reliable experimental techniques as our true positive set. To compare the quality of the predictor methods we used their positive predictive value (PPV), i.e. the proportion of the predicted epitopes that are true, experimentally confirmed epitopes, in relation to all the epitopes predicted. We conclude that AAPPred and ABCpred yield the best results as compared with the other programs and with a random prediction procedure. Our results also indicate that considering the consensual epitopes predicted by several programs does not improve the PPV.

Validity and reliability of the Malay version of the Hill-Bone compliance to high blood pressure therapy scale for use in primary healthcare settings in Malaysia: A cross-sectional study.

PubMed

Cheong, A T; Tong, S F; Sazlina, S G

2015-01-01

Hill-Bone compliance to high blood pressure therapy scale (HBTS) is one of the useful scales in primary care settings. It has been tested in America, Africa and Turkey with variable validity and reliability. The aim of this paper was to determine the validity and reliability of the Malay version of HBTS (HBTS-M) for the Malaysian population. HBTS comprises three subscales assessing compliance to medication, appointment and salt intake. The content validity of HBTS to the local population was agreed through consensus of expert panel. The 14 items used in the HBTS were adapted to reflect the local situations. It was translated into Malay and then back-translated into English. The translated version was piloted in 30 participants. This was followed by structural and predictive validity, and internal consistency testing in 262 patients with hypertension, who were on antihypertensive agent(s) for at least 1 year in two primary healthcare clinics in Kuala Lumpur, Malaysia. Exploratory factor analyses and the correlation between HBTS-M total score and blood pressure were performed. The Cronbach's alpha was calculated accordingly. Factor analysis revealed a three-component structure represented by two components on medication adherence and one on salt intake adherence. The Kaiser-Meyer-Olkin statistic was 0.764. The variance explained by each factors were 23.6%, 10.4% and 9.8%, respectively. However, the internal consistency for each component was suboptimal with Cronbach's alpha of 0.64, 0.55 and 0.29, respectively. Although there were two components representing medication adherence, the theoretical concepts underlying each concept cannot be differentiated. In addition, there was no correlation between the HBTS-M total score and blood pressure. HBTS-M did not conform to the structural and predictive validity of the original scale. Its reliability on assessing medication and salt intake adherence would most probably to be suboptimal in the Malaysian primary care setting.

Patient reactance as a moderator of the effect of therapist structure on posttreatment alcohol use.

PubMed

Karno, Mitchell P; Longabaugh, Richard; Herbeck, Diane

2009-11-01

We sought to replicate findings about the effect of therapist-imposed structure on alcoholism-treatment effectiveness for aftercare patients at different levels of interpersonal reactance and to examine if the effect generalizes to patients in a primary phase of treatment. Analyses were based on ex post facto observer ratings combined with outcome data from a randomized clinical trial. Participants had alcohol abuse or dependence (N = 247) and received treatment at either a primary outpatient treatment site (n = 125) or an aftercare site (n = 122) of Project MATCH (Matching Alcoholism Treatments to Client Heterogeneity). Patients' trait reactance and therapist structure were assessed via observer ratings based on videotaped therapy sessions. Dependent variables included percentage days abstinent, percentage heavy-drinking days, time to first drinking day, and time to first heavy-drinking day throughout a 1-year posttreatment period. The results indicated that increased therapist structure during aftercare treatment predicted fewer abstinent days and more heavy-drinking days for persons at a high level of reactance than for persons at a low level of reactance. The effect was a consistent predictor of alcohol use throughout each 3-month interval within the follow-up period. The interaction effect was not supported in the primary outpatient treatment sites, and it was not supported as a predictor of time to first drink or time to first heavy drink in either the aftercare or the outpatient sites. This study successfully replicated the finding that level of patient reactance appears to moderate the effect of therapist structure on alcohol-use outcomes in aftercare treatment settings. The lack of support for this effect in primary outpatient treatment settings suggests that the negative effect of structured treatment may be limited to patients who are further along in the recovery process.

Understanding the Dynamics of Soil Carbon in CMIP5 Models

NASA Astrophysics Data System (ADS)

Todd-Brown, K. E.; Luo, Y.; Randerson, J. T.; Allison, S. D.; Smith, M. J.

2014-12-01

Soil carbon stocks have the potential to be a strong source or sink for carbon dioxide over the next century, playing a critical role in climate change. These stocks are the result of small differences between much larger primary carbon fluxes: gross primary production, litter fall, autotrophic respiration and heterotrophic respiration. There was little agreement on predicted soil carbon stocks between Earth system models (ESMs) in the most recent Climate Model Intercomparison Project. Predicted present-day stocks ranged from roughly 500 Pg to over 3000 Pg and predicted changes over the 21st century ranged from -70 Pg to +250 Pg). The primary goal of this study was to understand why such large differences exist. We constructed four reduced complexity models to describe the primary carbon fluxes, making different assumptions about how soil carbon fluxes are modelled in ESMs. For each of these reduced complexity models we statistically inferred the most likely model parameters given the gridded ESM simulation outputs. Gross primary production was best explained by incoming short wave radiation, CO2 concentration, and leaf area index (global GPP comparison of simulation vs reduced complexity model of R2>0.9 (p < 1e-4) with slopes between 0.65 and 1.2 and intercepts between -13 and 67 Pg C yr-1). Autotrophic respiration was best explained as a proportion of GPP (R2 > 0.9 (p < 1e-4) with slopes between 0.78 and 1.1 and intercepts between -15 and 14 Pg C yr-1). Flux between the vegetation and soil pools were best explained as a proportion of the vegetation carbon stock (R2 > 0.9 (p < 1e-4) with slopes between 0.9 and 2.1 and intercepts between -65 and 25 Pg C yr-1). Finally heterotrophic respiration was best explained as a function of soil carbon stocks and soil temperature (R2 > 0.9 (p < 1e-4) with slopes between 0.7 and 1.5 and intercepts between -40 and 15 Pg C yr-1). This research suggests three main lines of decomposition model improvement: 1) improve connecting sub-models, 2) data integration to improve parameterization, 3) modification of model structure. The implied variation in RCM parameterization suggests that data integration could constrain model simulation results. However, the similarity in model structure may lead to systematic biases in the simulations without the introduction of new model structures.

Prediction of TF target sites based on atomistic models of protein-DNA complexes

PubMed Central

Angarica, Vladimir Espinosa; Pérez, Abel González; Vasconcelos, Ana T; Collado-Vides, Julio; Contreras-Moreira, Bruno

2008-01-01

Background The specific recognition of genomic cis-regulatory elements by transcription factors (TFs) plays an essential role in the regulation of coordinated gene expression. Studying the mechanisms determining binding specificity in protein-DNA interactions is thus an important goal. Most current approaches for modeling TF specific recognition rely on the knowledge of large sets of cognate target sites and consider only the information contained in their primary sequence. Results Here we describe a structure-based methodology for predicting sequence motifs starting from the coordinates of a TF-DNA complex. Our algorithm combines information regarding the direct and indirect readout of DNA into an atomistic statistical model, which is used to estimate the interaction potential. We first measure the ability of our method to correctly estimate the binding specificities of eight prokaryotic and eukaryotic TFs that belong to different structural superfamilies. Secondly, the method is applied to two homology models, finding that sampling of interface side-chain rotamers remarkably improves the results. Thirdly, the algorithm is compared with a reference structural method based on contact counts, obtaining comparable predictions for the experimental complexes and more accurate sequence motifs for the homology models. Conclusion Our results demonstrate that atomic-detail structural information can be feasibly used to predict TF binding sites. The computational method presented here is universal and might be applied to other systems involving protein-DNA recognition. PMID:18922190

Design and Performance of the Terrestrial Planet Finder Coronagraph

NASA Technical Reports Server (NTRS)

White, Mary L.; Shaklan, Stuart; Lisman, P. Doulas; Ho, Timothy; Mouroulis, Pantazis; Basinger, Scott; Ledeboer, Bill; Kwack, Eug; Kissil, Andy; Mosier, Gary;

Classification of Structural Coal-Controlling Styles and Analysis on Structural Coal-Controlling Actions

NASA Astrophysics Data System (ADS)

Zhan, Wen-feng

2017-11-01

Tectonism was the primary geologic factors for controlling the formation, deformation, and occurrence of coal measures. As the core of a new round of prediction and evaluation on the coalfield resource potential, the effect of coal-controlling structure was further strengthened and deepened in related researches. By systematically combing the tectonic coal-controlling effect and structure, this study determined the geodynamical classification basis for coal-controlling structures. According to the systematic analysis and summary on the related research results, the coal-controlling structure was categorized into extensional structure, compressive structure, shearing and rotational structure, inverted structure, as well as the sliding structure, syndepositional structure with coalfield structure characteristics. In accordance with the structure combination and distribution characteristics, the six major classes were further classified into 32 subclasses. Moreover, corresponding mode maps were drawn to discuss the basic characteristics and effect of the coal-controlling structures.

Multiscale Modeling of Primary Cilium Deformations Under Local Forces and Shear Flows

NASA Astrophysics Data System (ADS)

Peng, Zhangli; Feng, Zhe; Resnick, Andrew; Young, Yuan-Nan

2017-11-01

We study the detailed deformations of a primary cilium under local forces and shear flows by developing a multiscale model based on the state-of-the-art understanding of its molecular structure. Most eukaryotic cells are ciliated with primary cilia. Primary cilia play important roles in chemosensation, thermosensation, and mechanosensation, but the detailed mechanism for mechanosensation is not well understood. We apply the dissipative particle dynamics (DPD) to model an entire well with a primary cilium and consider its different components, including the basal body, microtubule doublets, actin cortex, and lipid bilayer. We calibrate the mechanical properties of individual components and their interactions from experimental measurements and molecular dynamics simulations. We validate the simulations by comparing the deformation profile of the cilium and the rotation of the basal body with optical trapping experiments. After validations, we investigate the deformation of the primary cilium under shear flows. Furthermore, we calculate the membrane tensions and cytoskeleton stresses, and use them to predict the activation of mechanosensitive channels.

Comparison of Measured and Block Structured Simulations for the F-16XL Aircraft

NASA Technical Reports Server (NTRS)

Boelens, O. J.; Badcock, K. J.; Elmilgui, A.; Abdol-Hamid, K. S.; Massey, S. J.

2008-01-01

This article presents a comparison of the predictions of three RANS codes for flight conditions of the F-16XL aircraft which feature vortical flow. The three codes, ENSOLV, PMB and PAB3D, solve on structured multi-block grids. Flight data for comparison was available in the form of surface pressures, skin friction, boundary layer data and photographs of tufts. The three codes provided predictions which were consistent with expectations based on the turbulence modelling used, which was k- , k- with vortex corrections and an Algebraic Stress Model. The agreement with flight data was good, with the exception of the outer wing primary vortex strength. The confidence in the application of the CFD codes to complex fighter configurations increased significantly through this study.

Effects of long-term nutrient additions on Arctic tundra, stream, and lake ecosystems: beyond NPP.

PubMed

Gough, Laura; Bettez, Neil D; Slavik, Karie A; Bowden, William B; Giblin, Anne E; Kling, George W; Laundre, James A; Shaver, Gaius R

2016-11-01

Primary producers form the base of food webs but also affect other ecosystem characteristics, such as habitat structure, light availability, and microclimate. Here, we examine changes caused by 5-30+ years of nutrient addition and resulting increases in net primary productivity (NPP) in tundra, streams, and lakes in northern Alaska. The Arctic provides an important opportunity to examine how ecosystems characterized by low diversity and low productivity respond to release from nutrient limitation. We review how responses of algae and plants affect light availability, perennial biotic structures available for consumers, oxygen levels, and temperature. Sometimes, responses were similar across all three ecosystems; e.g., increased NPP significantly reduced light to the substrate following fertilization. Perennial biotic structures increased in tundra and streams but not in lakes, and provided important new habitat niches for consumers as well as other producers. Oxygen and temperature responses also differed. Life history traits (e.g., longevity) of the primary producers along with the fate of detritus drove the responses and recovery. As global change persists and nutrients become more available in the Arctic and elsewhere, incorporating these factors as response variables will enable better prediction of ecosystem changes and feedbacks in this biome and others.

Compression strength of composite primary structural components

NASA Technical Reports Server (NTRS)

Johnson, Eric R.

1993-01-01

Two projects are summarized. The first project is entitled 'Stiffener Crippling Inititated by Delaminations' and its objective is to develop a computational model of the stiffener specimens that includes the capability to predict the interlaminar stress response at the flange free edge in postbuckling. The second is entitled 'Pressure Pillowing of an Orthogonally Stiffened Cylindrical Shell'. A paper written on this project is included.

The Mediating Role of Mind Wandering in the Relationship between Working Memory Capacity and Reading Comprehension

ERIC Educational Resources Information Center

McVay, Jennifer C.

2010-01-01

The primary goal of this study was to investigate the mediating role of mind wandering in the relationship between working memory capacity (WMC) and reading comprehension as predicted by the executive-attention theory of WMC (e.g., Kane & Engle, 2003). I used a latent-variable, structural-equation-model approach with three WMC span tasks, seven…

Reliability analysis of composite structures

NASA Technical Reports Server (NTRS)

Kan, Han-Pin

1992-01-01

A probabilistic static stress analysis methodology has been developed to estimate the reliability of a composite structure. Closed form stress analysis methods are the primary analytical tools used in this methodology. These structural mechanics methods are used to identify independent variables whose variations significantly affect the performance of the structure. Once these variables are identified, scatter in their values is evaluated and statistically characterized. The scatter in applied loads and the structural parameters are then fitted to appropriate probabilistic distribution functions. Numerical integration techniques are applied to compute the structural reliability. The predicted reliability accounts for scatter due to variability in material strength, applied load, fabrication and assembly processes. The influence of structural geometry and mode of failure are also considerations in the evaluation. Example problems are given to illustrate various levels of analytical complexity.

RF-Phos: A Novel General Phosphorylation Site Prediction Tool Based on Random Forest.

PubMed

Ismail, Hamid D; Jones, Ahoi; Kim, Jung H; Newman, Robert H; Kc, Dukka B

2016-01-01

Protein phosphorylation is one of the most widespread regulatory mechanisms in eukaryotes. Over the past decade, phosphorylation site prediction has emerged as an important problem in the field of bioinformatics. Here, we report a new method, termed Random Forest-based Phosphosite predictor 2.0 (RF-Phos 2.0), to predict phosphorylation sites given only the primary amino acid sequence of a protein as input. RF-Phos 2.0, which uses random forest with sequence and structural features, is able to identify putative sites of phosphorylation across many protein families. In side-by-side comparisons based on 10-fold cross validation and an independent dataset, RF-Phos 2.0 compares favorably to other popular mammalian phosphosite prediction methods, such as PhosphoSVM, GPS2.1, and Musite.

Predicting domain-domain interaction based on domain profiles with feature selection and support vector machines

PubMed Central

2010-01-01

Background Protein-protein interaction (PPI) plays essential roles in cellular functions. The cost, time and other limitations associated with the current experimental methods have motivated the development of computational methods for predicting PPIs. As protein interactions generally occur via domains instead of the whole molecules, predicting domain-domain interaction (DDI) is an important step toward PPI prediction. Computational methods developed so far have utilized information from various sources at different levels, from primary sequences, to molecular structures, to evolutionary profiles. Results In this paper, we propose a computational method to predict DDI using support vector machines (SVMs), based on domains represented as interaction profile hidden Markov models (ipHMM) where interacting residues in domains are explicitly modeled according to the three dimensional structural information available at the Protein Data Bank (PDB). Features about the domains are extracted first as the Fisher scores derived from the ipHMM and then selected using singular value decomposition (SVD). Domain pairs are represented by concatenating their selected feature vectors, and classified by a support vector machine trained on these feature vectors. The method is tested by leave-one-out cross validation experiments with a set of interacting protein pairs adopted from the 3DID database. The prediction accuracy has shown significant improvement as compared to InterPreTS (Interaction Prediction through Tertiary Structure), an existing method for PPI prediction that also uses the sequences and complexes of known 3D structure. Conclusions We show that domain-domain interaction prediction can be significantly enhanced by exploiting information inherent in the domain profiles via feature selection based on Fisher scores, singular value decomposition and supervised learning based on support vector machines. Datasets and source code are freely available on the web at http://liao.cis.udel.edu/pub/svdsvm. Implemented in Matlab and supported on Linux and MS Windows. PMID:21034480

Connectivity Predicts Deep Brain Stimulation Outcome in Parkinson Disease

PubMed Central

Horn, Andreas; Reich, Martin; Vorwerk, Johannes; Li, Ningfei; Wenzel, Gregor; Fang, Qianqian; Schmitz-Hübsch, Tanja; Nickl, Robert; Kupsch, Andreas; Volkmann, Jens; Kühn, Andrea A.; Fox, Michael D.

2018-01-01

Objective The benefit of deep brain stimulation (DBS) for Parkinson disease (PD) may depend on connectivity between the stimulation site and other brain regions, but which regions and whether connectivity can predict outcome in patients remain unknown. Here, we identify the structural and functional connectivity profile of effective DBS to the subthalamic nucleus (STN) and test its ability to predict outcome in an independent cohort. Methods A training dataset of 51 PD patients with STN DBS was combined with publicly available human connectome data (diffusion tractography and resting state functional connectivity) to identify connections reliably associated with clinical improvement (motor score of the Unified Parkinson Disease Rating Scale [UPDRS]). This connectivity profile was then used to predict outcome in an independent cohort of 44 patients from a different center. Results In the training dataset, connectivity between the DBS electrode and a distributed network of brain regions correlated with clinical response including structural connectivity to supplementary motor area and functional anticorrelation to primary motor cortex (p<0.001). This same connectivity profile predicted response in an independent patient cohort (p<0.01). Structural and functional connectivity were independent predictors of clinical improvement (p<0.001) and estimated response in individual patients with an average error of 15% UPDRS improvement. Results were similar using connectome data from normal subjects or a connectome age, sex, and disease matched to our DBS patients. Interpretation Effective STN DBS for PD is associated with a specific connectivity profile that can predict clinical outcome across independent cohorts. This prediction does not require specialized imaging in PD patients themselves. PMID:28586141

Pushing the size limit of de novo structure ensemble prediction guided by sparse SDSL-EPR restraints to 200 residues: The monomeric and homodimeric forms of BAX

PubMed Central

Fischer, Axel W.; Bordignon, Enrica; Bleicken, Stephanie; García-Sáez, Ana J.; Jeschke, Gunnar; Meiler, Jens

2016-01-01

Structure determination remains a challenge for many biologically important proteins. In particular, proteins that adopt multiple conformations often evade crystallization in all biologically relevant states. Although computational de novo protein folding approaches often sample biologically relevant conformations, the selection of the most accurate model for different functional states remains a formidable challenge, in particular, for proteins with more than about 150 residues. Electron paramagnetic resonance (EPR) spectroscopy can obtain limited structural information for proteins in well-defined biological states and thereby assist in selecting biologically relevant conformations. The present study demonstrates that de novo folding methods are able to accurately sample the folds of 192-residue long soluble monomeric Bcl-2-associated X protein (BAX). The tertiary structures of the monomeric and homodimeric forms of BAX were predicted using the primary structure as well as 25 and 11 EPR distance restraints, respectively. The predicted models were subsequently compared to respective NMR/X-ray structures of BAX. EPR restraints improve the protein-size normalized root-mean-square-deviation (RMSD100) of the most accurate models with respect to the NMR/crystal structure from 5.9 Å to 3.9 Å and from 5.7 Å to 3.3 Å, respectively. Additionally, the model discrimination is improved, which is demonstrated by an improvement of the enrichment from 5% to 15% and from 13% to 21%, respectively. PMID:27129417

Increased resource use efficiency amplifies positive response of aquatic primary production to experimental warming.

PubMed

Hood, James M; Benstead, Jonathan P; Cross, Wyatt F; Huryn, Alexander D; Johnson, Philip W; Gíslason, Gísli M; Junker, James R; Nelson, Daniel; Ólafsson, Jón S; Tran, Chau

2018-03-01

Climate warming is affecting the structure and function of river ecosystems, including their role in transforming and transporting carbon (C), nitrogen (N), and phosphorus (P). Predicting how river ecosystems respond to warming has been hindered by a dearth of information about how otherwise well-studied physiological responses to temperature scale from organismal to ecosystem levels. We conducted an ecosystem-level temperature manipulation to quantify how coupling of stream ecosystem metabolism and nutrient uptake responded to a realistic warming scenario. A ~3.3°C increase in mean water temperature altered coupling of C, N, and P fluxes in ways inconsistent with single-species laboratory experiments. Net primary production tripled during the year of experimental warming, while whole-stream N and P uptake rates did not change, resulting in 289% and 281% increases in autotrophic dissolved inorganic N and P use efficiency (UE), respectively. Increased ecosystem production was a product of unexpectedly large increases in mass-specific net primary production and autotroph biomass, supported by (i) combined increases in resource availability (via N mineralization and N 2 fixation) and (ii) elevated resource use efficiency, the latter associated with changes in community structure. These large changes in C and nutrient cycling could not have been predicted from the physiological effects of temperature alone. Our experiment provides clear ecosystem-level evidence that warming can shift the balance between C and nutrient cycling in rivers, demonstrating that warming will alter the important role of in-stream processes in C, N, and P transformations. Moreover, our results reveal a key role for nutrient supply and use efficiency in mediating responses of primary producers to climate warming. © 2017 John Wiley & Sons Ltd.

Evolution of Nano-structured Quasicrystals from Amorphous alloys

NASA Astrophysics Data System (ADS)

Xing, L. Q.; Kelton, K. F.

2002-03-01

Ta shows a significant effect on the precipitation of quasicrystals in (Zr_1-xTa_x)_64Cu_18Ni_8Al_10 amorphous alloys. The amorphous alloy made without Ta forms precipitates of tetragonal Zr_2Cu primary phases upon annealing. The addition of a small amount of Ta ( ~ 3 at%) to the alloy initiates the precipitation of primary icosahedral quasicrystal phases. Moreover, as the Ta concentration increases, the size of the precipitates decreases dramatically. To study the effect of Ta in this alloy system and to understand the mechanism for the precipitation of nano-structured quasicrystals, we have investigated the crystallization characteristics of the alloys made with different Ta concentration using DSC, checked the structures of the annealed samples with TEM and X-ray diffraction, and analyzed the kinetics of the crystallization processes. The kinetic parameter and the measured crystal size distribution will be compared with theoretical predictions from conventional nucleation and growth model and from a new model for nucleation that couples the long-range diffusion flux with the interfacial attachment processes.

Analytical and experimental investigation of aircraft metal structures reinforced with filamentary composites. Phase 1: Concept development and feasibility

NASA Technical Reports Server (NTRS)

Oken, S.; June, R. R.

1971-01-01

The analytical and experimental investigations are described in the first phase of a program to establish the feasibility of reinforcing metal aircraft structures with advanced filamentary composites. The interactions resulting from combining the two types of materials into single assemblies as well as their ability to function structurally were studied. The combinations studied were boron-epoxy reinforced aluminum, boron-epoxy reinforced titanium, and boron-polyimide reinforced titanium. The concepts used unidirectional composites as reinforcement in the primary loading direction and metal for carrying the transverse loads as well as its portion of the primary load. The program established that several realistic concepts could be fabricated, that these concepts could perform to a level that would result in significant weight savings, and that there are means for predicting their capability within a reasonable degree of accuracy. This program also encountered problems related to the application of polyimide systems that resulted in their relatively poor and variable performance.

A constraint logic programming approach to associate 1D and 3D structural components for large protein complexes.

PubMed

Dal Palù, Alessandro; Pontelli, Enrico; He, Jing; Lu, Yonggang

2007-01-01

The paper describes a novel framework, constructed using Constraint Logic Programming (CLP) and parallelism, to determine the association between parts of the primary sequence of a protein and alpha-helices extracted from 3D low-resolution descriptions of large protein complexes. The association is determined by extracting constraints from the 3D information, regarding length, relative position and connectivity of helices, and solving these constraints with the guidance of a secondary structure prediction algorithm. Parallelism is employed to enhance performance on large proteins. The framework provides a fast, inexpensive alternative to determine the exact tertiary structure of unknown proteins.

Three-dimensional (3D) structure prediction and function analysis of the chitin-binding domain 3 protein HD73_3189 from Bacillus thuringiensis HD73.

PubMed

Zhan, Yiling; Guo, Shuyuan

2015-01-01

Bacillus thuringiensis (Bt) is capable of producing a chitin-binding protein believed to be functionally important to bacteria during the stationary phase of its growth cycle. In this paper, the chitin-binding domain 3 protein HD73_3189 from B. thuringiensis has been analyzed by computer technology. Primary and secondary structural analyses demonstrated that HD73_3189 is negatively charged and contains several α-helices, aperiodical coils and β-strands. Domain and motif analyses revealed that HD73_3189 contains a signal peptide, an N-terminal chitin binding 3 domains, two copies of a fibronectin-like domain 3 and a C-terminal carbohydrate binding domain classified as CBM_5_12. Moreover, analysis predicted the protein's associated localization site to be the cell wall. Ligand site prediction determined that amino acid residues GLU-312, TRP-334, ILE-341 and VAL-382 exposed on the surface of the target protein exhibit polar interactions with the substrate.

Composite structural materials. [aircraft structures

NASA Technical Reports Server (NTRS)

Ansell, G. S.; Loewy, R. G.; Wiberley, S. E.

1980-01-01

The use of filamentary composite materials in the design and construction of primary aircraft structures is considered with emphasis on efforts to develop advanced technology in the areas of physical properties, structural concepts and analysis, manufacturing, and reliability and life prediction. The redesign of a main spar/rib region on the Boeing 727 elevator near its actuator attachment point is discussed. A composite fabrication and test facility is described as well as the use of minicomputers for computer aided design. Other topics covered include (1) advanced structural analysis methids for composites; (2) ultrasonic nondestructive testing of composite structures; (3) optimum combination of hardeners in the cure of epoxy; (4) fatigue in composite materials; (5) resin matrix characterization and properties; (6) postbuckling analysis of curved laminate composite panels; and (7) acoustic emission testing of composite tensile specimens.

Functional connectivity between somatosensory and motor brain areas predicts individual differences in motor learning by observing.

PubMed

McGregor, Heather R; Gribble, Paul L

2017-08-01

Action observation can facilitate the acquisition of novel motor skills; however, there is considerable individual variability in the extent to which observation promotes motor learning. Here we tested the hypothesis that individual differences in brain function or structure can predict subsequent observation-related gains in motor learning. Subjects underwent an anatomical MRI scan and resting-state fMRI scans to assess preobservation gray matter volume and preobservation resting-state functional connectivity (FC), respectively. On the following day, subjects observed a video of a tutor adapting her reaches to a novel force field. After observation, subjects performed reaches in a force field as a behavioral assessment of gains in motor learning resulting from observation. We found that individual differences in resting-state FC, but not gray matter volume, predicted postobservation gains in motor learning. Preobservation resting-state FC between left primary somatosensory cortex and bilateral dorsal premotor cortex, primary motor cortex, and primary somatosensory cortex and left superior parietal lobule was positively correlated with behavioral measures of postobservation motor learning. Sensory-motor resting-state FC can thus predict the extent to which observation will promote subsequent motor learning. NEW & NOTEWORTHY We show that individual differences in preobservation brain function can predict subsequent observation-related gains in motor learning. Preobservation resting-state functional connectivity within a sensory-motor network may be used as a biomarker for the extent to which observation promotes motor learning. This kind of information may be useful if observation is to be used as a way to boost neuroplasticity and sensory-motor recovery for patients undergoing rehabilitation for diseases that impair movement such as stroke. Copyright © 2017 the American Physiological Society.

Structural details (kinks and non-α conformations) in transmembrane helices are intrahelically determined and can be predicted by sequence pattern descriptors

PubMed Central

Rigoutsos, Isidore; Riek, Peter; Graham, Robert M.; Novotny, Jiri

2003-01-01

One of the promising methods of protein structure prediction involves the use of amino acid sequence-derived patterns. Here we report on the creation of non-degenerate motif descriptors derived through data mining of training sets of residues taken from the transmembrane-spanning segments of polytopic proteins. These residues correspond to short regions in which there is a deviation from the regular α-helical character (i.e. π-helices, 310-helices and kinks). A ‘search engine’ derived from these motif descriptors correctly identifies, and discriminates amongst instances of the above ‘non-canonical’ helical motifs contained in the SwissProt/TrEMBL database of protein primary structures. Our results suggest that deviations from α-helicity are encoded locally in sequence patterns only about 7–9 residues long and can be determined in silico directly from the amino acid sequence. Delineation of such variations in helical habit is critical to understanding the complex structure–function relationships of polytopic proteins and for drug discovery. The success of our current methodology foretells development of similar prediction tools capable of identifying other structural motifs from sequence alone. The method described here has been implemented and is available on the World Wide Web at http://cbcsrv.watson.ibm.com/Ttkw.html. PMID:12888523

Predictive Feedback Can Account for Biphasic Responses in the Lateral Geniculate Nucleus

PubMed Central

Jehee, Janneke F. M.; Ballard, Dana H.

2009-01-01

Biphasic neural response properties, where the optimal stimulus for driving a neural response changes from one stimulus pattern to the opposite stimulus pattern over short periods of time, have been described in several visual areas, including lateral geniculate nucleus (LGN), primary visual cortex (V1), and middle temporal area (MT). We describe a hierarchical model of predictive coding and simulations that capture these temporal variations in neuronal response properties. We focus on the LGN-V1 circuit and find that after training on natural images the model exhibits the brain's LGN-V1 connectivity structure, in which the structure of V1 receptive fields is linked to the spatial alignment and properties of center-surround cells in the LGN. In addition, the spatio-temporal response profile of LGN model neurons is biphasic in structure, resembling the biphasic response structure of neurons in cat LGN. Moreover, the model displays a specific pattern of influence of feedback, where LGN receptive fields that are aligned over a simple cell receptive field zone of the same polarity decrease their responses while neurons of opposite polarity increase their responses with feedback. This phase-reversed pattern of influence was recently observed in neurophysiology. These results corroborate the idea that predictive feedback is a general coding strategy in the brain. PMID:19412529

Using the Counseling Center Assessment of Psychological Symptoms-34 (CCAPS-34) to Predict Premature Termination in a College Counseling Sample

ERIC Educational Resources Information Center

Hall, Sean B.

2012-01-01

Swift and Greenberg (2012) observed that variables influencing the decision to drop out fluctuate according to the primary presenting problem, the amount of structure in therapy, the length of treatment, and the clinical setting. Due to these reports, researchers may focus on predictors of premature termination (PT) in treatment settings where the…

Remote sensing of the seasonal variation of coniferous forest structure and function

NASA Technical Reports Server (NTRS)

Spanner, Michael; Waring, Richard

1991-01-01

One of the objectives of the Oregon Transect Ecosystem Research (OTTER) project is the remotely sensed determination of the seasonal variation of leaf area index (LAI) and absorbed photosynthetically active radiation (APAR). These measurements are required for input into a forest ecosystem model which predicts net primary production evapotranspiration, and photosynthesis of coniferous forests. Details of the study are given.

Carbon-carbon primary structure for SSTO vehicles

NASA Astrophysics Data System (ADS)

Croop, Harold C.; Lowndes, Holland B.

1997-01-01

A hot structures development program is nearing completion to validate use of carbon-carbon composite structure for primary load carrying members in a single-stage-to-orbit, or SSTO, vehicle. A four phase program was pursued which involved design development and fabrication of a full-scale wing torque box demonstration component. The design development included vehicle and component selection, design criteria and approach, design data development, demonstration component design and analysis, test fixture design and analysis, demonstration component test planning, and high temperature test instrumentation development. The fabrication effort encompassed fabrication of structural elements for mechanical property verification as well as fabrication of the demonstration component itself and associated test fixturing. The demonstration component features 3D woven graphite preforms, integral spars, oxidation inhibited matrix, chemical vapor deposited (CVD) SiC oxidation protection coating, and ceramic matrix composite fasteners. The demonstration component has been delivered to the United States Air Force (USAF) for testing in the Wright Laboratory Structural Test Facility, WPAFB, OH. Multiple thermal-mechanical load cycles will be applied simulating two atmospheric cruise missions and one orbital mission. This paper discusses the overall approach to validation testing of the wing box component and presents some preliminary analytical test predictions.

Augmented Method to Improve Thermal Data for the Figure Drift Thermal Distortion Predictions of the JWST OTIS Cryogenic Vacuum Test

NASA Technical Reports Server (NTRS)

Park, Sang C.; Carnahan, Timothy M.; Cohen, Lester M.; Congedo, Cherie B.; Eisenhower, Michael J.; Ousley, Wes; Weaver, Andrew; Yang, Kan

2017-01-01

The JWST Optical Telescope Element (OTE) assembly is the largest optically stable infrared-optimized telescope currently being manufactured and assembled, and is scheduled for launch in 2018. The JWST OTE, including the 18 segment primary mirror, secondary mirror, and the Aft Optics Subsystem (AOS) are designed to be passively cooled and operate near 45K. These optical elements are supported by a complex composite backplane structure. As a part of the structural distortion model validation efforts, a series of tests are planned during the cryogenic vacuum test of the fully integrated flight hardware at NASA JSC Chamber A. The successful ends to the thermal-distortion phases are heavily dependent on the accurate temperature knowledge of the OTE structural members. However, the current temperature sensor allocations during the cryo-vac test may not have sufficient fidelity to provide accurate knowledge of the temperature distributions within the composite structure. A method based on an inverse distance relationship among the sensors and thermal model nodes was developed to improve the thermal data provided for the nanometer scale WaveFront Error (WFE) predictions. The Linear Distance Weighted Interpolation (LDWI) method was developed to augment the thermal model predictions based on the sparse sensor information. This paper will encompass the development of the LDWI method using the test data from the earlier pathfinder cryo-vac tests, and the results of the notional and as tested WFE predictions from the structural finite element model cases to characterize the accuracies of this LDWI method.

Interior noise control prediction study for high-speed propeller-driven aircraft

NASA Technical Reports Server (NTRS)

Rennison, D. C.; Wilby, J. F.; Marsh, A. H.; Wilby, E. G.

1979-01-01

An analytical model was developed to predict the noise levels inside propeller-driven aircraft during cruise at M = 0.8. The model was applied to three study aircraft with fuselages of different size (wide body, narrow body and small diameter) in order to determine the noise reductions required to achieve the goal of an A-weighted sound level which does not exceed 80 dB. The model was then used to determine noise control methods which could achieve the required noise reductions. Two classes of noise control treatments were investigated: add-on treatments which can be added to existing structures, and advanced concepts which would require changes to the fuselage primary structure. Only one treatment, a double wall with limp panel, provided the required noise reductions. Weight penalties associated with the treatment were estimated for the three study aircraft.

The Cost of Doing Business: Cost Structure of Electronic Immunization Registries

PubMed Central

Fontanesi, John M; Flesher, Don S; De Guire, Michelle; Lieberthal, Allan; Holcomb, Kathy

2002-01-01

Objective To predict the true cost of developing and maintaining an electronic immunization registry, and to set the framework for developing future cost-effective and cost-benefit analysis. Data Sources/Study Setting Primary data collected at three immunization registries located in California, accounting for 90 percent of all immunization records in registries in the state during the study period. Study Design A parametric cost analysis compared registry development and maintenance expenditures to registry performance requirements. Data Collection/Extraction Methods Data were collected at each registry through interviews, reviews of expenditure records, technical accomplishments development schedules, and immunization coverage rates. Principal Findings The cost of building immunization registries is predictable and independent of the hardware/software combination employed. The effort requires four man-years of technical effort or approximately $250,000 in 1998 dollars. Costs for maintaining a registry were approximately $5,100 per end user per three-year period. Conclusions There is a predictable cost structure for both developing and maintaining immunization registries. The cost structure can be used as a framework for examining the cost-effectiveness and cost-benefits of registries. The greatest factor effecting improvement in coverage rates was ongoing, user-based administrative investment. PMID:12479497

Using the structure of natural scenes and sounds to predict neural response properties in the brain

NASA Astrophysics Data System (ADS)

Deweese, Michael

2014-03-01

The natural scenes and sounds we encounter in the world are highly structured. The fact that animals and humans are so efficient at processing these sensory signals compared with the latest algorithms running on the fastest modern computers suggests that our brains can exploit this structure. We have developed a sparse mathematical representation of speech that minimizes the number of active model neurons needed to represent typical speech sounds. The model learns several well-known acoustic features of speech such as harmonic stacks, formants, onsets and terminations, but we also find more exotic structures in the spectrogra representation of sound such as localized checkerboard patterns and frequency-modulated excitatory subregions flanked by suppressive sidebands. Moreover, several of these novel features resemble neuronal receptive fields reported in the Inferior Colliculus (IC), as well as auditory thalamus (MGBv) and primary auditory cortex (A1), and our model neurons exhibit the same tradeoff in spectrotemporal resolution as has been observed in IC. To our knowledge, this is the first demonstration that receptive fields of neurons in the ascending mammalian auditory pathway beyond the auditory nerve can be predicted based on coding principles and the statistical properties of recorded sounds. We have also developed a biologically-inspired neural network model of primary visual cortex (V1) that can learn a sparse representation of natural scenes using spiking neurons and strictly local plasticity rules. The representation learned by our model is in good agreement with measured receptive fields in V1, demonstrating that sparse sensory coding can be achieved in a realistic biological setting.

Mechanism of action of chromogranin A on catecholamine release: molecular modeling of the catestatin region reveals a β-strand/loop/β-strand structure secured by hydrophobic interactions and predictive of activity

PubMed Central

Tsigelny, Igor; Mahata, Sushil K.; Taupenot, Laurent; Preece, Nicholas E.; Mahata, Manjula; Khan, Imran; Parmer, Robert J.; O’Connor, Daniel T.

2009-01-01

A novel fragment of chromogranin A, known as ‘catestatin’ (bovine chromogranin A344–364), inhibits catecholamine release from chromaffin cells and noradrenergic neurons by acting as a non-competitive nicotinic cholinergic antagonist, and may therefore constitute an endogenous autocrine feedback regulator of sympathoadrenal activity. To characterize how this activity depends on the peptide’s structure, we searched for common 3-dimensional motifs for this primary structure or its homologs. Catestatin’s primary structure bore significant (29–35.5% identity, general alignment score 44–57) sequence homology to fragment sequences within three homologs of known 3-dimensional structures, based on solved X-ray crystals: 8FAB, 1PKM, and 2IG2. Each of these sequences exists in nature as a β-strand/loop/β-strand structure, stabilized by hydrophobic interactions between the β-strands. The catestatin structure was stable during molecular dynamics simulations. The catestatin loop contains three Arg residues, whose electropositive side chains form the terminus of the structure, and give rise to substantial uncompensated charge asymmetry in the molecule. A hydrophobic moment plot revealed that catestatin is the only segment of chromogranin A predicted to contain amphiphilic β-strand. Circular dichroism in the far ultraviolet showed substantial (63%) β-sheet structure, especially in a hydrophobic environment. Alanine-substitution mutants of catestatin established a crucial role for the three central arginine residues in the loop (Arg351, Arg353, and Arg358), though not for two arginine residues in the strand region toward the amino-terminus. [125I]Catestatin bound to Torpedo membranes at a site other than the nicotinic agonist binding site. When the catestatin structure was ‘docked’ with the extracellular domain of the Torpedo nicotinic cholinergic receptor, it interacted principally with the β and δ subunits, in a relatively hydrophobic region of the cation pore extracellular orifice, and the complex of ligand and receptor largely occluded the cation pore, providing a structural basis for the non-competitive nicotinic cholinergic antagonist properties of the peptide. We conclude that a homology model of catestatin correctly predicts actual features of the peptide, both physical and biological. The model suggests particular spatial and charge features of the peptide which may serve as starting points in the development of non-peptide mimetics of this endogenous nicotinic cholinergic antagonist. PMID:9809795

Anticipative management for coral reef ecosystem services in the 21st century.

PubMed

Rogers, Alice; Harborne, Alastair R; Brown, Christopher J; Bozec, Yves-Marie; Castro, Carolina; Chollett, Iliana; Hock, Karlo; Knowland, Cheryl A; Marshell, Alyssa; Ortiz, Juan C; Razak, Tries; Roff, George; Samper-Villarreal, Jimena; Saunders, Megan I; Wolff, Nicholas H; Mumby, Peter J

2015-02-01

Under projections of global climate change and other stressors, significant changes in the ecology, structure and function of coral reefs are predicted. Current management strategies tend to look to the past to set goals, focusing on halting declines and restoring baseline conditions. Here, we explore a complementary approach to decision making that is based on the anticipation of future changes in ecosystem state, function and services. Reviewing the existing literature and utilizing a scenario planning approach, we explore how the structure of coral reef communities might change in the future in response to global climate change and overfishing. We incorporate uncertainties in our predictions by considering heterogeneity in reef types in relation to structural complexity and primary productivity. We examine 14 ecosystem services provided by reefs, and rate their sensitivity to a range of future scenarios and management options. Our predictions suggest that the efficacy of management is highly dependent on biophysical characteristics and reef state. Reserves are currently widely used and are predicted to remain effective for reefs with high structural complexity. However, when complexity is lost, maximizing service provision requires a broader portfolio of management approaches, including the provision of artificial complexity, coral restoration, fish aggregation devices and herbivore management. Increased use of such management tools will require capacity building and technique refinement and we therefore conclude that diversification of our management toolbox should be considered urgently to prepare for the challenges of managing reefs into the 21st century. © 2014 John Wiley & Sons Ltd.

A structural model for the flexural mechanics of nonwoven tissue engineering scaffolds.

PubMed

Engelmayr, George C; Sacks, Michael S

2006-08-01

The development of methods to predict the strength and stiffness of biomaterials used in tissue engineering is critical for load-bearing applications in which the essential functional requirements are primarily mechanical. We previously quantified changes in the effective stiffness (E) of needled nonwoven polyglycolic acid (PGA) and poly-L-lactic acid (PLLA) scaffolds due to tissue formation and scaffold degradation under three-point bending. Toward predicting these changes, we present a structural model for E of a needled nonwoven scaffold in flexure. The model accounted for the number and orientation of fibers within a representative volume element of the scaffold demarcated by the needling process. The spring-like effective stiffness of the curved fibers was calculated using the sinusoidal fiber shapes. Structural and mechanical properties of PGA and PLLA fibers and PGA, PLLA, and 50:50 PGA/PLLA scaffolds were measured and compared with model predictions. To verify the general predictive capability, the predicted dependence of E on fiber diameter was compared with experimental measurements. Needled nonwoven scaffolds were found to exhibit distinct preferred (PD) and cross-preferred (XD) fiber directions, with an E ratio (PD/XD) of approximately 3:1. The good agreement between the predicted and experimental dependence of E on fiber diameter (R2 = 0.987) suggests that the structural model can be used to design scaffolds with E values more similar to native soft tissues. A comparison with previous results for cell-seeded scaffolds (Engelmayr, G. C., Jr., et al., 2005, Biomaterials, 26(2), pp. 175-187) suggests, for the first time, that the primary mechanical effect of collagen deposition is an increase in the number of fiber-fiber bond points yielding effectively stiffer scaffold fibers. This finding indicated that the effects of tissue deposition on needled nonwoven scaffold mechanics do not follow a rule-of-mixtures behavior. These important results underscore the need for structural approaches in modeling the effects of engineered tissue formation on nonwoven scaffolds, and their potential utility in scaffold design.

A search for H/ACA snoRNAs in yeast using MFE secondary structure prediction.

PubMed

Edvardsson, Sverker; Gardner, Paul P; Poole, Anthony M; Hendy, Michael D; Penny, David; Moulton, Vincent

2003-05-01

Noncoding RNA genes produce functional RNA molecules rather than coding for proteins. One such family is the H/ACA snoRNAs. Unlike the related C/D snoRNAs these have resisted automated detection to date. We develop an algorithm to screen the yeast genome for novel H/ACA snoRNAs. To achieve this, we introduce some new methods for facilitating the search for noncoding RNAs in genomic sequences which are based on properties of predicted minimum free-energy (MFE) secondary structures. The algorithm has been implemented and can be generalized to enable screening of other eukaryote genomes. We find that use of primary sequence alone is insufficient for identifying novel H/ACA snoRNAs. Only the use of secondary structure filters reduces the number of candidates to a manageable size. From genomic context, we identify three strong H/ACA snoRNA candidates. These together with a further 47 candidates obtained by our analysis are being experimentally screened.

Predicting plankton net community production in the Atlantic Ocean

NASA Astrophysics Data System (ADS)

Serret, Pablo; Robinson, Carol; Fernández, Emilio; Teira, Eva; Tilstone, Gavin; Pérez, Valesca

2009-07-01

We present, test and implement two contrasting models to predict euphotic zone net community production (NCP), which are based on 14C primary production (PO 14CP) to NCP relationships over two latitudinal (ca. 30°S-45°N) transects traversing highly productive and oligotrophic provinces of the Atlantic Ocean (NADR, CNRY, BENG, NAST-E, ETRA and SATL, Longhurst et al., 1995 [An estimation of global primary production in the ocean from satellite radiometer data. Journal of Plankton Research 17, 1245-1271]). The two models include similar ranges of PO 14CP and community structure, but differ in the relative influence of allochthonous organic matter in the oligotrophic provinces. Both models were used to predict NCP from PO 14CP measurements obtained during 11 local and three seasonal studies in the Atlantic, Pacific and Indian Oceans, and from satellite-derived estimates of PO 14CP. Comparison of these NCP predictions with concurrent in situ measurements and geochemical estimates of NCP showed that geographic and annual patterns of NCP can only be predicted when the relative trophic importance of local vs. distant processes is similar in both modeled and predicted ecosystems. The system-dependent ability of our models to predict NCP seasonality suggests that trophic-level dynamics are stronger than differences in hydrodynamic regime, taxonomic composition and phytoplankton growth. The regional differences in the predictive power of both models confirm the existence of biogeographic differences in the scale of trophic dynamics, which impede the use of a single generalized equation to estimate global marine plankton NCP. This paper shows the potential of a systematic empirical approach to predict plankton NCP from local and satellite-derived P estimates.

Could Values and Social Structures in Singapore Facilitate Attainment of Patient-Focused, Cultural, and Linguistic Competency Standards in a Patient-Centered Medical Home Pilot?

PubMed Central

Shih, Jenny A; Shiow, Sue-Anne Toh Ee; Wee, Hwee-Lin

2015-01-01

Primary care practices in the United States are transforming into patient-centered medical homes (PCMHs) at a rapid pace. Newer PCMH standards have emphasized culturally and linguistically appropriate services (CLAS), but at this time, only some states in the United States have proposed or passed cultural competency training for health care professionals. Other countries are moving to PCMH models. Singapore, a small, ethnically diverse island nation, has national values and social structures that emphasize cultural and linguistic cohesion. In this piece, we examine Singapore’s first PCMH pilot with a national academic center and primary care practice group. Features such as common shared values, self-reliance, racial and religious harmony, patient experience surveillance, and incorporation of CLAS standards in routine health care transactions may predict success for the PCMH in Singapore, with some implications for the United States. PMID:28725822

Predictive variables for the biological behaviour of basal cell carcinoma of the face: relevance of morphometry of the nuclei.

PubMed

Appel, T; Bierhoff, E; Appel, K; von Lindern, J-J; Bergé, S; Niederhagen, B

2003-06-01

We did a morphometric analysis of 130 histological sections of basal cell carcinoma (BCC) of the face to find out whether morphometric variables in the structure of the nuclei of BCC cells could serve as predictors of the biological behaviour. We considered the following variables: maximum and minimum diameters, perimeter, nuclear area and five form factors that characterise and quantify the shape of a structure (axis ratio, shape factor, nuclear contour index, nuclear roundness and circumference ratio). We did a statistical analysis of primary and recurring tumours and four histology-based groups (multifocal superficial BCCs, nodular BCCs, sclerosing BCCs and miscellaneous forms) using a two-sided t test for independent samples. Multifocal superficial BCCs showed significantly smaller values for the directly measured variables (maximum and minimum diameters, perimeter and nuclear area). Morphometry could not distinguish between primary and recurring tumours.

Elevated Temperature Crack Growth Behavior in HSCT Structural Materials

NASA Technical Reports Server (NTRS)

Saxena, Ashok

1998-01-01

Structures in super-sonic aircraft are subjected to conditions of high temperature and cyclic and sustained loading for extended periods of time. The durability of structures fabricated from aluminum and certain titanium alloys in such demanding conditions is of primary concern to the designers and manufacturers of futuristic transport aircraft. Accordingly, the major goal of this project was to evaluate the performance and durability of high temperature aluminum and titanium alloys for use in high speed civil transport (HSCT) structures. Additional goals were to develop time-dependent fracture mechanics methodology and test methods for characterizing and predicting elevated temperature crack growth behavior in creep-brittle materials such as ones being considered for use in HSCT structures and to explore accelerated methods of simulating microstructural degradation during service and measuring degraded properties in these materials.

Meta-ecosystem dynamics and functioning on finite spatial networks

PubMed Central

Marleau, Justin N.; Guichard, Frédéric; Loreau, Michel

2014-01-01

The addition of spatial structure to ecological concepts and theories has spurred integration between sub-disciplines within ecology, including community and ecosystem ecology. However, the complexity of spatial models limits their implementation to idealized, regular landscapes. We present a model meta-ecosystem with finite and irregular spatial structure consisting of local nutrient–autotrophs–herbivores ecosystems connected through spatial flows of materials and organisms. We study the effect of spatial flows on stability and ecosystem functions, and provide simple metrics of connectivity that can predict these effects. Our results show that high rates of nutrient and herbivore movement can destabilize local ecosystem dynamics, leading to spatially heterogeneous equilibria or oscillations across the meta-ecosystem, with generally increased meta-ecosystem primary and secondary production. However, the onset and the spatial scale of these emergent dynamics depend heavily on the spatial structure of the meta-ecosystem and on the relative movement rate of the autotrophs. We show how this strong dependence on finite spatial structure eludes commonly used metrics of connectivity, but can be predicted by the eigenvalues and eigenvectors of the connectivity matrix that describe the spatial structure and scale. Our study indicates the need to consider finite-size ecosystems in meta-ecosystem theory. PMID:24403323

Prediction of protein structural classes by Chou's pseudo amino acid composition: approached using continuous wavelet transform and principal component analysis.

PubMed

Li, Zhan-Chao; Zhou, Xi-Bin; Dai, Zong; Zou, Xiao-Yong

2009-07-01

A prior knowledge of protein structural classes can provide useful information about its overall structure, so it is very important for quick and accurate determination of protein structural class with computation method in protein science. One of the key for computation method is accurate protein sample representation. Here, based on the concept of Chou's pseudo-amino acid composition (AAC, Chou, Proteins: structure, function, and genetics, 43:246-255, 2001), a novel method of feature extraction that combined continuous wavelet transform (CWT) with principal component analysis (PCA) was introduced for the prediction of protein structural classes. Firstly, the digital signal was obtained by mapping each amino acid according to various physicochemical properties. Secondly, CWT was utilized to extract new feature vector based on wavelet power spectrum (WPS), which contains more abundant information of sequence order in frequency domain and time domain, and PCA was then used to reorganize the feature vector to decrease information redundancy and computational complexity. Finally, a pseudo-amino acid composition feature vector was further formed to represent primary sequence by coupling AAC vector with a set of new feature vector of WPS in an orthogonal space by PCA. As a showcase, the rigorous jackknife cross-validation test was performed on the working datasets. The results indicated that prediction quality has been improved, and the current approach of protein representation may serve as a useful complementary vehicle in classifying other attributes of proteins, such as enzyme family class, subcellular localization, membrane protein types and protein secondary structure, etc.

Accurate prediction of collapse temperature using optical coherence tomography-based freeze-drying microscopy.

PubMed

Greco, Kristyn; Mujat, Mircea; Galbally-Kinney, Kristin L; Hammer, Daniel X; Ferguson, R Daniel; Iftimia, Nicusor; Mulhall, Phillip; Sharma, Puneet; Kessler, William J; Pikal, Michael J

2013-06-01

The objective of this study was to assess the feasibility of developing and applying a laboratory tool that can provide three-dimensional product structural information during freeze-drying and which can accurately characterize the collapse temperature (Tc ) of pharmaceutical formulations designed for freeze-drying. A single-vial freeze dryer coupled with optical coherence tomography freeze-drying microscopy (OCT-FDM) was developed to investigate the structure and Tc of formulations in pharmaceutically relevant products containers (i.e., freeze-drying in vials). OCT-FDM was used to measure the Tc and eutectic melt of three formulations in freeze-drying vials. The Tc as measured by OCT-FDM was found to be predictive of freeze-drying with a batch of vials in a conventional laboratory freeze dryer. The freeze-drying cycles developed using OCT-FDM data, as compared with traditional light transmission freeze-drying microscopy (LT-FDM), resulted in a significant reduction in primary drying time, which could result in a substantial reduction of manufacturing costs while maintaining product quality. OCT-FDM provides quantitative data to justify freeze-drying at temperatures higher than the Tc measured by LT-FDM and provides a reliable upper limit to setting a product temperature in primary drying. Copyright © 2013 Wiley Periodicals, Inc.

Predicted structure of MIF/CD74 and RTL1000/CD74 complexes.

PubMed

Meza-Romero, Roberto; Benedek, Gil; Leng, Lin; Bucala, Richard; Vandenbark, Arthur A

2016-04-01

Macrophage migration inhibitory factor (MIF) is a key cytokine in autoimmune and inflammatory diseases that attracts and then retains activated immune cells from the periphery to the tissues. MIF exists as a homotrimer and its effects are mediated through its primary receptor, CD74 (the class II invariant chain that exhibits a highly structured trimerization domain), present on class II expressing cells. Although a number of binding residues have been identified between MIF and CD74 trimers, their spatial orientation has not been established. Using a docking program in silico, we have modeled binding interactions between CD74 and MIF as well as CD74 and a competitive MIF inhibitor, RTL1000, a partial MHC class II construct that is currently in clinical trials for multiple sclerosis. These analyses revealed 3 binding sites on the MIF trimer that each were predicted to bind one CD74 trimer through interactions with two distinct 5 amino acid determinants. Surprisingly, predicted binding of one CD74 trimer to a single RTL1000 antagonist utilized the same two 5 residue determinants, providing strong suggestive evidence in support of the MIF binding regions on CD74. Taken together, our structural modeling predicts a new MIF(CD74)3 dodecamer that may provide the basis for increased MIF potency and the requirement for ~3-fold excess RTL1000 to achieve full antagonism.

A mechanism-mediated model for carcinogenicity: Model content and prediction of the outcome of rodent carcinogenicity bioassays currently being conducted on 25 organic chemicals

DOE Office of Scientific and Technical Information (OSTI.GOV)

Purdy, R.

A hierarchical model consisting of quantitative structure-activity relationships based mainly on chemical reactivity was developed to predict the carcinogenicity of organic chemicals to rodents. The model is comprised of quantitative structure-activity relationships, QSARs based on hypothesized mechanisms of action, metabolism, and partitioning. Predictors included octanol/water partition coefficient, molecular size, atomic partial charge, bond angle strain, atomic acceptor delocalizibility, atomic radical superdelocalizibility, the lowest unoccupied molecular orbital (LUMO) energy of hypothesized intermediate nitrenium ion of primary aromatic amines, difference in charge of ionized and unionized carbon-chlorine bonds, substituent size and pattern on polynuclear aromatic hydrocarbons, the distance between lone electron pairsmore » over a rigid structure, and the presence of functionalities such as nitroso and hydrazine. The model correctly classified 96% of the carcinogens in the training set of 306 chemicals, and 90% of the carcinogens in the test set of 301 chemicals. The test set by chance contained 84% of the positive thiocontaining chemicals. A QSAR for these chemicals was developed. This posttest set modified model correctly predicted 94% of the carcinogens in the test set. This model was used to predict the carcinogenicity of the 25 organic chemicals the U.S. National Toxicology Program was testing at the writing of this article. 12 refs., 3 tabs.« less

Nonlinear analyses of composite aerospace structures in sonic fatigue

NASA Technical Reports Server (NTRS)

Mei, Chuh

1993-01-01

This report summarizes the semiannual research progress, accomplishments, and future plans performed under the NASA Langley Research Center Grant No. NAG-1-1358. The primary research effort of this project is the development of analytical methods for the prediction of nonlinear random response of composite aerospace structures subjected to combined acoustic and thermal loads. The progress, accomplishments, and future plates on four sonic fatigue research topics are described. The sonic fatigue design and passive control of random response of shape memory alloy hybrid composites presented in section 4, which is suited especially for HSCT, is a new initiative.

Nonlinear analyses of composite aerospace structures in sonic fatigue

NASA Astrophysics Data System (ADS)

Mei, Chuh

1993-06-01

This report summarizes the semiannual research progress, accomplishments, and future plans performed under the NASA Langley Research Center Grant No. NAG-1-1358. The primary research effort of this project is the development of analytical methods for the prediction of nonlinear random response of composite aerospace structures subjected to combined acoustic and thermal loads. The progress, accomplishments, and future plates on four sonic fatigue research topics are described. The sonic fatigue design and passive control of random response of shape memory alloy hybrid composites presented in section 4, which is suited especially for HSCT, is a new initiative.

Simplified Model to Predict Deflection and Natural Frequency of Steel Pole Structures

NASA Astrophysics Data System (ADS)

Balagopal, R.; Prasad Rao, N.; Rokade, R. P.

2018-04-01

Steel pole structures are suitable alternate to transmission line towers, due to difficulty encountered in finding land for the new right of way for installation of new lattice towers. The steel poles have tapered cross section and they are generally used for communication, power transmission and lighting purposes. Determination of deflection of steel pole is important to decide its functionality requirement. The excessive deflection of pole may affect the signal attenuation and short circuiting problems in communication/transmission poles. In this paper, a simplified method is proposed to determine both primary and secondary deflection based on dummy unit load/moment method. The predicted deflection from proposed method is validated with full scale experimental investigation conducted on 8 m and 30 m high lighting mast, 132 and 400 kV transmission pole and found to be in close agreement with each other. Determination of natural frequency is an important criterion to examine its dynamic sensitivity. A simplified semi-empirical method using the static deflection from the proposed method is formulated to determine its natural frequency. The natural frequency predicted from proposed method is validated with FE analysis results. Further the predicted results are validated with experimental results available in literature.

Using Lidar and Radar measurements to constrain predictions of forest ecosystem structure and function.

PubMed

Antonarakis, Alexander S; Saatchi, Sassan S; Chazdon, Robin L; Moorcroft, Paul R

2011-06-01

Insights into vegetation and aboveground biomass dynamics within terrestrial ecosystems have come almost exclusively from ground-based forest inventories that are limited in their spatial extent. Lidar and synthetic-aperture Radar are promising remote-sensing-based techniques for obtaining comprehensive measurements of forest structure at regional to global scales. In this study we investigate how Lidar-derived forest heights and Radar-derived aboveground biomass can be used to constrain the dynamics of the ED2 terrestrial biosphere model. Four-year simulations initialized with Lidar and Radar structure variables were compared against simulations initialized from forest-inventory data and output from a long-term potential-vegtation simulation. Both height and biomass initializations from Lidar and Radar measurements significantly improved the representation of forest structure within the model, eliminating the bias of too many large trees that arose in the potential-vegtation-initialized simulation. The Lidar and Radar initializations decreased the proportion of larger trees estimated by the potential vegetation by approximately 20-30%, matching the forest inventory. This resulted in improved predictions of ecosystem-scale carbon fluxes and structural dynamics compared to predictions from the potential-vegtation simulation. The Radar initialization produced biomass values that were 75% closer to the forest inventory, with Lidar initializations producing canopy height values closest to the forest inventory. Net primary production values for the Radar and Lidar initializations were around 6-8% closer to the forest inventory. Correcting the Lidar and Radar initializations for forest composition resulted in improved biomass and basal-area dynamics as well as leaf-area index. Correcting the Lidar and Radar initializations for forest composition and fine-scale structure by combining the remote-sensing measurements with ground-based inventory data further improved predictions, suggesting that further improvements of structural and carbon-flux metrics will also depend on obtaining reliable estimates of forest composition and accurate representation of the fine-scale vertical and horizontal structure of plant canopies.

Structural stability, vibrational, and bonding properties of potassium 1, 1'-dinitroamino-5, 5'-bistetrazolate: An emerging green primary explosive.

PubMed

Yedukondalu, N; Vaitheeswaran, G

2015-08-14

Potassium 1,1'-dinitroamino-5,5'-bistetrazolate (K2DNABT) is a nitrogen rich (50.3% by weight, K2C2N12O4) green primary explosive with high performance characteristics, namely, velocity of detonation (D = 8.33 km/s), detonation pressure (P = 31.7 GPa), and fast initiating power to replace existing toxic primaries. In the present work, we report density functional theory (DFT) calculations on structural, equation of state, vibrational spectra, electronic structure, and absorption spectra of K2DNABT. We have discussed the influence of weak dispersive interactions on structural and vibrational properties through the DFT-D2 method. We find anisotropic compressibility behavior (b

Patient Reactance as a Moderator of the Effect of Therapist Structure on Posttreatment Alcohol Use*

PubMed Central

Karno, Mitchell P.; Longabaugh, Richard; Herbeck, Diane

2009-01-01

Objective: We sought to replicate findings about the effect of therapist-imposed structure on alcoholism-treatment effectiveness for aftercare patients at different levels of interpersonal reactance and to examine if the effect generalizes to patients in a primary phase of treatment. Method: Analyses were based on ex post facto observer ratings combined with outcome data from a randomized clinical trial. Participants had alcohol abuse or dependence (N = 247) and received treatment at either a primary outpatient treatment site (n = 125) or an aftercare site (n = 122) of Project MATCH (Matching Alcoholism Treatments to Client Heterogeneity). Patients' trait reactance and therapist structure were assessed via observer ratings based on videotaped therapy sessions. Dependent variables included percentage days abstinent, percentage heavy-drinking days, time to first drinking day, and time to first heavy-drinking day throughout a 1-year posttreatment period. Results: The results indicated that increased therapist structure during aftercare treatment predicted fewer abstinent days and more heavy-drinking days for persons at a high level of reactance than for persons at a low level of reactance. The effect was a consistent predictor of alcohol use throughout each 3-month interval within the follow-up period. The interaction effect was not supported in the primary outpatient treatment sites, and it was not supported as a predictor of time to first drink or time to first heavy drink in either the aftercare or the outpatient sites. Conclusions: This study successfully replicated the finding that level of patient reactance appears to moderate the effect of therapist structure on alcohol-use outcomes in aftercare treatment settings. The lack of support for this effect in primary outpatient treatment settings suggests that the negative effect of structured treatment may be limited to patients who are further along in the recovery process. PMID:19895770

Structural stability, vibrational, and bonding properties of potassium 1, 1'-dinitroamino-5, 5'-bistetrazolate: An emerging green primary explosive

NASA Astrophysics Data System (ADS)

Yedukondalu, N.; Vaitheeswaran, G.

2015-08-01

Potassium 1,1'-dinitroamino-5,5'-bistetrazolate (K2DNABT) is a nitrogen rich (50.3% by weight, K2C2N12O4) green primary explosive with high performance characteristics, namely, velocity of detonation (D = 8.33 km/s), detonation pressure (P = 31.7 GPa), and fast initiating power to replace existing toxic primaries. In the present work, we report density functional theory (DFT) calculations on structural, equation of state, vibrational spectra, electronic structure, and absorption spectra of K2DNABT. We have discussed the influence of weak dispersive interactions on structural and vibrational properties through the DFT-D2 method. We find anisotropic compressibility behavior (b

Anomalous Putamen Volume in Children With Complex Motor Stereotypies.

PubMed

Mahone, E Mark; Crocetti, Deana; Tochen, Laura; Kline, Tina; Mostofsky, Stewart H; Singer, Harvey S

2016-12-01

Complex motor stereotypies in children are repetitive rhythmic movements that have a predictable pattern and location, seem purposeful, but serve no obvious function, tend to be prolonged, and stop with distraction, e.g., arm or hand flapping, waving. They occur in both "primary" (otherwise typically developing) and secondary conditions. These movements are best defined as habitual behaviors and therefore pathophysiologically hypothesized to reside in premotor to posterior putamen circuits. This study sought to clarify the underlying neurobiologic abnormality in children with primary complex motor stereotypies using structural neuroimaging, emphasizing brain regions hypothesized to underlie these atypical behaviors. High-resolution anatomic magnetic resonance images, acquired at 3.0 T, were analyzed in children aged eight to twelve years (20 with primary complex motor stereotypies and 20 typically developing). Frontal lobe subregions and striatal structures were delineated for analysis. Significant reductions (P = 0.045) in the stereotypies group were identified in total putamen volume but not in caudate, nucleus accumbens, or frontal subregions. There were no group differences in total cerebral volume. Findings of a smaller putamen provide preliminary evidence suggesting the potential involvement of the habitual pathway as the underlying anatomic site in primary complex motor stereotypies. Copyright © 2016 Elsevier Inc. All rights reserved.

Recovery of known T-cell epitopes by computational scanning of a viral genome

NASA Astrophysics Data System (ADS)

Logean, Antoine; Rognan, Didier

2002-04-01

A new computational method (EpiDock) is proposed for predicting peptide binding to class I MHC proteins, from the amino acid sequence of any protein of immunological interest. Starting from the primary structure of the target protein, individual three-dimensional structures of all possible MHC-peptide (8-, 9- and 10-mers) complexes are obtained by homology modelling. A free energy scoring function (Fresno) is then used to predict the absolute binding free energy of all possible peptides to the class I MHC restriction protein. Assuming that immunodominant epitopes are usually found among the top MHC binders, the method can thus be applied to predict the location of immunogenic peptides on the sequence of the protein target. When applied to the prediction of HLA-A*0201-restricted T-cell epitopes from the Hepatitis B virus, EpiDock was able to recover 92% of known high affinity binders and 80% of known epitopes within a filtered subset of all possible nonapeptides corresponding to about one tenth of the full theoretical list. The proposed method is fully automated and fast enough to scan a viral genome in less than an hour on a parallel computing architecture. As it requires very few starting experimental data, EpiDock can be used: (i) to predict potential T-cell epitopes from viral genomes (ii) to roughly predict still unknown peptide binding motifs for novel class I MHC alleles.

Predicting the response of olfactory sensory neurons to odor mixtures from single odor response

NASA Astrophysics Data System (ADS)

Marasco, Addolorata; de Paris, Alessandro; Migliore, Michele

2016-04-01

The response of olfactory receptor neurons to odor mixtures is not well understood. Here, using experimental constraints, we investigate the mathematical structure of the odor response space and its consequences. The analysis suggests that the odor response space is 3-dimensional, and predicts that the dose-response curve of an odor receptor can be obtained, in most cases, from three primary components with specific properties. This opens the way to an objective procedure to obtain specific olfactory receptor responses by manipulating mixtures in a mathematically predictable manner. This result is general and applies, independently of the number of odor components, to any olfactory sensory neuron type with a response curve that can be represented as a sigmoidal function of the odor concentration.

The spatial structure of a nonlinear receptive field.

PubMed

Schwartz, Gregory W; Okawa, Haruhisa; Dunn, Felice A; Morgan, Josh L; Kerschensteiner, Daniel; Wong, Rachel O; Rieke, Fred

2012-11-01

Understanding a sensory system implies the ability to predict responses to a variety of inputs from a common model. In the retina, this includes predicting how the integration of signals across visual space shapes the outputs of retinal ganglion cells. Existing models of this process generalize poorly to predict responses to new stimuli. This failure arises in part from properties of the ganglion cell response that are not well captured by standard receptive-field mapping techniques: nonlinear spatial integration and fine-scale heterogeneities in spatial sampling. Here we characterize a ganglion cell's spatial receptive field using a mechanistic model based on measurements of the physiological properties and connectivity of only the primary excitatory circuitry of the retina. The resulting simplified circuit model successfully predicts ganglion-cell responses to a variety of spatial patterns and thus provides a direct correspondence between circuit connectivity and retinal output.

Synergy between NMR measurements and MD simulations of protein/RNA complexes: application to the RRMs, the most common RNA recognition motifs

PubMed Central

Krepl, Miroslav; Cléry, Antoine; Blatter, Markus; Allain, Frederic H.T.; Sponer, Jiri

2016-01-01

RNA recognition motif (RRM) proteins represent an abundant class of proteins playing key roles in RNA biology. We present a joint atomistic molecular dynamics (MD) and experimental study of two RRM-containing proteins bound with their single-stranded target RNAs, namely the Fox-1 and SRSF1 complexes. The simulations are used in conjunction with NMR spectroscopy to interpret and expand the available structural data. We accumulate more than 50 μs of simulations and show that the MD method is robust enough to reliably describe the structural dynamics of the RRM–RNA complexes. The simulations predict unanticipated specific participation of Arg142 at the protein–RNA interface of the SRFS1 complex, which is subsequently confirmed by NMR and ITC measurements. Several segments of the protein–RNA interface may involve competition between dynamical local substates rather than firmly formed interactions, which is indirectly consistent with the primary NMR data. We demonstrate that the simulations can be used to interpret the NMR atomistic models and can provide qualified predictions. Finally, we propose a protocol for ‘MD-adapted structure ensemble’ as a way to integrate the simulation predictions and expand upon the deposited NMR structures. Unbiased μs-scale atomistic MD could become a technique routinely complementing the NMR measurements of protein–RNA complexes. PMID:27193998

Use of restrained molecular dynamics to predict the conformations of phosphorylated receiver domains in two-component signaling systems.

PubMed

Foster, Clay A; West, Ann H

2017-01-01

Two-component signaling (TCS) is the primary means by which bacteria, as well as certain plants and fungi, respond to external stimuli. Signal transduction involves stimulus-dependent autophosphorylation of a sensor histidine kinase and phosphoryl transfer to the receiver domain of a downstream response regulator. Phosphorylation acts as an allosteric switch, inducing structural and functional changes in the pathway's components. Due to their transient nature, phosphorylated receiver domains are challenging to characterize structurally. In this work, we provide a methodology for simulating receiver domain phosphorylation to predict conformations that are nearly identical to experimental structures. Using restrained molecular dynamics, phosphorylated conformations of receiver domains can be reliably sampled on nanosecond timescales. These simulations also provide data on conformational dynamics that can be used to identify regions of functional significance related to phosphorylation. We first validated this approach on several well-characterized receiver domains and then used it to compare the upstream and downstream components of the fungal Sln1 phosphorelay. Our results demonstrate that this technique provides structural insight, obtained in the absence of crystallographic or NMR information, regarding phosphorylation-induced conformational changes in receiver domains that regulate the output of their associated signaling pathway. To our knowledge, this is the first time such a protocol has been described that can be broadly applied to TCS proteins for predictive purposes. Proteins 2016; 85:155-176. © 2016 Wiley Periodicals, Inc. © 2016 The Authors Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.

Happiness as a motivator: positive affect predicts primary control striving for career and educational goals.

PubMed

Haase, Claudia M; Poulin, Michael J; Heckhausen, Jutta

2012-08-01

What motivates individuals to invest time and effort and overcome obstacles (i.e., strive for primary control) when pursuing important goals? We propose that positive affect predicts primary control striving for career and educational goals, and we explore the mediating role of control beliefs. In Study 1, positive affect predicted primary control striving for career goals in a two-wave longitudinal study of a U.S. sample. In Study 2, positive affect predicted primary control striving for career and educational goals and objective career outcomes in a six-wave longitudinal study of a German sample. Control beliefs partially mediated the longitudinal associations with primary control striving. Thus, when individuals experience positive affect, they become more motivated to invest time and effort, and overcome obstacles when pursuing their goals, in part because they believe they have more control over attaining their goals.

Ocean acidification and rising temperatures may increase biofilm primary productivity but decrease grazer consumption

PubMed Central

Russell, Bayden D.; Connell, Sean D.; Findlay, Helen S.; Tait, Karen; Widdicombe, Stephen; Mieszkowska, Nova

2013-01-01

Climate change may cause ecosystems to become trophically restructured as a result of primary producers and consumers responding differently to increasing CO2 and temperature. This study used an integrative approach using a controlled microcosm experiment to investigate the combined effects of CO2 and temperature on key components of the intertidal system in the UK, biofilms and their consumers (Littorina littorea). In addition, to identify whether pre-exposure to experimental conditions can alter experimental outcomes we explicitly tested for differential effects on L. littorea pre-exposed to experimental conditions for two weeks and five months. In contrast to predictions based on metabolic theory, the combination of elevated temperature and CO2 over a five-week period caused a decrease in the amount of primary productivity consumed by grazers, while the abundance of biofilms increased. However, long-term pre-exposure to experimental conditions (five months) altered this effect, with grazing rates in these animals being greater than in animals exposed only for two weeks. We suggest that the structure of future ecosystems may not be predictable using short-term laboratory experiments alone owing to potentially confounding effects of exposure time and effects of being held in an artificial environment over prolonged time periods. A combination of laboratory (physiology responses) and large, long-term experiments (ecosystem responses) may therefore be necessary to adequately predict the complex and interactive effects of climate change as organisms may acclimate to conditions over the longer term. PMID:23980241

Ocean acidification and rising temperatures may increase biofilm primary productivity but decrease grazer consumption.

PubMed

Russell, Bayden D; Connell, Sean D; Findlay, Helen S; Tait, Karen; Widdicombe, Stephen; Mieszkowska, Nova

2013-01-01

Climate change may cause ecosystems to become trophically restructured as a result of primary producers and consumers responding differently to increasing CO2 and temperature. This study used an integrative approach using a controlled microcosm experiment to investigate the combined effects of CO2 and temperature on key components of the intertidal system in the UK, biofilms and their consumers (Littorina littorea). In addition, to identify whether pre-exposure to experimental conditions can alter experimental outcomes we explicitly tested for differential effects on L. littorea pre-exposed to experimental conditions for two weeks and five months. In contrast to predictions based on metabolic theory, the combination of elevated temperature and CO2 over a five-week period caused a decrease in the amount of primary productivity consumed by grazers, while the abundance of biofilms increased. However, long-term pre-exposure to experimental conditions (five months) altered this effect, with grazing rates in these animals being greater than in animals exposed only for two weeks. We suggest that the structure of future ecosystems may not be predictable using short-term laboratory experiments alone owing to potentially confounding effects of exposure time and effects of being held in an artificial environment over prolonged time periods. A combination of laboratory (physiology responses) and large, long-term experiments (ecosystem responses) may therefore be necessary to adequately predict the complex and interactive effects of climate change as organisms may acclimate to conditions over the longer term.

A model of attention-guided visual perception and recognition.

PubMed

Rybak, I A; Gusakova, V I; Golovan, A V; Podladchikova, L N; Shevtsova, N A

1998-08-01

A model of visual perception and recognition is described. The model contains: (i) a low-level subsystem which performs both a fovea-like transformation and detection of primary features (edges), and (ii) a high-level subsystem which includes separated 'what' (sensory memory) and 'where' (motor memory) structures. Image recognition occurs during the execution of a 'behavioral recognition program' formed during the primary viewing of the image. The recognition program contains both programmed attention window movements (stored in the motor memory) and predicted image fragments (stored in the sensory memory) for each consecutive fixation. The model shows the ability to recognize complex images (e.g. faces) invariantly with respect to shift, rotation and scale.

Behavioural and neuroanatomical correlates of auditory speech analysis in primary progressive aphasias.

PubMed

Hardy, Chris J D; Agustus, Jennifer L; Marshall, Charles R; Clark, Camilla N; Russell, Lucy L; Bond, Rebecca L; Brotherhood, Emilie V; Thomas, David L; Crutch, Sebastian J; Rohrer, Jonathan D; Warren, Jason D

2017-07-27

Non-verbal auditory impairment is increasingly recognised in the primary progressive aphasias (PPAs) but its relationship to speech processing and brain substrates has not been defined. Here we addressed these issues in patients representing the non-fluent variant (nfvPPA) and semantic variant (svPPA) syndromes of PPA. We studied 19 patients with PPA in relation to 19 healthy older individuals. We manipulated three key auditory parameters-temporal regularity, phonemic spectral structure and prosodic predictability (an index of fundamental information content, or entropy)-in sequences of spoken syllables. The ability of participants to process these parameters was assessed using two-alternative, forced-choice tasks and neuroanatomical associations of task performance were assessed using voxel-based morphometry of patients' brain magnetic resonance images. Relative to healthy controls, both the nfvPPA and svPPA groups had impaired processing of phonemic spectral structure and signal predictability while the nfvPPA group additionally had impaired processing of temporal regularity in speech signals. Task performance correlated with standard disease severity and neurolinguistic measures. Across the patient cohort, performance on the temporal regularity task was associated with grey matter in the left supplementary motor area and right caudate, performance on the phoneme processing task was associated with grey matter in the left supramarginal gyrus, and performance on the prosodic predictability task was associated with grey matter in the right putamen. Our findings suggest that PPA syndromes may be underpinned by more generic deficits of auditory signal analysis, with a distributed cortico-subcortical neuraoanatomical substrate extending beyond the canonical language network. This has implications for syndrome classification and biomarker development.

Predicting the performance of a strategic alliance: an analysis of the Community Clinical Oncology Program.

PubMed

Kaluzny, A D; Lacey, L M; Warnecke, R; Hynes, D M; Morrissey, J; Ford, L; Sondik, E

1993-06-01

This study is designed to examine the effects of environment and structure of the Community Clinical Oncology Program (CCOP) on performance as measured by patient accrual to National Cancer Institute (NCI)-approved treatment protocols. Data and analysis are part of a larger evaluation of the NCI Community Clinical Oncology Program during its second funding cycle, June 1987-May 1990. Data, taken from primary and secondary sources, included a survey of selected informants in CCOPs and research bases, CCOP grant applications, CCOP annual progress reports, and site visits to a subsample of CCOPs (N = 20) and research bases (N = 5). Accrual data were obtained from NCI records. Analysis involved three complementary sets of factors: the local health care resources environment available to the CCOP, the larger policy environment as reflected by the relationship of the CCOP to selected research bases and the NCI, and the operational structure of the CCOP itself. A hierarchical model examined the separate and cumulative effects of local and policy environment and structure on performance. Other things equal, the primary predictors of treatment accrual were: (1) the larger policy environment, as measured by the attendance of nurses at research base meetings; and (2) operational structure, as measured by the number and character of components within participating CCOPs and the number of hours per week worked by data managers. These factors explained 73 percent of the total variance in accrual performance. Findings suggest criteria for selecting the types of organizations to participate in the alliance, as well as for establishing guidelines for managing such alliances. A future challenge is to determine the extent to which factors predicting accrual to cancer treatment clinical trials are equally important as predictors of accrual to cancer prevention and control trials.

Hominoid visual brain structure volumes and the position of the lunate sulcus.

PubMed

de Sousa, Alexandra A; Sherwood, Chet C; Mohlberg, Hartmut; Amunts, Katrin; Schleicher, Axel; MacLeod, Carol E; Hof, Patrick R; Frahm, Heiko; Zilles, Karl

2010-04-01

It has been argued that changes in the relative sizes of visual system structures predated an increase in brain size and provide evidence of brain reorganization in hominins. However, data about the volume and anatomical limits of visual brain structures in the extant taxa phylogenetically closest to humans-the apes-remain scarce, thus complicating tests of hypotheses about evolutionary changes. Here, we analyze new volumetric data for the primary visual cortex and the lateral geniculate nucleus to determine whether or not the human brain departs from allometrically-expected patterns of brain organization. Primary visual cortex volumes were compared to lunate sulcus position in apes to investigate whether or not inferences about brain reorganization made from fossil hominin endocasts are reliable in this context. In contrast to previous studies, in which all species were relatively poorly sampled, the current study attempted to evaluate the degree of intraspecific variability by including numerous hominoid individuals (particularly Pan troglodytes and Homo sapiens). In addition, we present and compare volumetric data from three new hominoid species-Pan paniscus, Pongo pygmaeus, and Symphalangus syndactylus. These new data demonstrate that hominoid visual brain structure volumes vary more than previously appreciated. In addition, humans have relatively reduced primary visual cortex and lateral geniculate nucleus volumes as compared to allometric predictions from other hominoids. These results suggest that inferences about the position of the lunate sulcus on fossil endocasts may provide information about brain organization. Copyright 2010 Elsevier Ltd. All rights reserved.

Cosmological structure formation in Decaying Dark Matter models

NASA Astrophysics Data System (ADS)

Cheng, Dalong; Chu, M.-C.; Tang, Jiayu

2015-07-01

The standard cold dark matter (CDM) model predicts too many and too dense small structures. We consider an alternative model that the dark matter undergoes two-body decays with cosmological lifetime τ into only one type of massive daughters with non-relativistic recoil velocity Vk. This decaying dark matter model (DDM) can suppress the structure formation below its free-streaming scale at time scale comparable to τ. Comparing with warm dark matter (WDM), DDM can better reduce the small structures while being consistent with high redshfit observations. We study the cosmological structure formation in DDM by performing self-consistent N-body simulations and point out that cosmological simulations are necessary to understand the DDM structures especially on non-linear scales. We propose empirical fitting functions for the DDM suppression of the mass function and the concentration-mass relation, which depend on the decay parameters lifetime τ, recoil velocity Vk and redshift. The fitting functions lead to accurate reconstruction of the the non-linear power transfer function of DDM to CDM in the framework of halo model. Using these results, we set constraints on the DDM parameter space by demanding that DDM does not induce larger suppression than the Lyman-α constrained WDM models. We further generalize and constrain the DDM models to initial conditions with non-trivial mother fractions and show that the halo model predictions are still valid after considering a global decayed fraction. Finally, we point out that the DDM is unlikely to resolve the disagreement on cluster numbers between the Planck primary CMB prediction and the Sunyaev-Zeldovich (SZ) effect number count for τ ~ H0-1.

Interior noise prediction methodology: ATDAC theory and validation

NASA Technical Reports Server (NTRS)

Mathur, Gopal P.; Gardner, Bryce K.

1992-01-01

The Acoustical Theory for Design of Aircraft Cabins (ATDAC) is a computer program developed to predict interior noise levels inside aircraft and to evaluate the effects of different aircraft configurations on the aircraft acoustical environment. The primary motivation for development of this program is the special interior noise problems associated with advanced turboprop (ATP) aircraft where there is a tonal, low frequency noise problem. Prediction of interior noise levels requires knowledge of the energy sources, the transmission paths, and the relationship between the energy variable and the sound pressure level. The energy sources include engine noise, both airborne and structure-borne; turbulent boundary layer noise; and interior noise sources such as air conditioner noise and auxiliary power unit noise. Since propeller and engine noise prediction programs are widely available, they are not included in ATDAC. Airborne engine noise from any prediction or measurement may be input to this program. This report describes the theory and equations implemented in the ATDAC program.

Interior noise prediction methodology: ATDAC theory and validation

NASA Astrophysics Data System (ADS)

Mathur, Gopal P.; Gardner, Bryce K.

1992-04-01

The Acoustical Theory for Design of Aircraft Cabins (ATDAC) is a computer program developed to predict interior noise levels inside aircraft and to evaluate the effects of different aircraft configurations on the aircraft acoustical environment. The primary motivation for development of this program is the special interior noise problems associated with advanced turboprop (ATP) aircraft where there is a tonal, low frequency noise problem. Prediction of interior noise levels requires knowledge of the energy sources, the transmission paths, and the relationship between the energy variable and the sound pressure level. The energy sources include engine noise, both airborne and structure-borne; turbulent boundary layer noise; and interior noise sources such as air conditioner noise and auxiliary power unit noise. Since propeller and engine noise prediction programs are widely available, they are not included in ATDAC. Airborne engine noise from any prediction or measurement may be input to this program. This report describes the theory and equations implemented in the ATDAC program.

Comparative analysis of predictive models for nongenotoxic hepatocarcinogenicity using both toxicogenomics and quantitative structure-activity relationships.

PubMed

Liu, Zhichao; Kelly, Reagan; Fang, Hong; Ding, Don; Tong, Weida

2011-07-18

The primary testing strategy to identify nongenotoxic carcinogens largely relies on the 2-year rodent bioassay, which is time-consuming and labor-intensive. There is an increasing effort to develop alternative approaches to prioritize the chemicals for, supplement, or even replace the cancer bioassay. In silico approaches based on quantitative structure-activity relationships (QSAR) are rapid and inexpensive and thus have been investigated for such purposes. A slightly more expensive approach based on short-term animal studies with toxicogenomics (TGx) represents another attractive option for this application. Thus, the primary questions are how much better predictive performance using short-term TGx models can be achieved compared to that of QSAR models, and what length of exposure is sufficient for high quality prediction based on TGx. In this study, we developed predictive models for rodent liver carcinogenicity using gene expression data generated from short-term animal models at different time points and QSAR. The study was focused on the prediction of nongenotoxic carcinogenicity since the genotoxic chemicals can be inexpensively removed from further development using various in vitro assays individually or in combination. We identified 62 chemicals whose hepatocarcinogenic potential was available from the National Center for Toxicological Research liver cancer database (NCTRlcdb). The gene expression profiles of liver tissue obtained from rats treated with these chemicals at different time points (1 day, 3 days, and 5 days) are available from the Gene Expression Omnibus (GEO) database. Both TGx and QSAR models were developed on the basis of the same set of chemicals using the same modeling approach, a nearest-centroid method with a minimum redundancy and maximum relevancy-based feature selection with performance assessed using compound-based 5-fold cross-validation. We found that the TGx models outperformed QSAR in every aspect of modeling. For example, the TGx models' predictive accuracy (0.77, 0.77, and 0.82 for the 1-day, 3-day, and 5-day models, respectively) was much higher for an independent validation set than that of a QSAR model (0.55). Permutation tests confirmed the statistical significance of the model's prediction performance. The study concluded that a short-term 5-day TGx animal model holds the potential to predict nongenotoxic hepatocarcinogenicity. © 2011 American Chemical Society

Linear regression models for solvent accessibility prediction in proteins.

PubMed

Wagner, Michael; Adamczak, Rafał; Porollo, Aleksey; Meller, Jarosław

2005-04-01

The relative solvent accessibility (RSA) of an amino acid residue in a protein structure is a real number that represents the solvent exposed surface area of this residue in relative terms. The problem of predicting the RSA from the primary amino acid sequence can therefore be cast as a regression problem. Nevertheless, RSA prediction has so far typically been cast as a classification problem. Consequently, various machine learning techniques have been used within the classification framework to predict whether a given amino acid exceeds some (arbitrary) RSA threshold and would thus be predicted to be "exposed," as opposed to "buried." We have recently developed novel methods for RSA prediction using nonlinear regression techniques which provide accurate estimates of the real-valued RSA and outperform classification-based approaches with respect to commonly used two-class projections. However, while their performance seems to provide a significant improvement over previously published approaches, these Neural Network (NN) based methods are computationally expensive to train and involve several thousand parameters. In this work, we develop alternative regression models for RSA prediction which are computationally much less expensive, involve orders-of-magnitude fewer parameters, and are still competitive in terms of prediction quality. In particular, we investigate several regression models for RSA prediction using linear L1-support vector regression (SVR) approaches as well as standard linear least squares (LS) regression. Using rigorously derived validation sets of protein structures and extensive cross-validation analysis, we compare the performance of the SVR with that of LS regression and NN-based methods. In particular, we show that the flexibility of the SVR (as encoded by metaparameters such as the error insensitivity and the error penalization terms) can be very beneficial to optimize the prediction accuracy for buried residues. We conclude that the simple and computationally much more efficient linear SVR performs comparably to nonlinear models and thus can be used in order to facilitate further attempts to design more accurate RSA prediction methods, with applications to fold recognition and de novo protein structure prediction methods.

The sensitivities of in cloud and cloud top phase distributions to primary ice formation in ICON-LEM

NASA Astrophysics Data System (ADS)

Beydoun, H.; Karrer, M.; Tonttila, J.; Hoose, C.

2017-12-01

Mixed phase clouds remain a leading source of uncertainty in our attempt to quantify cloud-climate and aerosol-cloud climate interactions. Nevertheless, recent advances in parametrizing the primary ice formation process, high resolution cloud modelling, and retrievals of cloud phase distributions from satellite data offer an excellent opportunity to conduct closure studies on the sensitivity of the cloud phase to microphysical and dynamical processes. Particularly, the reliability of satellite data to resolve the phase at the top of the cloud provides a promising benchmark to compare model output to. We run large eddy simulations with the new ICOsahedral Non-hydrostatic atmosphere model (ICON) to place bounds on the sensitivity of in cloud and cloud top phase to the primary ice formation process. State of the art primary ice formation parametrizations in the form of the cumulative ice active site density ns are implemented in idealized deep convective cloud simulations. We exploit the ability of ICON-LEM to switch between a two moment microphysics scheme and the newly developed Predicted Particle Properties (P3) scheme by running our simulations in both configurations for comparison. To quantify the sensitivity of cloud phase to primary ice formation, cloud ice content is evaluated against order of magnitude changes in ns at variable convective strengths. Furthermore, we assess differences between in cloud and cloud top phase distributions as well as the potential impact of updraft velocity on the suppression of the Wegener-Bergeron-Findeisen process. The study aims to evaluate our practical understanding of primary ice formation in the context of predicting the structure and evolution of mixed phase clouds.

Pattern of tumour growth of the primary colon cancer predicts long-term outcome after resection of liver metastases.

PubMed

Spelt, Lidewij; Sasor, Agata; Ansari, Daniel; Andersson, Roland

2016-10-01

To identify significant predictive factors for overall survival (OS) and disease-free survival (DFS) after liver resection for colon cancer metastases, with special focus on features of the primary colon cancer, such as lymph node ratio (LNR), vascular invasion, and perineural invasion. Patients operated for colonic cancer liver metastases between 2006 and 2014 were included. Details on patient characteristics, the primary colon cancer operation and metastatic disease were collected. Multivariate analysis was performed to select predictive variables for OS and DFS. Median OS and DFS were 67 and 20 months, respectively. 1-, 3- and 5-year OS were 97, 76, and 52%. 1-, 3- and 5-year DFS were 65, 42, and 37%. Multivariate analysis showed LNR to be an independent predictive factor for DFS but not for OS. Other identified predictive factors were vascular and perineural invasion of the primary colon cancer, size of the largest metastasis and severe complications after liver surgery for OS, and perineural invasion, number of liver metastases and preoperative CEA-level for DFS. Traditional N-stage was also considered to be an independent predictive factor for DFS in a separate multivariate analysis. LNR and perineural invasion of the primary colon cancer can be used as a prognostic variable for DFS after a concomitant liver resection for colon cancer metastases. Vascular and perineural invasion of the primary colon cancer are predictive for OS.

Primary Versus Secondary Diagnosis of Generalized Anxiety Disorder in Youth: Is the Distinction an Important One?

PubMed

Ollendick, Thomas H; Jarrett, Matthew A; White, Bradley A; White, Susan W; Grills, Amie E

2016-08-01

Examine whether children with a primary diagnosis of generalized anxiety disorder (GAD) differ from children with a secondary diagnosis of GAD on clinician, parent, teacher, and youth-report measures. Based on consensus diagnoses, 64 youth referred to a general outpatient assessment clinic were categorized as having either a primary or secondary diagnosis of GAD. A semi-structured diagnostic interview was used to guide diagnostic decisions and assign primary versus secondary diagnostic status. We predicted that youth with a primary GAD diagnosis would present with greater anxiety symptomatology and symptom impairment on a variety of anxiety-related measures than youth with a secondary GAD diagnosis. Contrary to our hypotheses, no differences were found between those with primary versus secondary GAD diagnoses on measures of symptom severity and clinical impairment, comorbid diagnoses, or youth and teacher-report measures. Our findings have potential implications for the current practice of requiring primary anxiety diagnostic status as an inclusion criterion in clinical research and treatment outcome studies. Assuming our findings are confirmed in larger samples and with other anxiety disorders, future clinical trials and basic psychopathology research might not exclude youth based on absence of a particular anxiety disorder as the primary disorder but rather include individuals for whom that anxiety disorder is secondary as well.

A deep learning framework for improving long-range residue-residue contact prediction using a hierarchical strategy.

PubMed

Xiong, Dapeng; Zeng, Jianyang; Gong, Haipeng

2017-09-01

Residue-residue contacts are of great value for protein structure prediction, since contact information, especially from those long-range residue pairs, can significantly reduce the complexity of conformational sampling for protein structure prediction in practice. Despite progresses in the past decade on protein targets with abundant homologous sequences, accurate contact prediction for proteins with limited sequence information is still far from satisfaction. Methodologies for these hard targets still need further improvement. We presented a computational program DeepConPred, which includes a pipeline of two novel deep-learning-based methods (DeepCCon and DeepRCon) as well as a contact refinement step, to improve the prediction of long-range residue contacts from primary sequences. When compared with previous prediction approaches, our framework employed an effective scheme to identify optimal and important features for contact prediction, and was only trained with coevolutionary information derived from a limited number of homologous sequences to ensure robustness and usefulness for hard targets. Independent tests showed that 59.33%/49.97%, 64.39%/54.01% and 70.00%/59.81% of the top L/5, top L/10 and top 5 predictions were correct for CASP10/CASP11 proteins, respectively. In general, our algorithm ranked as one of the best methods for CASP targets. All source data and codes are available at http://166.111.152.91/Downloads.html . hgong@tsinghua.edu.cn or zengjy321@tsinghua.edu.cn. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Prediction of primary somatosensory neuron activity during active tactile exploration

PubMed Central

Campagner, Dario; Evans, Mathew Hywel; Bale, Michael Ross; Erskine, Andrew; Petersen, Rasmus Strange

2016-01-01

Primary sensory neurons form the interface between world and brain. Their function is well-understood during passive stimulation but, under natural behaving conditions, sense organs are under active, motor control. In an attempt to predict primary neuron firing under natural conditions of sensorimotor integration, we recorded from primary mechanosensory neurons of awake, head-fixed mice as they explored a pole with their whiskers, and simultaneously measured both whisker motion and forces with high-speed videography. Using Generalised Linear Models, we found that primary neuron responses were poorly predicted by whisker angle, but well-predicted by rotational forces acting on the whisker: both during touch and free-air whisker motion. These results are in apparent contrast to previous studies of passive stimulation, but could be reconciled by differences in the kinematics-force relationship between active and passive conditions. Thus, simple statistical models can predict rich neural activity elicited by natural, exploratory behaviour involving active movement of sense organs. DOI: http://dx.doi.org/10.7554/eLife.10696.001 PMID:26880559

PREvaIL, an integrative approach for inferring catalytic residues using sequence, structural, and network features in a machine-learning framework.

PubMed

Song, Jiangning; Li, Fuyi; Takemoto, Kazuhiro; Haffari, Gholamreza; Akutsu, Tatsuya; Chou, Kuo-Chen; Webb, Geoffrey I

2018-04-14

Determining the catalytic residues in an enzyme is critical to our understanding the relationship between protein sequence, structure, function, and enhancing our ability to design novel enzymes and their inhibitors. Although many enzymes have been sequenced, and their primary and tertiary structures determined, experimental methods for enzyme functional characterization lag behind. Because experimental methods used for identifying catalytic residues are resource- and labor-intensive, computational approaches have considerable value and are highly desirable for their ability to complement experimental studies in identifying catalytic residues and helping to bridge the sequence-structure-function gap. In this study, we describe a new computational method called PREvaIL for predicting enzyme catalytic residues. This method was developed by leveraging a comprehensive set of informative features extracted from multiple levels, including sequence, structure, and residue-contact network, in a random forest machine-learning framework. Extensive benchmarking experiments on eight different datasets based on 10-fold cross-validation and independent tests, as well as side-by-side performance comparisons with seven modern sequence- and structure-based methods, showed that PREvaIL achieved competitive predictive performance, with an area under the receiver operating characteristic curve and area under the precision-recall curve ranging from 0.896 to 0.973 and from 0.294 to 0.523, respectively. We demonstrated that this method was able to capture useful signals arising from different levels, leveraging such differential but useful types of features and allowing us to significantly improve the performance of catalytic residue prediction. We believe that this new method can be utilized as a valuable tool for both understanding the complex sequence-structure-function relationships of proteins and facilitating the characterization of novel enzymes lacking functional annotations. Copyright © 2018 Elsevier Ltd. All rights reserved.

Relationship between mechanical-property and energy-absorption trends for composite tubes

NASA Technical Reports Server (NTRS)

Farley, Gary L.

1992-01-01

U.S. Army helicopters are designed to dissipate prescribed levels of crash impact kinetic energy without compromising the integrity of the fuselage. Because of the complexity of the energy-absorption process it is imperative for designers of energy-absorbing structures to develop an in-depth understanding of how and why composite structures absorb energy. A description of the crushing modes and mechanisms of energy absorption for composite tubes and beams is presented. Three primary crushing modes of composite structures including transverse shearing, lamina bending, and local buckling are described. The experimental data presented show that fiber and matrix mechanical properties and laminate stiffness and strength mechanical properties cannot reliably predict the energy-absorption response of composite tubes.

Anomalous Putamen Volume in Children with Complex Motor Stereotypies

PubMed Central

Mahone, E. Mark; Crocetti, Deana; Tochen, Laura; Kline, Tina; Mostofsky, Stewart H.; Singer, Harvey S.

2016-01-01

Introduction Complex motor stereotypies in children are repetitive, rhythmic movements that have a predictable pattern and location, seem purposeful, but serve no obvious function, tend to be prolonged, and stop with distraction, e.g., arm/hand flapping, waving. They occur in both “primary” (otherwise typically developing) and secondary conditions. These movements are best defined as habitual behaviors and therefore pathophysiologically hypothesized to reside in premotor to posterior putamen circuits. This study sought to clarify the underlying neurobiological abnormality in children with primary complex motor stereotypies using structural neuroimaging, emphasizing brain regions hypothesized to underlie these atypical behaviors. Methods High-resolution anatomical MRI images, acquired at 3.0T, were analyzed in children ages 8–12 years (20 with primary complex motor stereotypies, 20 typically developing). Frontal lobe sub-regions and striatal structures were delineated for analysis. Results Significant reductions (p=0.045) in the stereotypies group were identified in total putamen volume, but not caudate, nucleus accumbens or frontal sub-regions. There were no group differences in total cerebral volume. Conclusion Findings of a smaller putamen provide preliminary evidence suggesting the potential involvement of the habitual pathway as the underlying anatomical site in primary complex motor stereotypies. PMID:27751663

Predicting effects of climate change on the composition and function of soil microbial communities

NASA Astrophysics Data System (ADS)

Dubinsky, E.; Brodie, E.; Myint, C.; Ackerly, D.; van Nostrand, J.; Bird, J.; Zhou, J.; Andersen, G.; Firestone, M.

2008-12-01

Complex soil microbial communities regulate critical ecosystem processes that will be altered by climate change. A critical step towards predicting the impacts of climate change on terrestrial ecosystems is to determine the primary controllers of soil microbial community composition and function, and subsequently evaluate climate change scenarios that alter these controllers. We surveyed complex soil bacterial and archaeal communities across a range of climatic and edaphic conditions to identify critical controllers of soil microbial community composition in the field and then tested the resulting predictions using a 2-year manipulation of precipitation and temperature using mesocosms of California annual grasslands. Community DNA extracted from field soils sampled from six different ecosystems was assayed for bacterial and archaeal communities using high-density phylogenetic microarrays as well as functional gene arrays. Correlations among the relative abundances of thousands of microbial taxa and edaphic factors such as soil moisture and nutrient content provided a basis for predicting community responses to changing soil conditions. Communities of soil bacteria and archaea were strongly structured by single environmental predictors, particularly variables related to soil water. Bacteria in the Actinomycetales and Bacilli consistently demonstrated a strong negative response to increasing soil moisture, while taxa in a greater variety of lineages responded positively to increasing soil moisture. In the climate change experiment, overall bacterial community structure was impacted significantly by total precipitation but not by plant species. Changes in soil moisture due to decreased rainfall resulted in significant and predictable alterations in community structure. Over 70% of the bacterial taxa in common with the cross-ecosystem study responded as predicted to altered precipitation, with the most conserved response from Actinobacteria. The functional consequences of these predictable changes in community composition were measured with functional arrays that detect genes involved in the metabolism of carbon, nitrogen and other elements. The response of soil microbial communities to altered precipitation can be predicted from the distribution of microbial taxa across moisture gradients.

Predictivity of dog co-culture model, primary human hepatocytes and HepG2 cells for the detection of hepatotoxic drugs in humans

DOE Office of Scientific and Technical Information (OSTI.GOV)

Atienzar, Franck A., E-mail: franck.atienzar@ucb.com; Novik, Eric I.; Gerets, Helga H.

Drug Induced Liver Injury (DILI) is a major cause of attrition during early and late stage drug development. Consequently, there is a need to develop better in vitro primary hepatocyte models from different species for predicting hepatotoxicity in both animals and humans early in drug development. Dog is often chosen as the non-rodent species for toxicology studies. Unfortunately, dog in vitro models allowing long term cultures are not available. The objective of the present manuscript is to describe the development of a co-culture dog model for predicting hepatotoxic drugs in humans and to compare the predictivity of the canine modelmore » along with primary human hepatocytes and HepG2 cells. After rigorous optimization, the dog co-culture model displayed metabolic capacities that were maintained up to 2 weeks which indicates that such model could be also used for long term metabolism studies. Most of the human hepatotoxic drugs were detected with a sensitivity of approximately 80% (n = 40) for the three cellular models. Nevertheless, the specificity was low approximately 40% for the HepG2 cells and hepatocytes compared to 72.7% for the canine model (n = 11). Furthermore, the dog co-culture model showed a higher superiority for the classification of 5 pairs of close structural analogs with different DILI concerns in comparison to both human cellular models. Finally, the reproducibility of the canine system was also satisfactory with a coefficient of correlation of 75.2% (n = 14). Overall, the present manuscript indicates that the dog co-culture model may represent a relevant tool to perform chronic hepatotoxicity and metabolism studies. - Highlights: • Importance of species differences in drug development. • Relevance of dog co-culture model for metabolism and toxicology studies. • Hepatotoxicity: higher predictivity of dog co-culture vs HepG2 and human hepatocytes.« less

Comparison of Aerial and Terrestrial Remote Sensing Techniques for Quantifying Forest Canopy Structural Complexity and Estimating Net Primary Productivity

NASA Astrophysics Data System (ADS)

Fahey, R. T.; Tallant, J.; Gough, C. M.; Hardiman, B. S.; Atkins, J.; Scheuermann, C. M.

2016-12-01

Canopy structure can be an important driver of forest ecosystem functioning - affecting factors such as radiative transfer and light use efficiency, and consequently net primary production (NPP). Both above- (aerial) and below-canopy (terrestrial) remote sensing techniques are used to assess canopy structure and each has advantages and disadvantages. Aerial techniques can cover large geographical areas and provide detailed information on canopy surface and canopy height, but are generally unable to quantitatively assess interior canopy structure. Terrestrial methods provide high resolution information on interior canopy structure and can be cost-effectively repeated, but are limited to very small footprints. Although these methods are often utilized to derive similar metrics (e.g., rugosity, LAI) and to address equivalent ecological questions and relationships (e.g., link between LAI and productivity), rarely are inter-comparisons made between techniques. Our objective is to compare methods for deriving canopy structural complexity (CSC) metrics and to assess the capacity of commonly available aerial remote sensing products (and combinations) to match terrestrially-sensed data. We also assess the potential to combine CSC metrics with image-based analysis to predict plot-based NPP measurements in forests of different ages and different levels of complexity. We use combinations of data from drone-based imagery (RGB, NIR, Red Edge), aerial LiDAR (commonly available medium-density leaf-off), terrestrial scanning LiDAR, portable canopy LiDAR, and a permanent plot network - all collected at the University of Michigan Biological Station. Our results will highlight the potential for deriving functionally meaningful CSC metrics from aerial imagery, LiDAR, and combinations of data sources. We will also present results of modeling focused on predicting plot-level NPP from combinations of image-based vegetation indices (e.g., NDVI, EVI) with LiDAR- or image-derived metrics of CSC (e.g., rugosity, porosity), canopy density, (e.g., LAI), and forest structure (e.g., canopy height). This work builds toward future efforts that will use other data combinations, such as those available at NEON sites, and could be used to inform and test popular ecosystem models (e.g., ED2) incorporating structure.

Testing the importance of family solidarity, community structure, information access, and social capital in predicting nutrition health knowledge and food choices in the Philippines.

PubMed

Moxley, Robert L; Jicha, Karl A; Thompson, Gretchen H

2011-01-01

This study investigates the influence of family solidarity, community structure, information access, social capital, and socioeconomic status on the extent of nutrition and health knowledge (NHK) among primary household meal planners. In turn, we pose the question: does this knowledge influence dietary decision making? Data are taken from a survey determining socioeconomic impacts of vitamin A fortified peanut butter on Philippine households. Questions on the relationships of nutrition to health were selected to construct a knowledge index on which household respondents could be ranked. We then tested hypotheses regarding what types of individual, family-level, and community structural characteristics would predict performance on this index. The results indicate that the strongest predictors of NHK come from sociological theory related to family solidarity and community centrality, in addition to information accessibility and household income. Our findings also indicate that NHK influences dietary choices with regard to the purchase of a vitamin fortified staple food product, which is essential when addressing nutritional deficiency problems in developing countries.

Discovery of the triple asteroidal system 87 Sylvia.

PubMed

Marchis, Franck; Descamps, Pascal; Hestroffer, Daniel; Berthier, Jérome

2005-08-11

After decades of speculation, the existence of binary asteroids has been observationally confirmed, with examples in all minor planet populations. However, no triple systems have hitherto been discovered. Here we report the unambiguous detection of a triple asteroidal system in the main belt, composed of a 280-km primary (87 Sylvia) and two small moonlets orbiting at 710 and 1,360 km. We estimate their orbital elements and use them to refine the shape of the primary body. Both orbits are equatorial, circular and prograde, suggesting a common origin. Using the orbital information to estimate its mass and density, 87 Sylvia appears to have a rubble-pile structure with a porosity of 25-60 per cent. The system was most probably formed through the disruptive collision of a parent asteroid, with the new primary resulting from accretion of fragments, while the moonlets are formed from the debris, as has been predicted previously.

Safety and immunogenicity of a live attenuated Japanese encephalitis chimeric virus vaccine (IMOJEV®) in children.

PubMed

Chokephaibulkit, K; Houillon, G; Feroldi, E; Bouckenooghe, A

2016-01-01

JE-CV (IMOJEV®, Sanofi Pasteur, France) is a live attenuated virus vaccine constructed by inserting coding sequences of the prM and E structural proteins of the Japanese encephalitis SA14-14-2 virus into the genome of yellow fever 17D virus. Primary immunization with JE-CV requires a single dose of the vaccine. This article reviews clinical trials of JE-CV in children aged up to 6 years conducted in countries across South-East Asia. Strong and persistent antibody responses were observed after single primary and booster doses, with 97% of children seroprotected up to five years after booster vaccination. Models of long-term antibody persistence predict a median duration of protection of approximately 30 years after a booster dose. The safety and reactogenicity profiles of JE-CV primary and booster doses are comparable to other widely used childhood vaccines.

Novel determinants of mammalian primary microRNA processing revealed by systematic evaluation of hairpin-containing transcripts and human genetic variation

PubMed Central

Roden, Christine; Gaillard, Jonathan; Kanoria, Shaveta; Rennie, William; Barish, Syndi; Cheng, Jijun; Pan, Wen; Liu, Jun; Cotsapas, Chris; Ding, Ye; Lu, Jun

2017-01-01

Mature microRNAs (miRNAs) are processed from hairpin-containing primary miRNAs (pri-miRNAs). However, rules that distinguish pri-miRNAs from other hairpin-containing transcripts in the genome are incompletely understood. By developing a computational pipeline to systematically evaluate 30 structural and sequence features of mammalian RNA hairpins, we report several new rules that are preferentially utilized in miRNA hairpins and govern efficient pri-miRNA processing. We propose that a hairpin stem length of 36 ± 3 nt is optimal for pri-miRNA processing. We identify two bulge-depleted regions on the miRNA stem, located ∼16–21 nt and ∼28–32 nt from the base of the stem, that are less tolerant of unpaired bases. We further show that the CNNC primary sequence motif selectively enhances the processing of optimal-length hairpins. We predict that a small but significant fraction of human single-nucleotide polymorphisms (SNPs) alter pri-miRNA processing, and confirm several predictions experimentally including a disease-causing mutation. Our study enhances the rules governing mammalian pri-miRNA processing and suggests a diverse impact of human genetic variation on miRNA biogenesis. PMID:28087842

Disgust proneness predicts obsessive-compulsive disorder symptom severity in a clinical sample of youth: Distinctions from negative affect.

PubMed

Olatunji, Bunmi O; Ebesutani, Chad; Kim, Jingu; Riemann, Bradley C; Jacobi, David M

2017-04-15

Although studies have linked disgust proneness to the etiology and maintenance of obsessive-compulsive disorder (OCD) in adults, there remains a paucity of research examining the specificity of this association among youth. The present study employed structural equation modeling to examine the association between disgust proneness, negative affect, and OCD symptom severity in a clinical sample of youth admitted to a residential treatment facility (N =471). Results indicate that disgust proneness and negative affect latent factors independently predicted an OCD symptom severity latent factor. However, when both variables were modeled as predictors simultaneously, latent disgust proneness remained significantly associated with OCD symptom severity, whereas the association between latent negative affect and OCD symptom severity became nonsignificant. Tests of mediation converged in support of disgust proneness as a significant intervening variable between negative affect and OCD symptom severity. Subsequent analysis showed that the path from disgust proneness to OCD symptom severity in the structural model was significantly stronger among those without a primary diagnosis of OCD compared to those with a primary diagnosis of OCD. Given the cross-sectional design, the causal inferences that can be made are limited. The present study is also limited by the exclusive reliance on self-report measures. Disgust proneness may play a uniquely important role in OCD among youth. Copyright © 2017 Elsevier B.V. All rights reserved.

Neural Networks for Nodal Staging of Non–Small Cell Lung Cancer with FDG PET and CT: Importance of Combining Uptake Values and Sizes of Nodes and Primary Tumor

PubMed Central

Vesselle, Hubert J.

2014-01-01

Purpose To evaluate the effect of adding lymph node size to three previously explored artificial neural network (ANN) input parameters (primary tumor maximum standardized uptake value or tumor uptake, tumor size, and nodal uptake at N1, N2, and N3 stations) in the structure of the ANN. The goal was to allow the resulting ANN structure to relate lymph node uptake for size to primary tumor uptake for size in the determination of the status of nodes as human readers do. Materials and Methods This prospective study was approved by the institutional review board, and informed consent was obtained from all participants. The authors developed a back-propagation ANN with one hidden layer and eight processing units. The data set used to train the network included node and tumor size and uptake from 133 patients with non–small cell lung cancer with surgically proved N status. Statistical analysis was performed with the paired t test. Results The ANN correctly predicted the N stage in 99.2% of cases, compared with 72.4% for the expert reader (P < .001). In categorization of N0 and N1 versus N2 and N3 disease, the ANN performed with 99.2% accuracy versus 92.2% for the expert reader (P < .001). Conclusion The ANN is 99.2% accurate in predicting surgical-pathologic nodal status with use of four fluorine 18 fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT)–derived parameters. Malignant and benign inflammatory lymph nodes have overlapping appearances at FDG PET/CT but can be differentiated by ANNs when the crucial input of node size is used. © RSNA, 2013 Online supplemental material is available for this article. PMID:24056403

Coupled Aerodynamic-Thermal-Structural (CATS) Analysis

NASA Technical Reports Server (NTRS)

1995-01-01

Coupled Aerodynamic-Thermal-Structural (CATS) Analysis is a focused effort within the Numerical Propulsion System Simulation (NPSS) program to streamline multidisciplinary analysis of aeropropulsion components and assemblies. Multidisciplinary analysis of axial-flow compressor performance has been selected for the initial focus of this project. CATS will permit more accurate compressor system analysis by enabling users to include thermal and mechanical effects as an integral part of the aerodynamic analysis of the compressor primary flowpath. Thus, critical details, such as the variation of blade tip clearances and the deformation of the flowpath geometry, can be more accurately modeled and included in the aerodynamic analyses. The benefits of this coupled analysis capability are (1) performance and stall line predictions are improved by the inclusion of tip clearances and hot geometries, (2) design alternatives can be readily analyzed, and (3) higher fidelity analysis by researchers in various disciplines is possible. The goals for this project are a 10-percent improvement in stall margin predictions and a 2:1 speed-up in multidisciplinary analysis times. Working cooperatively with Pratt & Whitney, the Lewis CATS team defined the engineering processes and identified the software products necessary for streamlining these processes. The basic approach is to integrate the aerodynamic, thermal, and structural computational analyses by using data management and Non-Uniform Rational B-Splines (NURBS) based data mapping. Five software products have been defined for this task: (1) a primary flowpath data mapper, (2) a two-dimensional data mapper, (3) a database interface, (4) a blade structural pre- and post-processor, and (5) a computational fluid dynamics code for aerothermal analysis of the drum rotor. Thus far (1) a cooperative agreement has been established with Pratt & Whitney, (2) a Primary Flowpath Data Mapper has been prototyped and delivered to General Electric Aircraft Engines and Pratt & Whitney for evaluation, (3) a collaborative effort has been initiated with the National Institute of Standards and Testing to develop a Standard Data Access Interface, and (4) a blade tip clearance capability has been implemented into the Structural Airfoil Blade Engineering Routine (SABER) program. We plan to continue to develop the data mappers and data management tools. As progress is made, additional efforts will be made to apply these tools to propulsion system applications.

Spatial models reveal the microclimatic buffering capacity of old-growth forests

PubMed Central

Frey, Sarah J. K.; Hadley, Adam S.; Johnson, Sherri L.; Schulze, Mark; Jones, Julia A.; Betts, Matthew G.

2016-01-01

Climate change is predicted to cause widespread declines in biodiversity, but these predictions are derived from coarse-resolution climate models applied at global scales. Such models lack the capacity to incorporate microclimate variability, which is critical to biodiversity microrefugia. In forested montane regions, microclimate is thought to be influenced by combined effects of elevation, microtopography, and vegetation, but their relative effects at fine spatial scales are poorly known. We used boosted regression trees to model the spatial distribution of fine-scale, under-canopy air temperatures in mountainous terrain. Spatial models predicted observed independent test data well (r = 0.87). As expected, elevation strongly predicted temperatures, but vegetation and microtopography also exerted critical effects. Old-growth vegetation characteristics, measured using LiDAR (light detection and ranging), appeared to have an insulating effect; maximum spring monthly temperatures decreased by 2.5°C across the observed gradient in old-growth structure. These cooling effects across a gradient in forest structure are of similar magnitude to 50-year forecasts of the Intergovernmental Panel on Climate Change and therefore have the potential to mitigate climate warming at local scales. Management strategies to conserve old-growth characteristics and to curb current rates of primary forest loss could maintain microrefugia, enhancing biodiversity persistence in mountainous systems under climate warming. PMID:27152339

Spatial models reveal the microclimatic buffering capacity of old-growth forests.

PubMed

Frey, Sarah J K; Hadley, Adam S; Johnson, Sherri L; Schulze, Mark; Jones, Julia A; Betts, Matthew G

2016-04-01

Climate change is predicted to cause widespread declines in biodiversity, but these predictions are derived from coarse-resolution climate models applied at global scales. Such models lack the capacity to incorporate microclimate variability, which is critical to biodiversity microrefugia. In forested montane regions, microclimate is thought to be influenced by combined effects of elevation, microtopography, and vegetation, but their relative effects at fine spatial scales are poorly known. We used boosted regression trees to model the spatial distribution of fine-scale, under-canopy air temperatures in mountainous terrain. Spatial models predicted observed independent test data well (r = 0.87). As expected, elevation strongly predicted temperatures, but vegetation and microtopography also exerted critical effects. Old-growth vegetation characteristics, measured using LiDAR (light detection and ranging), appeared to have an insulating effect; maximum spring monthly temperatures decreased by 2.5°C across the observed gradient in old-growth structure. These cooling effects across a gradient in forest structure are of similar magnitude to 50-year forecasts of the Intergovernmental Panel on Climate Change and therefore have the potential to mitigate climate warming at local scales. Management strategies to conserve old-growth characteristics and to curb current rates of primary forest loss could maintain microrefugia, enhancing biodiversity persistence in mountainous systems under climate warming.

Dynamic amphiphile libraries to screen for the "fragrant" delivery of siRNA into HeLa cells and human primary fibroblasts.

PubMed

Gehin, Charlotte; Montenegro, Javier; Bang, Eun-Kyoung; Cajaraville, Ana; Takayama, Shota; Hirose, Hisaaki; Futaki, Shiroh; Matile, Stefan; Riezman, Howard

2013-06-26

Dynamic amphiphiles are amphiphiles with dynamic covalent bridges between their hydrophilic heads and their hydrophobic tails. Their usefulness to activate ion transporters, for odorant release, and for differential sensing of odorants and perfumes, has been demonstrated recently. Here, we report that the same "fragrant" dynamic amphiphiles are ideal to screen for new siRNA transfection agents. The advantages of this approach include rapid access to fairly large libraries of complex structures, and possible transformation en route to assist uptake and minimize toxicity. We report single-component systems that exceed the best commercially available multicomponent cocktails with regard to both efficiency and velocity of EGFP knockdown in HeLa cells. In human primary fibroblasts, siRNA-mediated enzyme knockdown nearly doubled from >30% for Lipofectamine to >60% for our best hit. The identified structures were predictable neither from literature nor from results in fluorogenic vesicles and thus support the importance of conceptually innovative screening approaches.

Computational analysis of human and mouse CREB3L4 Protein

PubMed Central

Velpula, Kiran Kumar; Rehman, Azeem Abdul; Chigurupati, Soumya; Sanam, Ramadevi; Inampudi, Krishna Kishore; Akila, Chandra Sekhar

2012-01-01

CREB3L4 is a member of the CREB/ATF transcription factor family, characterized by their regulation of gene expression through the cAMP-responsive element. Previous studies identified this protein in mice and humans. Whereas CREB3L4 in mice (referred to as Tisp40) is found in the testes and functions in spermatogenesis, human CREB3L4 is primarily detected in the prostate and has been implicated in cancer. We conducted computational analyses to compare the structural homology between murine Tisp40α human CREB3L4. Our results reveal that the primary and secondary structures of the two proteins contain high similarity. Additionally, predicted helical transmembrane structure reveals that the proteins likely have similar structure and function. This study offers preliminary findings that support the translation of mouse Tisp40α findings into human models, based on structural homology. PMID:22829733

Prediction of Dementia in Primary Care Patients

PubMed Central

Jessen, Frank; Wiese, Birgitt; Bickel, Horst; Eiffländer-Gorfer, Sandra; Fuchs, Angela; Kaduszkiewicz, Hanna; Köhler, Mirjam; Luck, Tobias; Mösch, Edelgard; Pentzek, Michael; Riedel-Heller, Steffi G.; Wagner, Michael; Weyerer, Siegfried; Maier, Wolfgang; van den Bussche, Hendrik

2011-01-01

Background Current approaches for AD prediction are based on biomarkers, which are however of restricted availability in primary care. AD prediction tools for primary care are therefore needed. We present a prediction score based on information that can be obtained in the primary care setting. Methodology/Principal Findings We performed a longitudinal cohort study in 3.055 non-demented individuals above 75 years recruited via primary care chart registries (Study on Aging, Cognition and Dementia, AgeCoDe). After the baseline investigation we performed three follow-up investigations at 18 months intervals with incident dementia as the primary outcome. The best set of predictors was extracted from the baseline variables in one randomly selected half of the sample. This set included age, subjective memory impairment, performance on delayed verbal recall and verbal fluency, on the Mini-Mental-State-Examination, and on an instrumental activities of daily living scale. These variables were aggregated to a prediction score, which achieved a prediction accuracy of 0.84 for AD. The score was applied to the second half of the sample (test cohort). Here, the prediction accuracy was 0.79. With a cut-off of at least 80% sensitivity in the first cohort, 79.6% sensitivity, 66.4% specificity, 14.7% positive predictive value (PPV) and 97.8% negative predictive value of (NPV) for AD were achieved in the test cohort. At a cut-off for a high risk population (5% of individuals with the highest risk score in the first cohort) the PPV for AD was 39.1% (52% for any dementia) in the test cohort. Conclusions The prediction score has useful prediction accuracy. It can define individuals (1) sensitively for low cost-low risk interventions, or (2) more specific and with increased PPV for measures of prevention with greater costs or risks. As it is independent of technical aids, it may be used within large scale prevention programs. PMID:21364746

Prediction of dementia in primary care patients.

PubMed

Jessen, Frank; Wiese, Birgitt; Bickel, Horst; Eiffländer-Gorfer, Sandra; Fuchs, Angela; Kaduszkiewicz, Hanna; Köhler, Mirjam; Luck, Tobias; Mösch, Edelgard; Pentzek, Michael; Riedel-Heller, Steffi G; Wagner, Michael; Weyerer, Siegfried; Maier, Wolfgang; van den Bussche, Hendrik

2011-02-18

Current approaches for AD prediction are based on biomarkers, which are however of restricted availability in primary care. AD prediction tools for primary care are therefore needed. We present a prediction score based on information that can be obtained in the primary care setting. We performed a longitudinal cohort study in 3.055 non-demented individuals above 75 years recruited via primary care chart registries (Study on Aging, Cognition and Dementia, AgeCoDe). After the baseline investigation we performed three follow-up investigations at 18 months intervals with incident dementia as the primary outcome. The best set of predictors was extracted from the baseline variables in one randomly selected half of the sample. This set included age, subjective memory impairment, performance on delayed verbal recall and verbal fluency, on the Mini-Mental-State-Examination, and on an instrumental activities of daily living scale. These variables were aggregated to a prediction score, which achieved a prediction accuracy of 0.84 for AD. The score was applied to the second half of the sample (test cohort). Here, the prediction accuracy was 0.79. With a cut-off of at least 80% sensitivity in the first cohort, 79.6% sensitivity, 66.4% specificity, 14.7% positive predictive value (PPV) and 97.8% negative predictive value of (NPV) for AD were achieved in the test cohort. At a cut-off for a high risk population (5% of individuals with the highest risk score in the first cohort) the PPV for AD was 39.1% (52% for any dementia) in the test cohort. The prediction score has useful prediction accuracy. It can define individuals (1) sensitively for low cost-low risk interventions, or (2) more specific and with increased PPV for measures of prevention with greater costs or risks. As it is independent of technical aids, it may be used within large scale prevention programs.

Experimental whole-stream warming alters community size structure.

PubMed

Nelson, Daniel; Benstead, Jonathan P; Huryn, Alexander D; Cross, Wyatt F; Hood, James M; Johnson, Philip W; Junker, James R; Gíslason, Gísli M; Ólafsson, Jón S

2017-07-01

How ecological communities respond to predicted increases in temperature will determine the extent to which Earth's biodiversity and ecosystem functioning can be maintained into a warmer future. Warming is predicted to alter the structure of natural communities, but robust tests of such predictions require appropriate large-scale manipulations of intact, natural habitat that is open to dispersal processes via exchange with regional species pools. Here, we report results of a two-year whole-stream warming experiment that shifted invertebrate assemblage structure via unanticipated mechanisms, while still conforming to community-level metabolic theory. While warming by 3.8 °C decreased invertebrate abundance in the experimental stream by 60% relative to a reference stream, total invertebrate biomass was unchanged. Associated shifts in invertebrate assemblage structure were driven by the arrival of new taxa and a higher proportion of large, warm-adapted species (i.e., snails and predatory dipterans) relative to small-bodied, cold-adapted taxa (e.g., chironomids and oligochaetes). Experimental warming consequently shifted assemblage size spectra in ways that were unexpected, but consistent with thermal optima of taxa in the regional species pool. Higher temperatures increased community-level energy demand, which was presumably satisfied by higher primary production after warming. Our experiment demonstrates how warming reassembles communities within the constraints of energy supply via regional exchange of species that differ in thermal physiological traits. Similar responses will likely mediate impacts of anthropogenic warming on biodiversity and ecosystem function across all ecological communities. © 2016 John Wiley & Sons Ltd.

Life history theory predicts fish assemblage response to hydrologic regimes.

PubMed

Mims, Meryl C; Olden, Julian D

2012-01-01

The hydrologic regime is regarded as the primary driver of freshwater ecosystems, structuring the physical habitat template, providing connectivity, framing biotic interactions, and ultimately selecting for specific life histories of aquatic organisms. In the present study, we tested ecological theory predicting directional relationships between major dimensions of the flow regime and life history composition of fish assemblages in perennial free-flowing rivers throughout the continental United States. Using long-term discharge records and fish trait and survey data for 109 stream locations, we found that 11 out of 18 relationships (61%) tested between the three life history strategies (opportunistic, periodic, and equilibrium) and six hydrologic metrics (two each describing flow variability, predictability, and seasonality) were statistically significant (P < or = 0.05) according to quantile regression. Our results largely support a priori hypotheses of relationships between specific flow indices and relative prevalence of fish life history strategies, with 82% of all significant relationships observed supporting predictions from life history theory. Specifically, we found that (1) opportunistic strategists were positively related to measures of flow variability and negatively related to predictability and seasonality, (2) periodic strategists were positively related to high flow seasonality and negatively related to variability, and (3) the equilibrium strategists were negatively related to flow variability and positively related to predictability. Our study provides important empirical evidence illustrating the value of using life history theory to understand both the patterns and processes by which fish assemblage structure is shaped by adaptation to natural regimes of variability, predictability, and seasonality of critical flow events over broad biogeographic scales.

Model-based analysis of N-glycosylation in Chinese hamster ovary cells

PubMed Central

Krambeck, Frederick J.; Bennun, Sandra V.; Betenbaugh, Michael J.

2017-01-01

The Chinese hamster ovary (CHO) cell is the gold standard for manufacturing of glycosylated recombinant proteins for production of biotherapeutics. The similarity of its glycosylation patterns to the human versions enable the products of this cell line favorable pharmacokinetic properties and lower likelihood of causing immunogenic responses. Because glycan structures are the product of the concerted action of intracellular enzymes, it is difficult to predict a priori how the effects of genetic manipulations alter glycan structures of cells and therapeutic properties. For that reason, quantitative models able to predict glycosylation have emerged as promising tools to deal with the complexity of glycosylation processing. For example, an earlier version of the same model used in this study was used by others to successfully predict changes in enzyme activities that could produce a desired change in glycan structure. In this study we utilize an updated version of this model to provide a comprehensive analysis of N-glycosylation in ten Chinese hamster ovary (CHO) cell lines that include a wild type parent and nine mutants of CHO, through interpretation of previously published mass spectrometry data. The updated N-glycosylation mathematical model contains up to 50,605 glycan structures. Adjusting the enzyme activities in this model to match N-glycan mass spectra produces detailed predictions of the glycosylation process, enzyme activity profiles and complete glycosylation profiles of each of the cell lines. These profiles are consistent with biochemical and genetic data reported previously. The model-based results also predict glycosylation features of the cell lines not previously published, indicating more complex changes in glycosylation enzyme activities than just those resulting directly from gene mutations. The model predicts that the CHO cell lines possess regulatory mechanisms that allow them to adjust glycosylation enzyme activities to mitigate side effects of the primary loss or gain of glycosylation function known to exist in these mutant cell lines. Quantitative models of CHO cell glycosylation have the potential for predicting how glycoengineering manipulations might affect glycoform distributions to improve the therapeutic performance of glycoprotein products. PMID:28486471

NASA Composite Materials Development: Lessons Learned and Future Challenges

NASA Technical Reports Server (NTRS)

Tenney, Darrel R.; Davis, John G., Jr.; Pipes, R. Byron; Johnston, Norman

2009-01-01

Composite materials have emerged as the materials of choice for increasing the performance and reducing the weight and cost of military, general aviation, and transport aircraft and space launch vehicles. Major advancements have been made in the ability to design, fabricate, and analyze large complex aerospace structures. The recent efforts by Boeing and Airbus to incorporate composite into primary load carrying structures of large commercial transports and to certify the airworthiness of these structures is evidence of the significant advancements made in understanding and use of these materials in real world aircraft. NASA has been engaged in research on composites since the late 1960 s and has worked to address many development issues with these materials in an effort to ensure safety, improve performance, and improve affordability of air travel for the public good. This research has ranged from synthesis of advanced resin chemistries to development of mathematical analyses tools to reliably predict the response of built-up structures under combined load conditions. The lessons learned from this research are highlighted with specific examples to illustrate the problems encountered and solutions to these problems. Examples include specific technologies related to environmental effects, processing science, fabrication technologies, nondestructive inspection, damage tolerance, micromechanics, structural mechanics, and residual life prediction. The current state of the technology is reviewed and key issues requiring additional research identified. Also, grand challenges to be solved for expanded use of composites in aero structures are identified.

Finding the target sites of RNA-binding proteins

PubMed Central

Li, Xiao; Kazan, Hilal; Lipshitz, Howard D; Morris, Quaid D

2014-01-01

RNA–protein interactions differ from DNA–protein interactions because of the central role of RNA secondary structure. Some RNA-binding domains (RBDs) recognize their target sites mainly by their shape and geometry and others are sequence-specific but are sensitive to secondary structure context. A number of small- and large-scale experimental approaches have been developed to measure RNAs associated in vitro and in vivo with RNA-binding proteins (RBPs). Generalizing outside of the experimental conditions tested by these assays requires computational motif finding. Often RBP motif finding is done by adapting DNA motif finding methods; but modeling secondary structure context leads to better recovery of RBP-binding preferences. Genome-wide assessment of mRNA secondary structure has recently become possible, but these data must be combined with computational predictions of secondary structure before they add value in predicting in vivo binding. There are two main approaches to incorporating structural information into motif models: supplementing primary sequence motif models with preferred secondary structure contexts (e.g., MEMERIS and RNAcontext) and directly modeling secondary structure recognized by the RBP using stochastic context-free grammars (e.g., CMfinder and RNApromo). The former better reconstruct known binding preferences for sequence-specific RBPs but are not suitable for modeling RBPs that recognize shape and geometry of RNAs. Future work in RBP motif finding should incorporate interactions between multiple RBDs and multiple RBPs in binding to RNA. WIREs RNA 2014, 5:111–130. doi: 10.1002/wrna.1201 PMID:24217996

Tensor Analysis Reveals Distinct Population Structure that Parallels the Different Computational Roles of Areas M1 and V1

PubMed Central

Ryu, Stephen I.; Shenoy, Krishna V.; Cunningham, John P.; Churchland, Mark M.

2016-01-01

Cortical firing rates frequently display elaborate and heterogeneous temporal structure. One often wishes to compute quantitative summaries of such structure—a basic example is the frequency spectrum—and compare with model-based predictions. The advent of large-scale population recordings affords the opportunity to do so in new ways, with the hope of distinguishing between potential explanations for why responses vary with time. We introduce a method that assesses a basic but previously unexplored form of population-level structure: when data contain responses across multiple neurons, conditions, and times, they are naturally expressed as a third-order tensor. We examined tensor structure for multiple datasets from primary visual cortex (V1) and primary motor cortex (M1). All V1 datasets were ‘simplest’ (there were relatively few degrees of freedom) along the neuron mode, while all M1 datasets were simplest along the condition mode. These differences could not be inferred from surface-level response features. Formal considerations suggest why tensor structure might differ across modes. For idealized linear models, structure is simplest across the neuron mode when responses reflect external variables, and simplest across the condition mode when responses reflect population dynamics. This same pattern was present for existing models that seek to explain motor cortex responses. Critically, only dynamical models displayed tensor structure that agreed with the empirical M1 data. These results illustrate that tensor structure is a basic feature of the data. For M1 the tensor structure was compatible with only a subset of existing models. PMID:27814353

Surface structural ion adsorption modeling of competitive binding of oxyanions by metal (hydr)oxides

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hiemstra, T.; Riemsdijk, W.H. van

1999-02-01

An important challenge in surface complexation models (SCM) is to connect the molecular microscopic reality to macroscopic adsorption phenomena. This study elucidates the primary factor controlling the adsorption process by analyzing the adsorption and competition of PO{sub 4}, AsO{sub 4}, and SeO{sub 3}. The authors show that the structure of the surface-complex acting in the dominant electrostatic field can be ascertained as the primary controlling adsorption factor. The surface species of arsenate are identical with those of phosphate and the adsorption behavior is very similar. On the basis of the selenite adsorption, The authors show that the commonly used 1pKmore » models are incapable to incorporate in the adsorption modeling the correct bidentate binding mechanism found by spectroscopy. The use of the bidentate mechanism leads to a proton-oxyanion ratio and corresponding pH dependence that are too large. The inappropriate intrinsic charge attribution to the primary surface groups and the condensation of the inner sphere surface complex to a point charge are responsible for this behavior of commonly used 2pK models. Both key factors are differently defined in the charge distributed multi-site complexation (CD-MUSIC) model and are based in this model on a surface structural approach. The CD-MUSIC model can successfully describe the macroscopic adsorption phenomena using the surface speciation and binding mechanisms as found by spectroscopy. The model is also able to predict the anion competition well. The charge distribution in the interface is in agreement with the observed structure of surface complexes.« less

Research of carbon composite material for nonlinear finite element method

NASA Astrophysics Data System (ADS)

Kim, Jung Ho; Garg, Mohit; Kim, Ji Hoon

2012-04-01

Works on the absorption of collision energy in the structural members are carried out widely with various material and cross-sections. And, with ever increasing safety concerns, they are presently applied in various fields including railroad trains, air crafts and automobiles. In addition to this, problem of lighting structural members became important subject by control of exhaust gas emission, fuel economy and energy efficiency. CFRP(Carbon Fiber Reinforced Plastics) usually is applying the two primary structural members because of different result each design parameter as like stacking thickness, stacking angle, moisture absorption ect. We have to secure the data for applying primary structural members. But it always happens to test design parameters each for securing the data. So, it has much more money and time. We can reduce the money and the time, if can ensure the CFRP material properties each design parameters. In this study, we experiment the coupon test each tension, compression and shear using CFRP prepreg sheet and simulate non-linear analyze at the sources - test result, Caron longitudinal modulus and matrix poisson's ratio using GENOAMQC is specialized at Composite analysis. And then we predict the result that specimen manufacture changing stacking angle and experiment in such a way of test method using GENOA-MCQ.

In silico methods for co-transcriptional RNA secondary structure prediction and for investigating alternative RNA structure expression.

PubMed

Meyer, Irmtraud M

2017-05-01

RNA transcripts are the primary products of active genes in any living organism, including many viruses. Their cellular destiny not only depends on primary sequence signals, but can also be determined by RNA structure. Recent experimental evidence shows that many transcripts can be assigned more than a single functional RNA structure throughout their cellular life and that structure formation happens co-transcriptionally, i.e. as the transcript is synthesised in the cell. Moreover, functional RNA structures are not limited to non-coding transcripts, but can also feature in coding transcripts. The picture that now emerges is that RNA structures constitute an additional layer of information that can be encoded in any RNA transcript (and on top of other layers of information such as protein-context) in order to exert a wide range of functional roles. Moreover, different encoded RNA structures can be expressed at different stages of a transcript's life in order to alter the transcript's behaviour depending on its actual cellular context. Similar to the concept of alternative splicing for protein-coding genes, where a single transcript can yield different proteins depending on cellular context, it is thus appropriate to propose the notion of alternative RNA structure expression for any given transcript. This review introduces several computational strategies that my group developed to detect different aspects of RNA structure expression in vivo. Two aspects are of particular interest to us: (1) RNA secondary structure features that emerge during co-transcriptional folding and (2) functional RNA structure features that are expressed at different times of a transcript's life and potentially mutually exclusive. Copyright © 2017. Published by Elsevier Inc.

Repurposing High-Throughput Image Assays Enables Biological Activity Prediction for Drug Discovery.

PubMed

Simm, Jaak; Klambauer, Günter; Arany, Adam; Steijaert, Marvin; Wegner, Jörg Kurt; Gustin, Emmanuel; Chupakhin, Vladimir; Chong, Yolanda T; Vialard, Jorge; Buijnsters, Peter; Velter, Ingrid; Vapirev, Alexander; Singh, Shantanu; Carpenter, Anne E; Wuyts, Roel; Hochreiter, Sepp; Moreau, Yves; Ceulemans, Hugo

2018-05-17

In both academia and the pharmaceutical industry, large-scale assays for drug discovery are expensive and often impractical, particularly for the increasingly important physiologically relevant model systems that require primary cells, organoids, whole organisms, or expensive or rare reagents. We hypothesized that data from a single high-throughput imaging assay can be repurposed to predict the biological activity of compounds in other assays, even those targeting alternate pathways or biological processes. Indeed, quantitative information extracted from a three-channel microscopy-based screen for glucocorticoid receptor translocation was able to predict assay-specific biological activity in two ongoing drug discovery projects. In these projects, repurposing increased hit rates by 50- to 250-fold over that of the initial project assays while increasing the chemical structure diversity of the hits. Our results suggest that data from high-content screens are a rich source of information that can be used to predict and replace customized biological assays. Copyright © 2018 Elsevier Ltd. All rights reserved.

Predictable internal brain dynamics in EEG and its relation to conscious states

PubMed Central

Yoo, Jaewook; Kwon, Jaerock; Choe, Yoonsuck

2014-01-01

Consciousness is a complex and multi-faceted phenomenon defying scientific explanation. Part of the reason why this is the case is due to its subjective nature. In our previous computational experiments, to avoid such a subjective trap, we took a strategy to investigate objective necessary conditions of consciousness. Our basic hypothesis was that predictive internal dynamics serves as such a condition. This is in line with theories of consciousness that treat retention (memory), protention (anticipation), and primary impression as the tripartite temporal structure of consciousness. To test our hypothesis, we analyzed publicly available sleep and awake electroencephalogram (EEG) data. Our results show that EEG signals from awake or rapid eye movement (REM) sleep states have more predictable dynamics compared to those from slow-wave sleep (SWS). Since awakeness and REM sleep are associated with conscious states and SWS with unconscious or less consciousness states, these results support our hypothesis. The results suggest an intricate relationship among prediction, consciousness, and time, with potential applications to time perception and neurorobotics. PMID:24917813

Design and analysis of composite structures with stress concentrations

NASA Technical Reports Server (NTRS)

Garbo, S. P.

1983-01-01

An overview of an analytic procedure which can be used to provide comprehensive stress and strength analysis of composite structures with stress concentrations is given. The methodology provides designer/analysts with a user-oriented procedure which, within acceptable engineering accuracy, accounts for the effects of a wide range of application design variables. The procedure permits the strength of arbitrary laminate constructions under general bearing/bypass load conditions to be predicted with only unnotched unidirectional strength and stiffness input data required. Included is a brief discussion of the relevancy of this analysis to the design of primary aircraft structure; an overview of the analytic procedure with theory/test correlations; and an example of the use and interaction of this strength analysis relative to the design of high-load transfer bolted composite joints.

Computational Materials: Modeling and Simulation of Nanostructured Materials and Systems

NASA Technical Reports Server (NTRS)

Gates, Thomas S.; Hinkley, Jeffrey A.

2003-01-01

The paper provides details on the structure and implementation of the Computational Materials program at the NASA Langley Research Center. Examples are given that illustrate the suggested approaches to predicting the behavior and influencing the design of nanostructured materials such as high-performance polymers, composites, and nanotube-reinforced polymers. Primary simulation and measurement methods applicable to multi-scale modeling are outlined. Key challenges including verification and validation of models are highlighted and discussed within the context of NASA's broad mission objectives.

Developing predictive models for toxicity of organic chemicals to green algae based on mode of action.

PubMed

Bakire, Serge; Yang, Xinya; Ma, Guangcai; Wei, Xiaoxuan; Yu, Haiying; Chen, Jianrong; Lin, Hongjun

2018-01-01

Organic chemicals in the aquatic ecosystem may inhibit algae growth and subsequently lead to the decline of primary productivity. Growth inhibition tests are required for ecotoxicological assessments for regulatory purposes. In silico study is playing an important role in replacing or reducing animal tests and decreasing experimental expense due to its efficiency. In this work, a series of theoretical models was developed for predicting algal growth inhibition (log EC 50 ) after 72 h exposure to diverse chemicals. In total 348 organic compounds were classified into five modes of toxic action using the Verhaar Scheme. Each model was established by using molecular descriptors that characterize electronic and structural properties. The external validation and leave-one-out cross validation proved the statistical robustness of the derived models. Thus they can be used to predict log EC 50 values of chemicals that lack authorized algal growth inhibition values (72 h). This work systematically studied algal growth inhibition according to toxic modes and the developed model suite covers all five toxic modes. The outcome of this research will promote toxic mechanism analysis and be made applicable to structural diversity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Investigation on the forced response of a radial turbine under aerodynamic excitations

NASA Astrophysics Data System (ADS)

Ma, Chaochen; Huang, Zhi; Qi, Mingxu

2016-04-01

Rotor blades in a radial turbine with nozzle guide vanes typically experience harmonic aerodynamic excitations due to the rotor stator interaction. Dynamic stresses induced by the harmonic excitations can result in high cycle fatigue (HCF) of the blades. A reliable prediction method for forced response issue is essential to avoid the HCF problem. In this work, the forced response mechanisms were investigated based on a fluid structure interaction (FSI) method. Aerodynamic excitations were obtained by three-dimensional unsteady computational fluid dynamics (CFD) simulation with phase shifted periodic boundary conditions. The first two harmonic pressures were determined as the primary components of the excitation and applied to finite element (FE) model to conduct the computational structural dynamics (CSD) simulation. The computed results from the harmonic forced response analysis show good agreement with the predictions of Singh's advanced frequency evaluation (SAFE) diagram. Moreover, the mode superposition method used in FE simulation offers an efficient way to provide quantitative assessments of mode response levels and resonant strength.

Desert mammal populations are limited by introduced predators rather than future climate change

PubMed Central

Wardle, Glenda M.; Dickman, Chris R.

2017-01-01

Climate change is predicted to place up to one in six species at risk of extinction in coming decades, but extinction probability is likely to be influenced further by biotic interactions such as predation. We use structural equation modelling to integrate results from remote camera trapping and long-term (17–22 years) regional-scale (8000 km2) datasets on vegetation and small vertebrates (greater than 38 880 captures) to explore how biotic processes and two key abiotic drivers influence the structure of a diverse assemblage of desert biota in central Australia. We use our models to predict how changes in rainfall and wildfire are likely to influence the cover and productivity of the dominant vegetation and the impacts of predators on their primary rodent prey over a 100-year timeframe. Our results show that, while vegetation cover may decline due to climate change, the strongest negative effect on prey populations in this desert system is top-down suppression from introduced predators. PMID:29291051

Shuttle Experimental Radar for Geological Exploration (SERGE); antenna and integration concept definition study

NASA Technical Reports Server (NTRS)

Kierein, J. W.

1977-01-01

The baseline configuration defined has the SERGE antenna panel array mounted on the OFT-2 pallet sufficiently high in the bay that negligible amounts of radiation from the beam are reflected from orbiter surfaces into the shuttle payload bay. The array is symmetrically mounted to the pallet along the array long dimension with the pallet at the center. It utilizes a graphite epoxy trusswork support structure. The antenna panels are of SEASAT engineering model design and construction. The antenna array has 7 panels and a 7-way naturally tapered coax corporate feed system. The performance of the system is predicted to exceed 33 db gain, have -15 db sidelobes in the E-plane and even lower in the H-plane, and have and E-plane beamwidth less than 2.2 deg, all within performance specification. The primary support structure is predicted to exceed the specified greater than 25 hertz fundamental frequency, although individual panels will have hertz fundamental frequency.

A LES-based Eulerian-Lagrangian approach to predict the dynamics of bubble plumes

NASA Astrophysics Data System (ADS)

Fraga, Bruño; Stoesser, Thorsten; Lai, Chris C. K.; Socolofsky, Scott A.

2016-01-01

An approach for Eulerian-Lagrangian large-eddy simulation of bubble plume dynamics is presented and its performance evaluated. The main numerical novelties consist in defining the gas-liquid coupling based on the bubble size to mesh resolution ratio (Dp/Δx) and the interpolation between Eulerian and Lagrangian frameworks through the use of delta functions. The model's performance is thoroughly validated for a bubble plume in a cubic tank in initially quiescent water using experimental data obtained from high-resolution ADV and PIV measurements. The predicted time-averaged velocities and second-order statistics show good agreement with the measurements, including the reproduction of the anisotropic nature of the plume's turbulence. Further, the predicted Eulerian and Lagrangian velocity fields, second-order turbulence statistics and interfacial gas-liquid forces are quantified and discussed as well as the visualization of the time-averaged primary and secondary flow structure in the tank.

Reconstructing disturbances and their biogeochemical consequences over multiple timescales

USGS Publications Warehouse

McLauchlan, Kendra K.; Higuera, Philip E.; Gavin, Daniel G.; Perakis, Steven S.; Mack, Michelle C.; Alexander, Heather; Battles, John; Biondi, Franco; Buma, Brian; Colombaroli, Daniele; Enders, Sara K.; Engstrom, Daniel R.; Hu, Feng Sheng; Marlon, Jennifer R.; Marshall, John; McGlone, Matt; Morris, Jesse L.; Nave, Lucas E.; Shuman, Bryan; Smithwick, Erica A.H.; Urrego, Dunia H.; Wardle, David A.; Williams, Christopher J.; Williams, Joseph J.

2014-01-01

Ongoing changes in disturbance regimes are predicted to cause acute changes in ecosystem structure and function in the coming decades, but many aspects of these predictions are uncertain. A key challenge is to improve the predictability of postdisturbance biogeochemical trajectories at the ecosystem level. Ecosystem ecologists and paleoecologists have generated complementary data sets about disturbance (type, severity, frequency) and ecosystem response (net primary productivity, nutrient cycling) spanning decadal to millennial timescales. Here, we take the first steps toward a full integration of these data sets by reviewing how disturbances are reconstructed using dendrochronological and sedimentary archives and by summarizing the conceptual frameworks for carbon, nitrogen, and hydrologic responses to disturbances. Key research priorities include further development of paleoecological techniques that reconstruct both disturbances and terrestrial ecosystem dynamics. In addition, mechanistic detail from disturbance experiments, long-term observations, and chronosequences can help increase the understanding of ecosystem resilience.

The habenula encodes negative motivational value associated with primary punishment in humans.

PubMed

Lawson, Rebecca P; Seymour, Ben; Loh, Eleanor; Lutti, Antoine; Dolan, Raymond J; Dayan, Peter; Weiskopf, Nikolaus; Roiser, Jonathan P

2014-08-12

Learning what to approach, and what to avoid, involves assigning value to environmental cues that predict positive and negative events. Studies in animals indicate that the lateral habenula encodes the previously learned negative motivational value of stimuli. However, involvement of the habenula in dynamic trial-by-trial aversive learning has not been assessed, and the functional role of this structure in humans remains poorly characterized, in part, due to its small size. Using high-resolution functional neuroimaging and computational modeling of reinforcement learning, we demonstrate positive habenula responses to the dynamically changing values of cues signaling painful electric shocks, which predict behavioral suppression of responses to those cues across individuals. By contrast, negative habenula responses to monetary reward cue values predict behavioral invigoration. Our findings show that the habenula plays a key role in an online aversive learning system and in generating associated motivated behavior in humans.

Effect of tow alignment on the mechanical performance of 3D woven textile composites

NASA Technical Reports Server (NTRS)

Norman, Timothy L.; Allison, Patti; Baldwin, Jack W.; Gracias, Brian K.; Seesdorf, Dave

1993-01-01

Three-dimensional (3D) woven preforms are currently being considered for use as primary structural components. Lack of technology to properly manufacture, characterize and predict mechanical properties, and predict damage mechanisms leading to failure are problems facing designers of textile composite materials. Two material systems with identical specifications but different manufacturing approaches are investigated. One manufacturing approach resulted in an irregular (nonuniform) preform geometry. The other approach yielded the expected preform geometry (uniform). The objectives are to compare the mechanical properties of the uniform and nonuniform angle interlock 3D weave constructions. The effect of adding layers of laminated tape to the outer surfaces of the textile preform is also examined. Damage mechanisms are investigated and test methods are evaluated.

Line-of-sight structure toward strong lensing galaxy clusters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bayliss, Matthew B.; Johnson, Traci; Sharon, Keren

2014-03-01

We present an analysis of the line-of-sight structure toward a sample of 10 strong lensing cluster cores. Structure is traced by groups that are identified spectroscopically in the redshift range, 0.1 ≤ z ≤ 0.9, and we measure the projected angular and comoving separations between each group and the primary strong lensing clusters in each corresponding line of sight. From these data we measure the distribution of projected angular separations between the primary strong lensing clusters and uncorrelated large-scale structure as traced by groups. We then compare the observed distribution of angular separations for our strong lensing selected lines ofmore » sight against the distribution of groups that is predicted for clusters lying along random lines of sight. There is clear evidence for an excess of structure along the line of sight at small angular separations (θ ≤ 6') along the strong lensing selected lines of sight, indicating that uncorrelated structure is a significant systematic that contributes to producing galaxy clusters with large cross sections for strong lensing. The prevalence of line-of-sight structure is one of several biases in strong lensing clusters that can potentially be folded into cosmological measurements using galaxy cluster samples. These results also have implications for current and future studies—such as the Hubble Space Telescope Frontier Fields—that make use of massive galaxy cluster lenses as precision cosmological telescopes; it is essential that the contribution of line-of-sight structure be carefully accounted for in the strong lens modeling of the cluster lenses.« less

Market mechanisms protect the vulnerable brain.

PubMed

Ramchandran, Kanchna; Nayakankuppam, Dhananjay; Berg, Joyce; Tranel, Daniel; Denburg, Natalie L

2011-07-01

Markets are mechanisms of social exchange, intended to facilitate trading. However, the question remains as to whether markets would help or hurt individuals with decision-makings deficits, as is frequently encountered in the case of cognitive aging. Essential for predicting future gains and losses in monetary and social domains, the striatal nuclei in the brain undergo structural, neurochemical, and functional decline with age. We correlated the efficacy of market mechanisms with dorsal striatal decline in an aging population, by using market based trading in the context of the 2008 U.S. Presidential Elections (primary cycle). Impaired decision-makers displayed higher prediction error (difference between their prediction and actual outcome). Lower in vivo caudate volume was also associated with higher prediction error. Importantly, market-based trading protected older adults with lower caudate volume to a greater extent from their own poorly calibrated predictions. Counterintuitive to the traditional public perception of the market as a fickle, risky proposition where vulnerable traders are most surely to be burned, we suggest that market-based mechanisms protect individuals with brain-based decision-making vulnerabilities. Copyright © 2011 Elsevier Ltd. All rights reserved.

Market mechanisms protect the vulnerable brain

PubMed Central

Ramchandran, Kanchna; Nayakankuppam, Dhananjay; Berg, Joyce; Tranel, Daniel

2011-01-01

Markets are mechanisms of social exchange, intended to facilitate trading. However, the question remains as to whether markets would help or hurt individuals with decision-makings deficits, as is frequently encountered in the case of cognitive aging. Essential for predicting future gains and losses in monetary and social domains, the striatal nuclei in the brain undergo structural, neurochemical, and functional decline with age. We correlated the efficacy of market mechanisms with dorsal striatal decline in an aging population, by using market based trading in the context of the 2008 U.S Presidential Elections (primary cycle). Impaired decision-makers displayed higher prediction error (difference between their prediction and actual outcome). Lower in vivo caudate volume was also associated with higher prediction error. Importantly, market-based trading protected older adults with lower caudate volume to a greater extent from their own poorly calibrated predictions. Counterintuitive to the traditional public perception of the market as a fickle, risky proposition where vulnerable traders are most surely to be burned, we suggest that market-based mechanisms protect individuals with brain-based decision-making vulnerabilities. PMID:21600226

Induced helical backbone conformations of self-organizable dendronized polymers.

PubMed

Rudick, Jonathan G; Percec, Virgil

2008-12-01

Control of function through the primary structure of a molecule presents a significant challenge with valuable rewards for nanoscience. Dendritic building blocks encoded with information that defines their three-dimensional shape (e.g., flat-tapered or conical) and how they associate with each other are referred to as self-assembling dendrons. Self-organizable dendronized polymers possess a flat-tapered or conical self-assembling dendritic side chain on each repeat unit of a linear polymer backbone. When appended to a covalent polymer, the self-assembling dendrons direct a folding process (i.e., intramolecular self-assembly). Alternatively, intermolecular self-assembly of dendrons mediated by noncovalent interactions between apex groups can generate a supramolecular polymer backbone. Self-organization, as we refer to it, is the spontaneous formation of periodic and quasiperiodic arrays from supramolecular elements. Covalent and supramolecular polymers jacketed with self-assembling dendrons self-organize. The arrays are most often comprised of cylindrical or spherical objects. The shape of the object is determined by the primary structure of the dendronized polymer: the structure of the self-assembling dendron and the length of the polymer backbone. It is therefore possible to predictably generate building blocks for single-molecule nanotechnologies or arrays of supramolecules for bottom-up self-assembly. We exploit the self-organization of polymers jacketed with self-assembling dendrons to elucidate how primary structure determines the adopted conformation and fold (i.e., secondary and tertiary structure), how the supramolecules associate (i.e., quaternary structure), and their resulting functions. A combination of experimental techniques is employed to interrogate the primary, secondary, tertiary, and quaternary structure of the self-organizable dendronized polymers. We refer to the process by which we interpolate between the various levels of structural information to rationalize function as retrostructural analysis. Retrostructural analysis validates our hypothesis that the self-assembling dendrons induce a helical backbone conformation in cylindrical self-organizable dendronized polymers. This helical conformation mediates unprecedented functions. Self-organizable dendronized polymers have emerged as powerful building blocks for nanoscience by virtue of their dimensions and ability to self-organize. Discrete cylindrical and spherical structures with well-defined dimensions can be visualized and manipulated individually. More importantly, they provide a robust framework for elucidating functions available only at the nanoscale. This Account will highlight structures and functions generated from self-organizable dendronized polymers that enable integration of the nanoworld with its macroscopic universe. Emphasis is placed on those structures and functions derived from the induced helical backbone conformation of cylindrical self-organizable dendronized polymers.

Decision Trees Predicting Tumor Shrinkage for Head and Neck Cancer: Implications for Adaptive Radiotherapy.

PubMed

Surucu, Murat; Shah, Karan K; Mescioglu, Ibrahim; Roeske, John C; Small, William; Choi, Mehee; Emami, Bahman

2016-02-01

To develop decision trees predicting for tumor volume reduction in patients with head and neck (H&N) cancer using pretreatment clinical and pathological parameters. Forty-eight patients treated with definitive concurrent chemoradiotherapy for squamous cell carcinoma of the nasopharynx, oropharynx, oral cavity, or hypopharynx were retrospectively analyzed. These patients were rescanned at a median dose of 37.8 Gy and replanned to account for anatomical changes. The percentages of gross tumor volume (GTV) change from initial to rescan computed tomography (CT; %GTVΔ) were calculated. Two decision trees were generated to correlate %GTVΔ in primary and nodal volumes with 14 characteristics including age, gender, Karnofsky performance status (KPS), site, human papilloma virus (HPV) status, tumor grade, primary tumor growth pattern (endophytic/exophytic), tumor/nodal/group stages, chemotherapy regimen, and primary, nodal, and total GTV volumes in the initial CT scan. The C4.5 Decision Tree induction algorithm was implemented. The median %GTVΔ for primary, nodal, and total GTVs was 26.8%, 43.0%, and 31.2%, respectively. Type of chemotherapy, age, primary tumor growth pattern, site, KPS, and HPV status were the most predictive parameters for primary %GTVΔ decision tree, whereas for nodal %GTVΔ, KPS, site, age, primary tumor growth pattern, initial primary GTV, and total GTV volumes were predictive. Both decision trees had an accuracy of 88%. There can be significant changes in primary and nodal tumor volumes during the course of H&N chemoradiotherapy. Considering the proposed decision trees, radiation oncologists can select patients predicted to have high %GTVΔ, who would theoretically gain the most benefit from adaptive radiotherapy, in order to better use limited clinical resources. © The Author(s) 2015.

Molecular docking of Glycine max and Medicago truncatula ureases with urea; bioinformatics approaches.

PubMed

Filiz, Ertugrul; Vatansever, Recep; Ozyigit, Ibrahim Ilker

2016-03-01

Urease (EC 3.5.1.5) is a nickel-dependent metalloenzyme catalyzing the hydrolysis of urea into ammonia and carbon dioxide. It is present in many bacteria, fungi, yeasts and plants. Most species, with few exceptions, use nickel metalloenzyme urease to hydrolyze urea, which is one of the commonly used nitrogen fertilizer in plant growth thus its enzymatic hydrolysis possesses vital importance in agricultural practices. Considering the essentiality and importance of urea and urease activity in most plants, this study aimed to comparatively investigate the ureases of two important legume species such as Glycine max (soybean) and Medicago truncatula (barrel medic) from Fabaceae family. With additional plant species, primary and secondary structures of 37 plant ureases were comparatively analyzed using various bioinformatics tools. A structure based phylogeny was constructed using predicted 3D models of G. max and M. truncatula, whose crystallographic structures are not available, along with three additional solved urease structures from Canavalia ensiformis (PDB: 4GY7), Bacillus pasteurii (PDB: 4UBP) and Klebsiella aerogenes (PDB: 1FWJ). In addition, urease structures of these species were docked with urea to analyze the binding affinities, interacting amino acids and atom distances in urease-urea complexes. Furthermore, mutable amino acids which could potentially affect the protein active site, stability and flexibility as well as overall protein stability were analyzed in urease structures of G. max and M. truncatula. Plant ureases demonstrated similar physico-chemical properties with 833-878 amino acid residues and 89.39-90.91 kDa molecular weight with mainly acidic (5.15-6.10 pI) nature. Four protein domain structures such as urease gamma, urease beta, urease alpha and amidohydro 1 characterized the plant ureases. Secondary structure of plant ureases also demonstrated conserved protein architecture, with predominantly α-helix and random coil structures. In structure-based phylogeny, plant ureases from G. max, M. truncatula and C. ensiformis were clearly diverged from bacterial ureases of B. pasteurii and K. aerogenes. Glu, Thr, His and Gly were commonly found as interacting residues in most urease-urea docking complexes while Glu was available in all docked structures. Besides, Ala and Arg residues, which are reported in active-site architecture of plant and bacterial ureases were present in G. max urea-urease complex but not present in others. Moreover, Arg435 and Arg437 in M. truncatula and G. max, respectively were identified as highly mutable hotspot residues residing in amidohydro 1 domain of enzyme. In addition, a number of stabilizing residues were predicted upon mutation of these hotspot residues however Cys and Thr made strong implications since they were also found in codon-aligned sequences as substitutions of hotspot residues. Comparative analyses of primary sequence and secondary structure in 37 different plants demonstrated quite conserved natures of ureases in plant kingdom. Structure-based phylogeny indicated the presence of a possible prokaryote-eukaryote split and implicated the subjection of bacterial ureases to heavy selection in prokaryotic evolution compared to plants. Urea-urease docking complexes suggested that different species could share common interacting residues as well as may have some other uncommon residues at species-dependent way. In silico mutation analyses identified mutable amino acids, which were predicted to reside in catalytic site of enzyme therefore mutagenesis at these sites seemed to have adverse effects on enzyme efficiency or function. This study findings will become valuable preliminary resource for future studies to further understand the primary, secondary and tertiary structures of urease sequences in plants as well as it will provide insights about various binding features of urea-urease complexes.

Organic particulate matter formation at varying relative humidity using surrogate secondary and primary organic compounds with activity corrections in the condensed phase obtained using a method based on the Wilson equation

NASA Astrophysics Data System (ADS)

Chang, E. I.; Pankow, J. F.

2008-01-01

Secondary organic aerosol (SOA) formation in the atmosphere is currently often modeled using a multiple lumped "two-product" (N·2p) approach. The N·2p approach neglects: 1) variation of activity coefficient (ζi) values and mean molecular weight MW in the particulate matter (PM) phase; 2) water uptake into the PM; and 3) the possibility of phase separation in the PM. This study considers these effects by adopting an (N·2p)ζ, MW ,θ approach (θ is a phase index). Specific chemical structures are assigned to 25 lumped SOA compounds and to 15 representative primary organic aerosol (POA) compounds to allow calculation of ζi and MW values. The SOA structure assignments are based on chamber-derived 2p gas/particle partition coefficient values coupled with known effects of structure on vapor pressure pL,i° (atm). To facilitate adoption of the (N·2p)ζ, MW, θ approach in large-scale models, this study also develops CP-Wilson.1, a group-contribution ζi-prediction method that is more computationally economical than the UNIFAC model of Fredenslund et al. (1975). Group parameter values required by CP-Wilson.1 are obtained by fitting ζi values to predictions from UNIFAC. The (N·2p)ζ,MW, θ approach is applied (using CP-Wilson.1) to several real α-pinene/O3 chamber cases for high reacted hydrocarbon levels (ΔHC≍400 to 1000 μg m-3) when relative humidity (RH) ≍50%. Good agreement between the chamber and predicted results is obtained using both the (N·2p)ζ, MW, θ and N·2p approaches, indicating relatively small water effects under these conditions. However, for a hypothetical α-pinene/O3 case at ΔHC=30 μg m-3 and RH=50%, the (N·2p)ζ, MW, θ approach predicts that water uptake will lead to an organic PM level that is more double that predicted by the N·2p approach. Adoption of the (N·2p)ζ, MW, θ approach using reasonable lumped structures for SOA and POA compounds is recommended for ambient PM modeling.

On the Use of 3dB Qualification Margin for Structural Parts on Expendable Launch Vehicles

NASA Technical Reports Server (NTRS)

Yunis, Isam

2007-01-01

The standard random vibration qualification test used for Expendable Launch Vehicle components is Maximum Predicted Environment (MPE) + 6dB for a duration of 4 times the service life of the part. This can be a severe qualification test for these fatigue-sensitive structures. This paper uses flight data from several launch vehicles to establish that reducing the qualification approach to MPE+3dB for the duration of the peak environment (1x life) is valid for fatigue-sensitive structural components. Items that can be classified as fatigue-sensitive are probes, ducts, tubing, bellows, hoses, and any non-functional structure. Non-functional structure may be flight critical or carry fluid, but it cannot include any moving parts or electronics. This reduced qualification approach does not include primary or secondary structure which would be exclusively designed by peak loads, either transient or quasi-static, that are so large and of so few cycles as to make fatigue a moot point.

[Validation of the abbreviated Zarit scales for measuring burden syndrome in the primary caregiver of an elderly patient].

PubMed

Vélez Lopera, Johana María; Berbesí Fernández, Dedsy; Cardona Arango, Doris; Segura Cardona, Angela; Ordóñez Molina, Jaime

2012-07-01

To determine which abbreviated Zarit Scale (ZS) better evaluates the burden of the caregiver of an elderly patient in Medellin, Colombia. Validation study. Primary Care setting in the city of Medellin. Primary caregiver of dependent elderly patients over 65 years old. Sensitivity, specificity, positive predictive value, and negative predictive value for the different abbreviated Zarit scales, plus performing a reliability analysis using the Cronbach Alpha coefficient. The abbreviated scales obtained a sensitivity of between 36.84 and 81.58%, specificity between 95.99 and 100%, positive predictive values between 71.05 and 100%, and negative predictive values of between 91.64 and 97.42%. The scale that better determined caregiver burden in Primary Care was the Bedard Screening scale, with a sensitivity of 81.58%, a specificity of 96.35% and positive and negative predictive values of 75.61% and 97.42%, respectively. Copyright © 2010 Elsevier España, S.L. All rights reserved.

Posttest analysis of a 1:6-scale reinforced concrete reactor containment building

DOE Office of Scientific and Technical Information (OSTI.GOV)

Weatherby, J.R.

In an experiment conducted at Sandia National Laboratories, 1:6-scale model of a reinforced concrete light water reactor containment building was pressurized with nitrogen gas to more than three times its design pressure. The pressurization produced one large tear and several smaller tears in the steel liner plate that functioned as the primary pneumatic seal for the structure. The data collected from the overpressurization test have been used to evaluate and further refine methods of structural analysis that can be used to predict the performance of containment buildings under conditions produced by a severe accident. This report describes posttest finite elementmore » analyses of the 1:6-scale model tests and compares pretest predictions of the structural response to the experimental results. Strain and displacements calculated in axisymmetric finite element analyses of the 1:6-scale model are compared to strains and displacement measured in the experiment. Detailed analyses of the liner plate are also described in the report. The region of the liner surrounding the large tear was analyzed using two different two-dimensional finite elements model. The results from these analyzed indicate that the primary mechanisms that initiated the tear can be captured in a two- dimensional finite element model. Furthermore, the analyses show that studs used to anchor the liner to the concrete wall, played an important role in initiating the liner tear. Three-dimensional finite element analyses of liner plates loaded by studs are also presented. Results from the three-dimensional analyses are compared to results from two-dimensional analyses of the same problems. 12 refs., 56 figs., 1 tab.« less

Crystal structure of the S187F variant of human liver alanine: Aminotransferase associated with primary hyperoxaluria type I and its functional implications

PubMed Central

Oppici, Elisa; Fodor, Krisztian; Paiardini, Alessandro; Williams, Chris; Voltattorni, Carla Borri; Wilmanns, Matthias; Cellini, Barbara

2013-01-01

The substitution of Ser187, a residue located far from the active site of human liver peroxisomal alanine:glyoxylate aminotransferase (AGT), by Phe gives rise to a variant associated with primary hyperoxaluria type I. Unexpectedly, previous studies revealed that the recombinant form of S187F exhibits a remarkable loss of catalytic activity, an increased pyridoxal 5′-phosphate (PLP) binding affinity and a different coenzyme binding mode compared with normal AGT. To shed light on the structural elements responsible for these defects, we solved the crystal structure of the variant to a resolution of 2.9 Å. Although the overall conformation of the variant is similar to that of normal AGT, we noticed: (i) a displacement of the PLP-binding Lys209 and Val185, located on the re and si side of PLP, respectively, and (ii) slight conformational changes of other active site residues, in particular Trp108, the base stacking residue with the pyridine cofactor moiety. This active site perturbation results in a mispositioning of the AGT-pyridoxamine 5′-phosphate (PMP) complex and of the external aldimine, as predicted by molecular modeling studies. Taken together, both predicted and observed movements caused by the S187F mutation are consistent with the following functional properties of the variant: (i) a 300- to 500-fold decrease in both the rate constant of L-alanine half-transamination and the kcat of the overall transamination, (ii) a different PMP binding mode and affinity, and (iii) a different microenvironment of the external aldimine. Proposals for the treatment of patients bearing S187F mutation are discussed on the basis of these results. Proteins 2013; 81:1457–1465. © 2013 Wiley Periodicals, Inc. PMID:23589421

Viking Mars lander 1975 dynamic test model/orbiter developmental test model forced vibration test

NASA Technical Reports Server (NTRS)

Fortenberry, J.; Brownlee, G. R.

1974-01-01

The Viking Mars Lander 1975 dynamic test model and orbiter developmental test model were subjected to forced vibration sine tests. Flight acceptance (FA) and type approval (TA) test levels were applied to the spacecraft structure in a longitudinal test configuration using a 133,440-N (30,000-lb) force shaker. Testing in the two lateral axes (X, Y) was performed at lower levels using four 667-N (150-lb) force shakers. Forced vibration qualification (TA) test levels were successfully imposed on the spacecraft at frequencies down to 10 Hz. Measured responses showed the same character as analytical predictions, and correlation was reasonably good. Because of control system test tolerances, orbiter primary structure generally did not reach the design load limits attained in earlier static testing. A post-test examination of critical orbiter structure disclosed no apparent damage to the structure as a result of the test environment.

New families of human regulatory RNA structures identified by comparative analysis of vertebrate genomes.

PubMed

Parker, Brian J; Moltke, Ida; Roth, Adam; Washietl, Stefan; Wen, Jiayu; Kellis, Manolis; Breaker, Ronald; Pedersen, Jakob Skou

2011-11-01

Regulatory RNA structures are often members of families with multiple paralogous instances across the genome. Family members share functional and structural properties, which allow them to be studied as a whole, facilitating both bioinformatic and experimental characterization. We have developed a comparative method, EvoFam, for genome-wide identification of families of regulatory RNA structures, based on primary sequence and secondary structure similarity. We apply EvoFam to a 41-way genomic vertebrate alignment. Genome-wide, we identify 220 human, high-confidence families outside protein-coding regions comprising 725 individual structures, including 48 families with known structural RNA elements. Known families identified include both noncoding RNAs, e.g., miRNAs and the recently identified MALAT1/MEN β lincRNA family; and cis-regulatory structures, e.g., iron-responsive elements. We also identify tens of new families supported by strong evolutionary evidence and other statistical evidence, such as GO term enrichments. For some of these, detailed analysis has led to the formulation of specific functional hypotheses. Examples include two hypothesized auto-regulatory feedback mechanisms: one involving six long hairpins in the 3'-UTR of MAT2A, a key metabolic gene that produces the primary human methyl donor S-adenosylmethionine; the other involving a tRNA-like structure in the intron of the tRNA maturation gene POP1. We experimentally validate the predicted MAT2A structures. Finally, we identify potential new regulatory networks, including large families of short hairpins enriched in immunity-related genes, e.g., TNF, FOS, and CTLA4, which include known transcript destabilizing elements. Our findings exemplify the diversity of post-transcriptional regulation and provide a resource for further characterization of new regulatory mechanisms and families of noncoding RNAs.

Nutrient Limitation in Northern Gulf of Mexico (NGOM): Phytoplankton Communities and Photosynthesis Respond to Nutrient Pulse

PubMed Central

Zhao, Yan; Quigg, Antonietta

2014-01-01

Although the Mississippi-Atchafalaya River system exports large amounts of nutrients to the Northern Gulf of Mexico annually, nutrient limitation of primary productivity still occurs offshore, acting as one of the major factors controlling local phytoplankton biomass and community structure. Bioassays were conducted for 48 hrs at two stations adjacent to the river plumes in April and August 2012. High Performance of Liquid Chromatography (HPLC) combined with ChemTax and a Fluorescence Induction and Relaxation (FIRe) system were combined to observe changes in the phytoplankton community structure and photosynthetic activity. Major fluorescence parameters (Fo, Fv/Fm) performed well to reveal the stimulating effect of the treatments with nitrogen (N-nitrate) and with nitrogen plus phosphate (+NPi). HPLC/ChemTax results showed that phytoplankton community structure shifted with nitrate addition: we observed an increase in the proportion of diatoms and prasinophytes and a decrease in cyanobacteria and prymnesiophytes. These findings are consistent with predictions from trait-based analysis which predict that phytoplankton groups with high maximum growth rates (μmax) and high nutrient uptake rates (Vmax) readily take advantage of the addition of limiting nutrients. Changes in phytoplankton community structure, if persistent, could trigger changes of particular organic matter fluxes and alter the micro-food web cycles and bottom oxygen consumption. PMID:24551144

Analysis of a Hybrid Wing Body Center Section Test Article

NASA Technical Reports Server (NTRS)

Wu, Hsi-Yung T.; Shaw, Peter; Przekop, Adam

2013-01-01

The hybrid wing body center section test article is an all-composite structure made of crown, floor, keel, bulkhead, and rib panels utilizing the Pultruded Rod Stitched Efficient Unitized Structure (PRSEUS) design concept. The primary goal of this test article is to prove that PRSEUS components are capable of carrying combined loads that are representative of a hybrid wing body pressure cabin design regime. This paper summarizes the analytical approach, analysis results, and failure predictions of the test article. A global finite element model of composite panels, metallic fittings, mechanical fasteners, and the Combined Loads Test System (COLTS) test fixture was used to conduct linear structural strength and stability analyses to validate the specimen under the most critical combination of bending and pressure loading conditions found in the hybrid wing body pressure cabin. Local detail analyses were also performed at locations with high stress concentrations, at Tee-cap noodle interfaces with surrounding laminates, and at fastener locations with high bearing/bypass loads. Failure predictions for different composite and metallic failure modes were made, and nonlinear analyses were also performed to study the structural response of the test article under combined bending and pressure loading. This large-scale specimen test will be conducted at the COLTS facility at the NASA Langley Research Center.

How does vegetation structure influence woodpeckers and secondary cavity nesting birds in African cork oak forest?

NASA Astrophysics Data System (ADS)

Segura, Amalia

2017-08-01

The Great Spotted Woodpecker provides important information about the status of a forest in terms of structure and age. As a primary cavity creator, it provides small-medium size cavities for passerines. However, despite its interest as an ecosystem engineer, studies of this species in Africa are scarce. Here, spatially explicit predictive models were used to investigate how forest structural variables are related to both the Great Spotted Woodpecker and secondary cavity nesting birds in Maamora cork oak forest (northwest Morocco). A positive association between Great Spotted Woodpecker and both dead-tree density and large mature trees (>60 cm dbh) was found. This study area, Maamora, has an old-growth forest structure incorporating a broad range of size and condition of live and dead trees, favouring Great Spotted Woodpecker by providing high availability of foraging and excavating sites. Secondary cavity nesting birds, represented by Great Tit, African Blue Tit, and Hoopoe, were predicted by Great Spotted Woodpecker detections. The findings suggest that the conservation of the Maamora cork oak forest could be key to maintaining these hole-nesting birds. However, this forest is threatened by forestry practises and livestock overgrazing and the challenge is therefore to find sustainable management strategies that ensure conservation while allowing its exploitation.

Factor Structure and Predictive Validity of a Homework Motivation Measure for Use With Middle School Students With Attention-Deficit/Hyperactivity Disorder (ADHD).

PubMed

Langberg, Joshua M; Smith, Zoe R; Dvorsky, Melissa R; Molitor, Stephen J; Bourchtein, Elizaveta; Eddy, Laura D; Eadeh, Hana-May; Oddo, Lauren E

2017-08-31

Many students with attention-deficit/hyperactivity disorder (ADHD) exhibit deficits in motivation to pursue long-term goals. Students with ADHD have particular difficulty with motivation to complete homework-related tasks and often fail to complete assignments. Although these problems are common and may impact academic performance, no homework-motivation measures have been validated for use with students with ADHD. The primary goal of the present study was to evaluate the factor structure and predictive validity of a homework-motivation measure based upon the expectancy-value theory of achievement motivation. A sample of 285 middle school students with ADHD completed the measure, and confirmatory factor analysis was used to evaluate the proposed factor structure and associations with parent and teacher ratings of homework performance. A 2-factor structure emerged, and model fit was excellent. Further, student-rated ability-expectancy beliefs demonstrated significant associations with parent-rated homework problems and performance and with teacher-rated homework performance and percentage of assignments turned in above and beyond ADHD symptoms. Future directions for studying the importance of motivation in students with ADHD are provided, with particular attention to the role that reward sensitivity may play in motivation. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Unravelling the structure of species extinction risk for predictive conservation science.

PubMed

Lee, Tien Ming; Jetz, Walter

2011-05-07

Extinction risk varies across species and space owing to the combined and interactive effects of ecology/life history and geography. For predictive conservation science to be effective, large datasets and integrative models that quantify the relative importance of potential factors and separate rapidly changing from relatively static threat drivers are urgently required. Here, we integrate and map in space the relative and joint effects of key correlates of The International Union for Conservation of Nature-assessed extinction risk for 8700 living birds. Extinction risk varies significantly with species' broad-scale environmental niche, geographical range size, and life-history and ecological traits such as body size, developmental mode, primary diet and foraging height. Even at this broad scale, simple quantifications of past human encroachment across species' ranges emerge as key in predicting extinction risk, supporting the use of land-cover change projections for estimating future threat in an integrative setting. A final joint model explains much of the interspecific variation in extinction risk and provides a remarkably strong prediction of its observed global geography. Our approach unravels the species-level structure underlying geographical gradients in extinction risk and offers a means of disentangling static from changing components of current and future threat. This reconciliation of intrinsic and extrinsic, and of past and future extinction risk factors may offer a critical step towards a more continuous, forward-looking assessment of species' threat status based on geographically explicit environmental change projections, potentially advancing global predictive conservation science.

How preschool executive functioning predicts several aspects of math achievement in Grades 1 and 3: A longitudinal study.

PubMed

Viterbori, Paola; Usai, M Carmen; Traverso, Laura; De Franchis, Valentina

2015-12-01

This longitudinal study analyzes whether selected components of executive function (EF) measured during the preschool period predict several indices of math achievement in primary school. Six EF measures were assessed in a sample of 5-year-old children (N = 175). The math achievement of the same children was then tested in Grades 1 and 3 using both a composite math score and three single indices of written calculation, arithmetical facts, and problem solving. Using previous results obtained from the same sample of children, a confirmatory factor analysis examining the latent EF structure in kindergarten indicated that a two-factor model provided the best fit for the data. In this model, inhibition and working memory (WM)-flexibility were separate dimensions. A full structural equation model was then used to test the hypothesis that math achievement (the composite math score and single math scores) in Grades 1 and 3 could be explained by the two EF components comprising the kindergarten model. The results indicate that the WM-flexibility component measured during the preschool period substantially predicts mathematical achievement, especially in Grade 3. The math composite scores were predicted by the WM-flexibility factor at both grade levels. In Grade 3, both problem solving and arithmetical facts were predicted by the WM-flexibility component. The results empirically support interventions that target EF as an important component of early childhood mathematics education. Copyright © 2015 Elsevier Inc. All rights reserved.

Adoption of Evidence-Based Fall Prevention Practices in Primary Care for Older Adults with a History of Falls.

PubMed

Phelan, Elizabeth A; Aerts, Sally; Dowler, David; Eckstrom, Elizabeth; Casey, Colleen M

2016-01-01

A multifactorial approach to assess and manage modifiable risk factors is recommended for older adults with a history of falls. Limited research suggests that this approach does not routinely occur in clinical practice, but most related studies are based on provider self-report, with the last chart audit of United States practice published over a decade ago. We conducted a retrospective chart review to assess the extent to which patients aged 65+ years with a history of repeated falls or fall-related health-care use received multifactorial risk assessment and interventions. The setting was an academic primary care clinic in the Pacific Northwest. Among the 116 patients meeting our inclusion criteria, 48% had some type of documented assessment. Their mean age was 79 ± 8 years; 68% were female, and 10% were non-white. They averaged six primary care visits over a 12-month period subsequent to their index fall. Frequency of assessment of fall-risk factors varied from 24% (for home safety) to 78% (for vitamin D). An evidence-based intervention was recommended for identified risk factors 73% of the time, on average. Two risk factors were addressed infrequently: medications (21%) and home safety (24%). Use of a structured visit note template independently predicted assessment of fall-risk factors (p = 0.003). Geriatrics specialists were more likely to use a structured note template (p = 0.04) and perform more fall-risk factor assessments (4.6 vs. 3.6, p = 0.007) than general internists. These results suggest opportunities for improving multifactorial fall-risk assessment and management of older adults at high fall risk in primary care. A structured visit note template facilitates assessment. Given that high-risk medications have been found to be independent risk factors for falls, increasing attention to medications should become a key focus of both public health educational efforts and fall prevention in primary care practice.

Adoption of Evidence-Based Fall Prevention Practices in Primary Care for Older Adults with a History of Falls

PubMed Central

Phelan, Elizabeth A.; Aerts, Sally; Dowler, David; Eckstrom, Elizabeth; Casey, Colleen M.

2016-01-01

A multifactorial approach to assess and manage modifiable risk factors is recommended for older adults with a history of falls. Limited research suggests that this approach does not routinely occur in clinical practice, but most related studies are based on provider self-report, with the last chart audit of United States practice published over a decade ago. We conducted a retrospective chart review to assess the extent to which patients aged 65+ years with a history of repeated falls or fall-related health-care use received multifactorial risk assessment and interventions. The setting was an academic primary care clinic in the Pacific Northwest. Among the 116 patients meeting our inclusion criteria, 48% had some type of documented assessment. Their mean age was 79 ± 8 years; 68% were female, and 10% were non-white. They averaged six primary care visits over a 12-month period subsequent to their index fall. Frequency of assessment of fall-risk factors varied from 24% (for home safety) to 78% (for vitamin D). An evidence-based intervention was recommended for identified risk factors 73% of the time, on average. Two risk factors were addressed infrequently: medications (21%) and home safety (24%). Use of a structured visit note template independently predicted assessment of fall-risk factors (p = 0.003). Geriatrics specialists were more likely to use a structured note template (p = 0.04) and perform more fall-risk factor assessments (4.6 vs. 3.6, p = 0.007) than general internists. These results suggest opportunities for improving multifactorial fall-risk assessment and management of older adults at high fall risk in primary care. A structured visit note template facilitates assessment. Given that high-risk medications have been found to be independent risk factors for falls, increasing attention to medications should become a key focus of both public health educational efforts and fall prevention in primary care practice. PMID:27660753

Improved Helicopter Rotor Performance Prediction through Loose and Tight CFD/CSD Coupling

NASA Astrophysics Data System (ADS)

Ickes, Jacob C.

Helicopters and other Vertical Take-Off or Landing (VTOL) vehicles exhibit an interesting combination of structural dynamic and aerodynamic phenomena which together drive the rotor performance. The combination of factors involved make simulating the rotor a challenging and multidisciplinary effort, and one which is still an active area of interest in the industry because of the money and time it could save during design. Modern tools allow the prediction of rotorcraft physics from first principles. Analysis of the rotor system with this level of accuracy provides the understanding necessary to improve its performance. There has historically been a divide between the comprehensive codes which perform aeroelastic rotor simulations using simplified aerodynamic models, and the very computationally intensive Navier-Stokes Computational Fluid Dynamics (CFD) solvers. As computer resources become more available, efforts have been made to replace the simplified aerodynamics of the comprehensive codes with the more accurate results from a CFD code. The objective of this work is to perform aeroelastic rotorcraft analysis using first-principles simulations for both fluids and structural predictions using tools available at the University of Toledo. Two separate codes are coupled together in both loose coupling (data exchange on a periodic interval) and tight coupling (data exchange each time step) schemes. To allow the coupling to be carried out in a reliable and efficient way, a Fluid-Structure Interaction code was developed which automatically performs primary functions of loose and tight coupling procedures. Flow phenomena such as transonics, dynamic stall, locally reversed flow on a blade, and Blade-Vortex Interaction (BVI) were simulated in this work. Results of the analysis show aerodynamic load improvement due to the inclusion of the CFD-based airloads in the structural dynamics analysis of the Computational Structural Dynamics (CSD) code. Improvements came in the form of improved peak/trough magnitude prediction, better phase prediction of these locations, and a predicted signal with a frequency content more like the flight test data than the CSD code acting alone. Additionally, a tight coupling analysis was performed as a demonstration of the capability and unique aspects of such an analysis. This work shows that away from the center of the flight envelope, the aerodynamic modeling of the CSD code can be replaced with a more accurate set of predictions from a CFD code with an improvement in the aerodynamic results. The better predictions come at substantially increased computational costs between 1,000 and 10,000 processor-hours.

Influence of clinostat rotation on fertilized amphibian egg pattern specification

NASA Technical Reports Server (NTRS)

Neff, A. W.; Smith, R. C.; Malacinski, G. M.; Chung, H.-M.

1984-01-01

Pattern specification in fertile Xenopus eggs rotated on horizontal clinostats was monitored with respect to primary embryonic axis formation, subsequent morphogenesis, and compartmentalization of the cytoplasm. At the speeds of 1 to 24 rpm (which are believed to simulate microgravity) a large percentage of eggs developed normal axial structures. Eggs clinostated at 12 rpm showed a randomization of dorsal/ventral polarity. The cytoplasmic compartments showed some clinostat effects but no abnormal mixing, disruption or dislocation of compartments. It is predicted that Xenopus eggs fertilized and allowed to develop in space will retain normal cytoplasmic density compartments, establish primary axes and undergo normal morphogenesis in space. Their dorsal/ventral polarity may not, however, be determined by the sperm entrance site (as is the case for 1 g eggs).

Added value of delayed computed tomography angiography in primary intracranial hemorrhage and hematoma size for predicting spot sign.

PubMed

Wu, Te Chang; Chen, Tai Yuan; Shiue, Yow Ling; Chen, Jeon Hor; Hsieh, Tsyh-Jyi; Ko, Ching Chung; Lin, Ching Po

2018-04-01

Background The computed tomography angiography (CTA) spot sign represents active contrast extravasation within acute primary intracerebral hemorrhage (ICH) and is an independent predictor of hematoma expansion (HE) and poor clinical outcomes. The spot sign could be detected on first-pass CTA (fpCTA) or delayed CTA (dCTA). Purpose To investigate the additional benefits of dCTA spot sign in primary ICH and hematoma size for predicting spot sign. Material and Methods This is a retrospective study of 100 patients who underwent non-contrast CT (NCCT) and CTA within 24 h of onset of primary ICH. The presence of spot sign on fpCTA or dCTA, and hematoma size on NCCT were recorded. The spot sign on fpCTA or dCTA for predicting significant HE, in-hospital mortality, and poor clinical outcomes (mRS ≥ 4) are calculated. The hematoma size for prediction of CTA spot sign was also analyzed. Results Only the spot sign on dCTA could predict high risk of significant HE and poor clinical outcomes as on fpCTA ( P < 0.05). With dCTA, there is increased sensitivity and negative predictive value (NPV) for predicting significant HE, in-hospital mortality, and poor clinical outcomes. The XY value (product of the two maximum perpendicular axial dimensions) is the best predictor (area under the curve [AUC] = 0.82) for predicting spot sign on fpCTA or dCTA in the absence of intraventricular and subarachnoid hemorrhage. Conclusion This study clarifies that dCTA imaging could improve predictive performance of CTA in primary ICH. Furthermore, the XY value is the best predictor for CTA spot sign.

Analytical Approach for Estimating Preliminary Mass of ARES I Crew Launch Vehicle Upper Stage Structural Components

NASA Technical Reports Server (NTRS)

Aggarwal, Pravin

2007-01-01

In January 2004, President Bush gave the National Aeronautics and Space Administration (NASA) a vision for Space Exploration by setting our sight on a bold new path to go back to the Moon, then to Mars and beyond. In response to this vision, NASA started the Constellation Program, which is a new exploration launch vehicle program. The primary mission for the Constellation Program is to carry out a series of human expeditions ranging from Low Earth Orbit to the surface of Mars and beyond for the purposes of conducting human exploration of space, as specified by the Vision for Space Exploration (VSE). The intent is that the information and technology developed by this program will provide the foundation for broader exploration activities as our operational experience grows. The ARES I Crew Launch Vehicle (CLV) has been designated as the launch vehicle that will be developed as a "first step" to facilitate the aforementioned human expeditions. The CLV Project is broken into four major elements: First Stage, Upper Stage Engine, Upper Stage (US), and the Crew Exploration Vehicle (CEV). NASA's Marshall Space Flight Center (MSFC) is responsible for the design of the CLV and has the prime responsibility to design the upper stage of the vehicle. The US is the second propulsive stage of the CLV and provides CEV insertion into low Earth orbit (LEO) after separation from the First Stage of the Crew Launch Vehicle. The fully integrated Upper Stage is a mix of modified existing heritage hardware (J-2X Engine) and new development (primary structure, subsystems, and avionics). The Upper Stage assembly is a structurally stabilized cylindrical structure, which is powered by a single J-2X engine which is developed as a separate Element of the CLV. The primary structure includes the load bearing liquid hydrogen (LH2) and liquid oxygen (LOX) propellant tanks, a Forward Skirt, the Intertank structure, the Aft Skirt and the Thrust Structure. A Systems Tunnel, which carries fluid and electrical power functions to other Elements of the CLV, is included as secondary structure. The MSFC has an overall responsibility for the integrated US element as well as structural design an thermal control of the fuel tanks, intertank, interstage, avionics, main propulsion system, Reaction Control System (RCS) for both the Upper Stage and the First Stage. MSFC's Spacecraft and Vehicle Department, Structural and Analysis Design Division is developing a set of predicted mass of these elements. This paper details the methodology, criterion and tools used for the preliminary mass predictions of the upper stage structural assembly components. In general, weight of the cylindrical barrel sections are estimated using the commercial code Hypersizer, whereas, weight of the domes are developed using classical solutions. HyperSizer is software that performs automated structural analysis and sizing optimization based on aerospace methods for strength, stability, and stiffness. Analysis methods range from closed form, traditional hand calculations repeated every day in industry to more advanced panel buckling algorithms. Margin-of-safety reporting for every potential failure provides the engineer with a powerful insight into the structural problem. Optimization capabilities include finding minimum weight panel or beam concepts, material selections, cross sectional dimensions, thicknesses, and lay-ups from a library of 40 different stiffened and sandwich designs and a database of composite, metallic, honeycomb, and foam materials. Multiple different concepts (orthogrid, isogrid, and skin stiffener) were run for multiple loading combinations of ascent design load with and with out tank pressure as well as proof pressure condition. Subsequently, selected optimized concept obtained from Hypersizer runs was translated into a computer aid design (CAD) model to account for the wall thickness tolerance, weld land etc for developing the most probable weight of the components. The flow diram summarizes the analysis steps used in developing these predicted mass.

HIV Education and Welfare Services in Primary Care: An Empirical Model of Integration in Brazil’s Unified Health System

PubMed Central

Rahman, Rahbel; Pinto, Rogério M.; Wall, Melanie M.

2017-01-01

Integration of health education and welfare services in primary care systems is a key strategy to solve the multiple determinants of chronic diseases, such as Human Immunodeficiency Virus Infection and Acquired Immune Deficiency Syndrome (HIV/AIDS). However, there is a scarcity of conceptual models from which to build integration strategies. We provide a model based on cross-sectional data from 168 Community Health Agents, 62 nurses, and 32 physicians in two municipalities in Brazil’s Unified Health System (UHS). The outcome, service integration, comprised HIV education, community activities (e.g., health walks and workshops), and documentation services (e.g., obtainment of working papers and birth certificates). Predictors included individual factors (provider confidence, knowledge/skills, perseverance, efficacy); job characteristics (interprofessional collaboration, work-autonomy, decision-making autonomy, skill variety); and organizational factors (work conditions and work resources). Structural equation modeling was used to identify factors associated with service integration. Knowledge and skills, skill variety, confidence, and perseverance predicted greater integration of HIV education alongside community activities and documentation services. Job characteristics and organizational factors did not predict integration. Our study offers an explanatory model that can be adapted to examine other variables that may influence integration of different services in global primary healthcare systems. Findings suggest that practitioner trainings to improve integration should focus on cognitive constructs—confidence, perseverance, knowledge, and skills. PMID:28335444

HIV Education and Welfare Services in Primary Care: An Empirical Model of Integration in Brazil's Unified Health System.

PubMed

Rahman, Rahbel; Pinto, Rogério M; Wall, Melanie M

2017-03-14

Integration of health education and welfare services in primary care systems is a key strategy to solve the multiple determinants of chronic diseases, such as Human Immunodeficiency Virus Infection and Acquired Immune Deficiency Syndrome (HIV/AIDS). However, there is a scarcity of conceptual models from which to build integration strategies. We provide a model based on cross-sectional data from 168 Community Health Agents, 62 nurses, and 32 physicians in two municipalities in Brazil's Unified Health System (UHS). The outcome, service integration, comprised HIV education, community activities (e.g., health walks and workshops), and documentation services (e.g., obtainment of working papers and birth certificates). Predictors included individual factors (provider confidence, knowledge/skills, perseverance, efficacy); job characteristics (interprofessional collaboration, work-autonomy, decision-making autonomy, skill variety); and organizational factors (work conditions and work resources). Structural equation modeling was used to identify factors associated with service integration. Knowledge and skills, skill variety, confidence, and perseverance predicted greater integration of HIV education alongside community activities and documentation services. Job characteristics and organizational factors did not predict integration. Our study offers an explanatory model that can be adapted to examine other variables that may influence integration of different services in global primary healthcare systems. Findings suggest that practitioner trainings to improve integration should focus on cognitive constructs-confidence, perseverance, knowledge, and skills.

Geological Structures in the WaIls of Vestan Craters

NASA Technical Reports Server (NTRS)

Mittlefehldt, David; Nathues, A.; Beck, A. W.; Hoffmann, M.; Schaefer, M.; Williams, D. A.

2014-01-01

A compelling case can be made that Vesta is the parent asteroid for the howardite, eucrite and diogenite (HED) meteorites [1], although this interpretation has been questioned [2]. Generalized models for the structure of the crust of Vesta have been developed based on petrologic studies of basaltic eucrites, cumulate eucrites and diogenites. These models use inferred cooling rates for different types of HEDs and compositional variations within the clan to posit that the lower crust is dominantly diogenitic in character, cumulate eucrites occur deep in the upper crust, and basaltic eucrites dominate the higher levels of the upper crust [3-5]. These models lack fine-scale resolution and thus do not allow for detailed predictions of crustal structure. Geophysical models predict dike and sill intrusions ought to be present, but their widths may be quite small [6]. The northern hemisphere of Vesta is heavily cratered, and the southern hemisphere is dominated by two 400-500 km diameter basins that excavated deep into the crust [7-8]. Physical modeling of regolith formation on 300 km diameter asteroids predicts that debris layers would reach a few km in thickness, while on asteroids of Vesta's diameter regolith thicknesses would be less [9]. This agrees well with the estimated =1 km thickness of local debris excavated by a 45 km diameter vestan crater [10]. Large craters and basins may have punched through the regolith/megaregolith and exposed primary vestan crustal structures. We will use Dawn Framing Camera (FC) [11] images and color ratio maps from the High Altitude and Low Altitude Mapping Orbits (HAMO, 65 m/pixel; LAMO, 20 m/pixel) to evaluate structures exposed on the walls of craters: two examples are discussed here.

Auroral Current and Electrodynamics Structure (ACES) Observations of Ionospheric Feedback in the Alfven Resonator

NASA Technical Reports Server (NTRS)

Cohen, Ian J.; Lessard, Marc; Lund, Eric J.; Bounds, Scott R.; Kletzing, Craig; Kaeppler, Stephen R.; Sigsbee, Kristine M.; Streltsov, Anatoly V.; Labelle, James W.; Dombrowski, Micah P.;

Conservation of Matrix Attachment Region-Binding Filament-Like Protein 1 among Higher Plants1

PubMed Central

Harder, Patricia A.; Silverstein, Rebecca A.; Meier, Iris

2000-01-01

The interaction of chromatin with the nuclear matrix via matrix attachment regions (MARs) on the DNA is considered to be of fundamental importance for higher-order chromatin organization and the regulation of gene expression. We have previously isolated a novel nuclear matrix-localized protein (MFP1) from tomato (Lycopersicon esculentum) that preferentially binds to MAR DNA. Tomato MFP1 has a predicted filament-protein-like structure and is associated with the nuclear envelope via an N-terminal targeting domain. Based on the antigenic relationship, we report here that MFP1 is conserved in a large number of dicot and monocot species. Several cDNAs were cloned from tobacco (Nicotiana tabacum) and shown to correspond to two tobacco MFP1 genes. Comparison of the primary and predicted secondary structures of MFP1 from tomato, tobacco, and Arabidopsis indicates a high degree of conservation of the N-terminal targeting domain, the overall putative coiled-coil structure of the protein, and the C-terminal DNA-binding domain. In addition, we show that tobacco MFP1 is regulated in an organ-specific and developmental fashion, and that this regulation occurs at the level of transcription or RNA stability. PMID:10631266

Reuse at the Software Productivity Consortium

NASA Technical Reports Server (NTRS)

Weiss, David M.

1989-01-01

The Software Productivity Consortium is sponsored by 14 aerospace companies as a developer of software engineering methods and tools. Software reuse and prototyping are currently the major emphasis areas. The Methodology and Measurement Project in the Software Technology Exploration Division has developed some concepts for reuse which they intend to develop into a synthesis process. They have identified two approaches to software reuse: opportunistic and systematic. The assumptions underlying the systematic approach, phrased as hypotheses, are the following: the redevelopment hypothesis, i.e., software developers solve the same problems repeatedly; the oracle hypothesis, i.e., developers are able to predict variations from one redevelopment to others; and the organizational hypothesis, i.e., software must be organized according to behavior and structure to take advantage of the predictions that the developers make. The conceptual basis for reuse includes: program families, information hiding, abstract interfaces, uses and information hiding hierarchies, and process structure. The primary reusable software characteristics are black-box descriptions, structural descriptions, and composition and decomposition based on program families. Automated support can be provided for systematic reuse, and the Consortium is developing a prototype reuse library and guidebook. The software synthesis process that the Consortium is aiming toward includes modeling, refinement, prototyping, reuse, assessment, and new construction.

Ruling out coronary artery disease in primary care: development and validation of a simple prediction rule.

PubMed

Bösner, Stefan; Haasenritter, Jörg; Becker, Annette; Karatolios, Konstantinos; Vaucher, Paul; Gencer, Baris; Herzig, Lilli; Heinzel-Gutenbrunner, Monika; Schaefer, Juergen R; Abu Hani, Maren; Keller, Heidi; Sönnichsen, Andreas C; Baum, Erika; Donner-Banzhoff, Norbert

2010-09-07

Chest pain can be caused by various conditions, with life-threatening cardiac disease being of greatest concern. Prediction scores to rule out coronary artery disease have been developed for use in emergency settings. We developed and validated a simple prediction rule for use in primary care. We conducted a cross-sectional diagnostic study in 74 primary care practices in Germany. Primary care physicians recruited all consecutive patients who presented with chest pain (n = 1249) and recorded symptoms and findings for each patient (derivation cohort). An independent expert panel reviewed follow-up data obtained at six weeks and six months on symptoms, investigations, hospital admissions and medications to determine the presence or absence of coronary artery disease. Adjusted odds ratios of relevant variables were used to develop a prediction rule. We calculated measures of diagnostic accuracy for different cut-off values for the prediction scores using data derived from another prospective primary care study (validation cohort). The prediction rule contained five determinants (age/sex, known vascular disease, patient assumes pain is of cardiac origin, pain is worse during exercise, and pain is not reproducible by palpation), with the score ranging from 0 to 5 points. The area under the curve (receiver operating characteristic curve) was 0.87 (95% confidence interval [CI] 0.83-0.91) for the derivation cohort and 0.90 (95% CI 0.87-0.93) for the validation cohort. The best overall discrimination was with a cut-off value of 3 (positive result 3-5 points; negative result

Predicting targets of compounds against neurological diseases using cheminformatic methodology

NASA Astrophysics Data System (ADS)

Nikolic, Katarina; Mavridis, Lazaros; Bautista-Aguilera, Oscar M.; Marco-Contelles, José; Stark, Holger; do Carmo Carreiras, Maria; Rossi, Ilaria; Massarelli, Paola; Agbaba, Danica; Ramsay, Rona R.; Mitchell, John B. O.

2015-02-01

Recently developed multi-targeted ligands are novel drug candidates able to interact with monoamine oxidase A and B; acetylcholinesterase and butyrylcholinesterase; or with histamine N-methyltransferase and histamine H3-receptor (H3R). These proteins are drug targets in the treatment of depression, Alzheimer's disease, obsessive disorders, and Parkinson's disease. A probabilistic method, the Parzen-Rosenblatt window approach, was used to build a "predictor" model using data collected from the ChEMBL database. The model can be used to predict both the primary pharmaceutical target and off-targets of a compound based on its structure. Molecular structures were represented based on the circular fingerprint methodology. The same approach was used to build a "predictor" model from the DrugBank dataset to determine the main pharmacological groups of the compound. The study of off-target interactions is now recognised as crucial to the understanding of both drug action and toxicology. Primary pharmaceutical targets and off-targets for the novel multi-target ligands were examined by use of the developed cheminformatic method. Several multi-target ligands were selected for further study, as compounds with possible additional beneficial pharmacological activities. The cheminformatic targets identifications were in agreement with four 3D-QSAR (H3R/D1R/D2R/5-HT2aR) models and by in vitro assays for serotonin 5-HT1a and 5-HT2a receptor binding of the most promising ligand ( 71/MBA-VEG8).

Canopy structural complexity as a continental predictor of primary production: Using NEON to transform understanding of forest structure-function

NASA Astrophysics Data System (ADS)

Atkins, J. W.; Fahey, R. T.; Gough, C. M.; Hardiman, B. S.

2016-12-01

Ecosystem structure-function relationships represent a long-standing research area for ecosystem science. Relationships between canopy structural complexity (CSC) and net primary productivity (NPP), have been characterized for a limited number of sites, yet whether these relationships are conserved across eco-climatic boundaries remains unknown. We hypothesize an underlying mechanistic basis for global NPP-CSC linkages to include improved resource-use efficiency as CSC increases, examined here by correlating CSC with measures of light-use efficiency and nitrogen-use efficiency. Here we present a broad, continental scale analysis of CSC-NPP linkages. We are using multiple NEON sites coupled with other sites across a diverse array of temperate forest types spanning six eco-climatic domains of the continental United States to examine CSC-NPP relationships. Portable canopy LiDAR (PCL) data were used to calculate a suite of CSC metrics at the plot-level within each site. Ongoing work compares CSC to co-located measurements of wood net primary production estimated from the incremental change in woody biomass calculated using tree allometries. Results to date show CSC is highly variable across forest sites and may provide additional explanatory power for predicting NPP that is independent of other commonly used forest structural attributes such as leaf area index. CSC metrics such as rugosity vary widely across sites—ranging from high values (30 - 35) in complex canopies such as the Great Smoky Mountains to low values in open, savanna systems like North-Central Florida (< 0.5 - 2). NPP, and light- and nitrogen-use calculations are underway and will be paired with site-level CSC, with the expectation that CSC, resource-use efficiency, and NPP are positively correlated. Advancing understanding of how and why CSC affects forest NPP across a broad spatial dimension could transform mechanistic understanding of ecosystem structure-carbon cycling relationships, and greatly improve carbon cycling models and remote sensing applications, while providing a crucial linkage between the two.

PredPPCrys: accurate prediction of sequence cloning, protein production, purification and crystallization propensity from protein sequences using multi-step heterogeneous feature fusion and selection.

PubMed

Wang, Huilin; Wang, Mingjun; Tan, Hao; Li, Yuan; Zhang, Ziding; Song, Jiangning

2014-01-01

X-ray crystallography is the primary approach to solve the three-dimensional structure of a protein. However, a major bottleneck of this method is the failure of multi-step experimental procedures to yield diffraction-quality crystals, including sequence cloning, protein material production, purification, crystallization and ultimately, structural determination. Accordingly, prediction of the propensity of a protein to successfully undergo these experimental procedures based on the protein sequence may help narrow down laborious experimental efforts and facilitate target selection. A number of bioinformatics methods based on protein sequence information have been developed for this purpose. However, our knowledge on the important determinants of propensity for a protein sequence to produce high diffraction-quality crystals remains largely incomplete. In practice, most of the existing methods display poorer performance when evaluated on larger and updated datasets. To address this problem, we constructed an up-to-date dataset as the benchmark, and subsequently developed a new approach termed 'PredPPCrys' using the support vector machine (SVM). Using a comprehensive set of multifaceted sequence-derived features in combination with a novel multi-step feature selection strategy, we identified and characterized the relative importance and contribution of each feature type to the prediction performance of five individual experimental steps required for successful crystallization. The resulting optimal candidate features were used as inputs to build the first-level SVM predictor (PredPPCrys I). Next, prediction outputs of PredPPCrys I were used as the input to build second-level SVM classifiers (PredPPCrys II), which led to significantly enhanced prediction performance. Benchmarking experiments indicated that our PredPPCrys method outperforms most existing procedures on both up-to-date and previous datasets. In addition, the predicted crystallization targets of currently non-crystallizable proteins were provided as compendium data, which are anticipated to facilitate target selection and design for the worldwide structural genomics consortium. PredPPCrys is freely available at http://www.structbioinfor.org/PredPPCrys.

Convergence of an iterative procedure for large-scale static analysis of structural components

NASA Technical Reports Server (NTRS)

Austin, F.; Ojalvo, I. U.

1976-01-01

The paper proves convergence of an iterative procedure for calculating the deflections of built-up component structures which can be represented as consisting of a dominant, relatively stiff primary structure and a less stiff secondary structure, which may be composed of one or more substructures that are not connected to one another but are all connected to the primary structure. The iteration consists in estimating the deformation of the primary structure in the absence of the secondary structure on the assumption that all mechanical loads are applied directly to the primary structure. The j-th iterate primary structure deflections at the interface are imposed on the secondary structure, and the boundary loads required to produce these deflections are computed. The cycle is completed by applying the interface reaction to the primary structure and computing its updated deflections. It is shown that the mathematical condition for convergence of this procedure is that the maximum eigenvalue of the equation relating primary-structure deflection to imposed secondary-structure deflection be less than unity, which is shown to correspond with the physical requirement that the secondary structure be more flexible at the interface boundary.

Evaluation of dual flow thrust vectored nozzles with exhaust stream impingement. MS Thesis Final Technical Report, Oct. 1990 - Jul. 1991

NASA Technical Reports Server (NTRS)

Carpenter, Thomas W.

1991-01-01

The main objective of this project was to predict the expansion wave/oblique shock wave structure in an under-expanded jet expanding from a convergent nozzle. The shock structure was predicted by combining the calculated curvature of the free pressure boundary with principles and governing equations relating to oblique shock wave and expansion wave interaction. The procedure was then continued until the shock pattern repeated itself. A mathematical model was then formulated and written in FORTRAN to calculate the oblique shock/expansion wave structure within the jet. In order to study shock waves in expanding jets, Schlieren photography, a form of flow visualization, was employed. Thirty-six Schlieren photographs of jets from both a straight and 15 degree nozzle were taken. An iterative procedure was developed to calculate the shock structure within the jet and predict the non-dimensional values of Prandtl primary wavelength (w/rn), distance to Mach Disc (Ld) and Mach Disc radius (rd). These values were then compared to measurements taken from Schlieren photographs and experimental results. The results agreed closely to measurements from Schlieren photographs and previously obtained data. This method provides excellent results for pressure ratios below that at which a Mach Disc first forms. Calculated values of non-dimensional distance to the Mach Disc (Ld) agreed closely to values measured from Schlieren photographs and published data. The calculated values of non-dimensional Mach Disc radius (rd), however, deviated from published data by as much as 25 percent at certain pressure ratios.

Predicting the performance of a strategic alliance: an analysis of the Community Clinical Oncology Program.

PubMed Central

Kaluzny, A D; Lacey, L M; Warnecke, R; Hynes, D M; Morrissey, J; Ford, L; Sondik, E

1993-01-01

OBJECTIVE. This study is designed to examine the effects of environment and structure of the Community Clinical Oncology Program (CCOP) on performance as measured by patient accrual to National Cancer Institute (NCI)-approved treatment protocols. DATA SOURCES/STUDY SETTING. Data and analysis are part of a larger evaluation of the NCI Community Clinical Oncology Program during its second funding cycle, June 1987-May 1990. Data, taken from primary and secondary sources, included a survey of selected informants in CCOPs and research bases, CCOP grant applications, CCOP annual progress reports, and site visits to a subsample of CCOPs (N = 20) and research bases (N = 5). Accrual data were obtained from NCI records. STUDY DESIGN. Analysis involved three complementary sets of factors: the local health care resources environment available to the CCOP, the larger policy environment as reflected by the relationship of the CCOP to selected research bases and the NCI, and the operational structure of the CCOP itself. A hierarchical model examined the separate and cumulative effects of local and policy environment and structure on performance. PRINCIPAL FINDINGS. Other things equal, the primary predictors of treatment accrual were: (1) the larger policy environment, as measured by the attendance of nurses at research base meetings; and (2) operational structure, as measured by the number and character of components within participating CCOPs and the number of hours per week worked by data managers. These factors explained 73 percent of the total variance in accrual performance. CONCLUSIONS. Findings suggest criteria for selecting the types of organizations to participate in the alliance, as well as for establishing guidelines for managing such alliances. A future challenge is to determine the extent to which factors predicting accrual to cancer treatment clinical trials are equally important as predictors of accrual to cancer prevention and control trials. PMID:8514498

Buckling behavior of origami unit cell facets under compressive loads

NASA Astrophysics Data System (ADS)

Kshad, Mohamed Ali Emhmed; Naguib, Hani E.

2018-03-01

Origami structures as cores for sandwich structures are designed to withstand the compressive loads and to dissipate compressive energy. The deformation of the origami panels and the unit cell facets are the primary factors behind the compressive energy dissipation in origami structures. During the loading stage, the origami structures deform through the folding and unfolding process of the unit cell facets, and also through the plastic deformation of the facets. This work presents a numerical study of the buckling behavior of different origami unit cell elements under compressive loading. The studied origami configurations were Miura and Ron-Resch-like origami structures. Finite element package was used to model the origami structures. The study investigated the buckling behavior of the unit cell facets of two types of origami structures Miura origami and Ron-Resch-Like origami structures. The simulation was conducted using ANSYS finite element software, in which the model of the unit cell represented by shell elements, and the eigenvalues buckling solver was used to predict the theoretical buckling of the unit cell elements.

Three Dimensional Numerical Simulation and Characterization of Crack Growth in the Weld Region of a Friction Stir Welded Structure

NASA Technical Reports Server (NTRS)

Seshadri, Banavara R.; Smith, Stephen W.; Newman, John A.

2013-01-01

Friction stir welding (FSW) fabrication technology is being adopted in aerospace applications. The use of this technology can reduce production cost, lead-times, reduce structural weight and need for fasteners and lap joints, which are typically the primary locations of crack initiation and multi-site fatigue damage in aerospace structures. FSW is a solid state welding process that is well-suited for joining aluminum alloy components; however, the process introduces residual stresses (both tensile and compressive) in joined components. The propagation of fatigue cracks in a residual stress field and the resulting redistribution of the residual stress field and its effect on crack closure have to be estimated. To insure the safe insertion of complex integral structures, an accurate understanding of the fatigue crack growth behavior and the complex crack path process must be understood. A life prediction methodology for fatigue crack growth through the weld under the influence of residual stresses in aluminum alloy structures fabricated using FSW will be detailed. The effects and significance of the magnitude of residual stress at a crack tip on the estimated crack tip driving force are highlighted. The location of the crack tip relative to the FSW and the effect of microstructure on fatigue crack growth are considered. A damage tolerant life prediction methodology accounting for microstructural variation in the weld zone and residual stress field will lead to the design of lighter and more reliable aerospace structures

Code System to Calculate Tornado-Induced Flow Material Transport.

DOE Office of Scientific and Technical Information (OSTI.GOV)

ANDRAE, R. W.

1999-11-18

Version: 00 TORAC models tornado-induced flows, pressures, and material transport within structures. Its use is directed toward nuclear fuel cycle facilities and their primary release pathway, the ventilation system. However, it is applicable to other structures and can model other airflow pathways within a facility. In a nuclear facility, this network system could include process cells, canyons, laboratory offices, corridors, and offgas systems. TORAC predicts flow through a network system that also includes ventilation system components such as filters, dampers, ducts, and blowers. These ventilation system components are connected to the rooms and corridors of the facility to form amore » complete network for moving air through the structure and, perhaps, maintaining pressure levels in certain areas. The material transport capability in TORAC is very basic and includes convection, depletion, entrainment, and filtration of material.« less

Reduced exercise capacity in untreated adults with primary growth hormone resistance (Laron syndrome).

PubMed

Ben-Dov, Issahar; Gaides, Mark; Scheinowitz, Mickey; Wagner, Rivka; Laron, Zvi

2003-12-01

Primary IGF-I deficiency (Laron syndrome, LS) may decrease exercise capacity as a result of a lack of an IGF-I effect on heart, peripheral muscle or lung structure and/or function. Eight patients (six females) who had never received treatment with IGF-I, with mean age of 36 +/- 10 (SD) years (range 21-48), weight 47 +/- 9 kg (31-61), height 126 +/- 12 cm (112-140) and body mass index of 29 +/- 4 kg/m2 (24-34), and 12 age-matched controls, underwent lung function tests and incremental cycling to the limit of tolerance (CPX, MedGraphics). Predicted values for the patients were derived from adult equations based on height. In LS patients, lung function was near normal; vital capacity was 84 +/- 11% of expected (66-103). Peak exercise O2-uptake and the anaerobic threshold were reduced, 57 +/- 20% of predicted and 33 +/- 9% of predicted peak (P = 0.005 vs. controls), despite normal mean exercise breathing reserve. All parameters were normal in the controls. Exercise capacity in untreated adults with LS is significantly reduced. The limitation for most patients was not ventilatory but resulted either from low cardiac output and/or from dysfunction of the peripheral muscles. However, the relative contribution of each of these elements and/or the role of poor fitness needs further study.

Variable disruption of a syntactic processing network in primary progressive aphasia.

PubMed

Wilson, Stephen M; DeMarco, Andrew T; Henry, Maya L; Gesierich, Benno; Babiak, Miranda; Miller, Bruce L; Gorno-Tempini, Maria Luisa

2016-11-01

Syntactic processing deficits are highly variable in individuals with primary progressive aphasia. Damage to left inferior frontal cortex has been associated with syntactic deficits in primary progressive aphasia in a number of structural and functional neuroimaging studies. However, a contrasting picture of a broader syntactic network has emerged from neuropsychological studies in other aphasic cohorts, and functional imaging studies in healthy controls. To reconcile these findings, we used functional magnetic resonance imaging to investigate the functional neuroanatomy of syntactic comprehension in 51 individuals with primary progressive aphasia, composed of all clinical variants and a range of degrees of syntactic processing impairment. We used trial-by-trial reaction time as a proxy for syntactic processing load, to determine which regions were modulated by syntactic processing in each patient, and how the set of regions recruited was related to whether syntactic processing was ultimately successful or unsuccessful. Relationships between functional abnormalities and patterns of cortical atrophy were also investigated. We found that the individual degree of syntactic comprehension impairment was predicted by left frontal atrophy, but also by functional disruption of a broader syntactic processing network, comprising left posterior frontal cortex, left posterior temporal cortex, and the left intraparietal sulcus and adjacent regions. These regions were modulated by syntactic processing in healthy controls and in patients with primary progressive aphasia with relatively spared syntax, but they were modulated to a lesser extent or not at all in primary progressive aphasia patients whose syntax was relatively impaired. Our findings suggest that syntactic comprehension deficits in primary progressive aphasia reflect not only structural and functional changes in left frontal cortex, but also disruption of a wider syntactic processing network. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Manipulating Public Expectations; Pre- and Postprimary Statements in the '76 Campaign.

ERIC Educational Resources Information Center

Freshley, Dwight L.

Predicting the outcome of a primary election gives a candidate more exposure to the press, gives him or her a chance to predict modestly and then look better than the prediction, and helps create interest in the election and thereby increase voter turnout. During the 1976 Presidential primaries, most candidates adhered to the classic rule to make…

Do Different Young Plantation-Grown Species Require Different Biomass Models?

Treesearch

Bryce E. Schlaegel; Harvey E. Kennedy

1985-01-01

Sweetgum and water oak trees sampled from a plantation over 7 years were used to test whether primary tree component (bole wood, bole bark, limb wood, limb bark, and leaves) predictions could be summed to estimate total bole, total limb, and total tree values. Estimations by summing primary component predictions were not significantly different from predictions for the...

Overview of the ACT program

NASA Technical Reports Server (NTRS)

Davis, John G., Jr.

1992-01-01

NASA's Advanced Composites Program (ACT) was initiated in 1988. A National Research Announcement was issued to solicit innovative ideas that could significantly contribute to development and demonstration of an integrated technology data base and confidence level that permits cost-effective use of composite primary structures in transport aircraft. Fifteen contracts were awarded by the Spring of 1989 and the participants include commercial and military airframe manufacturers, materials developers and suppliers, universities, and government laboratories. The program approach is to develop materials, structural mechanics methodology, design concepts, and fabrication procedures that offer the potential to make composite structures cost-effective compared to aluminum structure. Goals for the ACT program included 30-50 percent weight reduction, 20-25 percent acquisition cost reduction, and provided the scientific basis for predicting materials and structures performance. This paper provides an overview of the ACT program status, plans, and selected technical accomplishments. Sixteen additional papers, which provide more detailed information on the research and development accomplishments, are contained in this publication.

EPA DSSTox and ToxCast Project Updates: Generating New ...

EPA Pesticide Factsheets

EPA’s National Center for Computational Toxicology is generating data and capabilities to support a new paradigm for toxicity screening and prediction. The DSSTox project is improving public access to quality structure-annotated chemical toxicity information in less summarized forms than traditionally employed in SAR modeling, and in ways that facilitate data-mining and data read-across. The DSSTox Structure-Browser provides structure searchability across the full published DSSTox toxicity-related inventory, enables linkages to and from previously isolated toxicity data resources (soon to include public microarray resources GEO, ArrayExpress, and CEBS), and provides link-outs to cross-indexed public resources such as PubChem, ChemSpider, and ACToR. The published DSSTox inventory and bioassay information also have been integrated into PubChem allowing a user to take full advantage of PubChem structure-activity and bioassay clustering features. Phase I of the ToxCastTM project has generated high-throughput screening (HTS) data from several hundred biochemical and cell-based assays for a set of 320 chemicals, mostly pesticide actives, with rich toxicology profiles. DSSTox and ACToR are providing the primary cheminformatics support for ToxCastTM and collaborative efforts with the National Toxicology Program’s HTS Program and the NIH Chemical Genomics Center. DSSTox will also be a primary vehicle for publishing ToxCastTM ToxRef summarized bioassay data for use

Predicting the onset of hazardous alcohol drinking in primary care: development and validation of a simple risk algorithm.

PubMed

Bellón, Juan Ángel; de Dios Luna, Juan; King, Michael; Nazareth, Irwin; Motrico, Emma; GildeGómez-Barragán, María Josefa; Torres-González, Francisco; Montón-Franco, Carmen; Sánchez-Celaya, Marta; Díaz-Barreiros, Miguel Ángel; Vicens, Catalina; Moreno-Peral, Patricia

2017-04-01

Little is known about the risk of progressing to hazardous alcohol use in abstinent or low-risk drinkers. To develop and validate a simple brief risk algorithm for the onset of hazardous alcohol drinking (HAD) over 12 months for use in primary care. Prospective cohort study in 32 health centres from six Spanish provinces, with evaluations at baseline, 6 months, and 12 months. Forty-one risk factors were measured and multilevel logistic regression and inverse probability weighting were used to build the risk algorithm. The outcome was new occurrence of HAD during the study, as measured by the AUDIT. From the lists of 174 GPs, 3954 adult abstinent or low-risk drinkers were recruited. The 'predictAL-10' risk algorithm included just nine variables (10 questions): province, sex, age, cigarette consumption, perception of financial strain, having ever received treatment for an alcohol problem, childhood sexual abuse, AUDIT-C, and interaction AUDIT-C*Age. The c-index was 0.886 (95% CI = 0.854 to 0.918). The optimal cutoff had a sensitivity of 0.83 and specificity of 0.80. Excluding childhood sexual abuse from the model (the 'predictAL-9'), the c-index was 0.880 (95% CI = 0.847 to 0.913), sensitivity 0.79, and specificity 0.81. There was no statistically significant difference between the c-indexes of predictAL-10 and predictAL-9. The predictAL-10/9 is a simple and internally valid risk algorithm to predict the onset of hazardous alcohol drinking over 12 months in primary care attendees; it is a brief tool that is potentially useful for primary prevention of hazardous alcohol drinking. © British Journal of General Practice 2017.

Predicting the Onset of Anxiety Syndromes at 12 Months in Primary Care Attendees. The PredictA-Spain Study

PubMed Central

Moreno-Peral, Patricia; Luna, Juan de Dios; Marston, Louise; King, Michael; Nazareth, Irwin; Motrico, Emma; GildeGómez-Barragán, María Josefa; Torres-González, Francisco; Montón-Franco, Carmen; Sánchez-Celaya, Marta; Díaz-Barreiros, Miguel Ángel; Vicens, Catalina; Muñoz-Bravo, Carlos; Bellón, Juan Ángel

2014-01-01

Background There are no risk algorithms for the onset of anxiety syndromes at 12 months in primary care. We aimed to develop and validate internally a risk algorithm to predict the onset of anxiety syndromes at 12 months. Methods A prospective cohort study with evaluations at baseline, 6 and 12 months. We measured 39 known risk factors and used multilevel logistic regression and inverse probability weighting to build the risk algorithm. Our main outcome was generalized anxiety, panic and other non-specific anxiety syndromes as measured by the Primary Care Evaluation of Mental Disorders, Patient Health Questionnaire (PRIME-MD-PHQ). We recruited 3,564 adult primary care attendees without anxiety syndromes from 174 family physicians and 32 health centers in 6 Spanish provinces. Results The cumulative 12-month incidence of anxiety syndromes was 12.2%. The predictA-Spain risk algorithm included the following predictors of anxiety syndromes: province; sex (female); younger age; taking medicines for anxiety, depression or stress; worse physical and mental quality of life (SF-12); dissatisfaction with paid and unpaid work; perception of financial strain; and the interactions sex*age, sex*perception of financial strain, and age*dissatisfaction with paid work. The C-index was 0.80 (95% confidence interval = 0.78–0.83) and the Hedges' g = 1.17 (95% confidence interval = 1.04–1.29). The Copas shrinkage factor was 0.98 and calibration plots showed an accurate goodness of fit. Conclusions The predictA-Spain risk algorithm is valid to predict anxiety syndromes at 12 months. Although external validation is required, the predictA-Spain is available for use as a predictive tool in the prevention of anxiety syndromes in primary care. PMID:25184313

Weighting Primary Care Patient Panel Size: A Novel Electronic Health Record-Derived Measure Using Machine Learning.

PubMed

Rajkomar, Alvin; Yim, Joanne Wing Lan; Grumbach, Kevin; Parekh, Ami

2016-10-14

Characterizing patient complexity using granular electronic health record (EHR) data regularly available to health systems is necessary to optimize primary care processes at scale. To characterize the utilization patterns of primary care patients and create weighted panel sizes for providers based on work required to care for patients with different patterns. We used EHR data over a 2-year period from patients empaneled to primary care clinicians in a single academic health system, including their in-person encounter history and virtual encounters such as telephonic visits, electronic messaging, and care coordination with specialists. Using a combination of decision rules and k-means clustering, we identified clusters of patients with similar health care system activity. Phenotypes with basic demographic information were used to predict future health care utilization using log-linear models. Phenotypes were also used to calculate weighted panel sizes. We identified 7 primary care utilization phenotypes, which were characterized by various combinations of primary care and specialty usage and were deemed clinically distinct by primary care physicians. These phenotypes, combined with age-sex and primary payer variables, predicted future primary care utilization with R 2 of .394 and were used to create weighted panel sizes. Individual patients' health care utilization may be useful for classifying patients by primary care work effort and for predicting future primary care usage.

Identifying Drug-Target Interactions with Decision Templates.

PubMed

Yan, Xiao-Ying; Zhang, Shao-Wu

2018-01-01

During the development process of new drugs, identification of the drug-target interactions wins primary concerns. However, the chemical or biological experiments bear the limitation in coverage as well as the huge cost of both time and money. Based on drug similarity and target similarity, chemogenomic methods can be able to predict potential drug-target interactions (DTIs) on a large scale and have no luxurious need about target structures or ligand entries. In order to reflect the cases that the drugs having variant structures interact with common targets and the targets having dissimilar sequences interact with same drugs. In addition, though several other similarity metrics have been developed to predict DTIs, the combination of multiple similarity metrics (especially heterogeneous similarities) is too naïve to sufficiently explore the multiple similarities. In this paper, based on Gene Ontology and pathway annotation, we introduce two novel target similarity metrics to address above issues. More importantly, we propose a more effective strategy via decision template to integrate multiple classifiers designed with multiple similarity metrics. In the scenarios that predict existing targets for new drugs and predict approved drugs for new protein targets, the results on the DTI benchmark datasets show that our target similarity metrics are able to enhance the predictive accuracies in two scenarios. And the elaborate fusion strategy of multiple classifiers has better predictive power than the naïve combination of multiple similarity metrics. Compared with other two state-of-the-art approaches on the four popular benchmark datasets of binary drug-target interactions, our method achieves the best results in terms of AUC and AUPR for predicting available targets for new drugs (S2), and predicting approved drugs for new protein targets (S3).These results demonstrate that our method can effectively predict the drug-target interactions. The software package can freely available at https://github.com/NwpuSY/DT_all.git for academic users. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Cellulose-Pectin Spatial Contacts Are Inherent to Never-Dried Arabidopsis Primary Cell Walls: Evidence from Solid-State Nuclear Magnetic Resonance1[OPEN

PubMed Central

Wang, Tuo; Park, Yong Bum; Hong, Mei

2015-01-01

The structural role of pectins in plant primary cell walls is not yet well understood because of the complex and disordered nature of the cell wall polymers. We recently introduced multidimensional solid-state nuclear magnetic resonance spectroscopy to characterize the spatial proximities of wall polysaccharides. The data showed extensive cross peaks between pectins and cellulose in the primary wall of Arabidopsis (Arabidopsis thaliana), indicating subnanometer contacts between the two polysaccharides. This result was unexpected because stable pectin-cellulose interactions are not predicted by in vitro binding assays and prevailing cell wall models. To investigate whether the spatial contacts that give rise to the cross peaks are artifacts of sample preparation, we now compare never-dried Arabidopsis primary walls with dehydrated and rehydrated samples. One-dimensional 13C spectra, two-dimensional 13C-13C correlation spectra, water-polysaccharide correlation spectra, and dynamics data all indicate that the structure, mobility, and intermolecular contacts of the polysaccharides are indistinguishable between never-dried and rehydrated walls. Moreover, a partially depectinated cell wall in which 40% of homogalacturonan is extracted retains cellulose-pectin cross peaks, indicating that the cellulose-pectin contacts are not due to molecular crowding. The cross peaks are observed both at −20°C and at ambient temperature, thus ruling out freezing as a cause of spatial contacts. These results indicate that rhamnogalacturonan I and a portion of homogalacturonan have significant interactions with cellulose microfibrils in the native primary wall. This pectin-cellulose association may be formed during wall biosynthesis and may involve pectin entrapment in or between cellulose microfibrils, which cannot be mimicked by in vitro binding assays. PMID:26036615

Chemogenomics approaches to rationalizing the mode-of-action of traditional Chinese and Ayurvedic medicines.

PubMed

Mohd Fauzi, Fazlin; Koutsoukas, Alexios; Lowe, Robert; Joshi, Kalpana; Fan, Tai-Ping; Glen, Robert C; Bender, Andreas

2013-03-25

Traditional Chinese medicine (TCM) and Ayurveda have been used in humans for thousands of years. While the link to a particular indication has been established in man, the mode-of-action (MOA) of the formulations often remains unknown. In this study, we aim to understand the MOA of formulations used in traditional medicine using an in silico target prediction algorithm, which aims to predict protein targets (and hence MOAs), given the chemical structure of a compound. Following this approach we were able to establish several links between suggested MOAs and experimental evidence. In particular, compounds from the 'tonifying and replenishing medicinal' class from TCM exhibit a hypoglycemic effect which can be related to activity of the ingredients against the Sodium-Glucose Transporters (SGLT) 1 and 2 as well as Protein Tyrosine Phosphatase (PTP). Similar results were obtained for Ayurvedic anticancer drugs. Here, both primary anticancer targets (those directly involved in cancer pathogenesis) such as steroid-5-alpha-reductase 1 and 2 were predicted as well as targets which act synergistically with the primary target, such as the efflux pump P-glycoprotein (P-gp). In addition, we were able to elucidate some targets which may point us to novel MOAs as well as explain side effects. Most notably, GPBAR1, which was predicted as a target for both 'tonifying and replenishing medicinal' and anticancer classes, suggests an influence of the compounds on metabolism. Understanding the MOA of these compounds is beneficial as it provides a resource for NMEs with possibly higher efficacy in the clinic than those identified by single-target biochemical assays.

Structure of the Wechsler Intelligence Scale for Children - Fourth Edition in a Group of Children with ADHD.

PubMed

Gomez, Rapson; Vance, Alasdair; Watson, Shaun D

2016-01-01

This study used confirmatory factor analysis to examine the factor structure for the 10 core WISC-IV subtests in a group of children (N = 812) with ADHD. The study examined oblique four- and five-factor models, higher order models with one general secondary factor and four and five primary factors, and a bifactor model with a general factor and four specific factors. The findings supported all models tested, with the bifactor model being the optimum model. For this model, only the general factor had high explained common variance and omega hierarchical value, and it predicted reading and arithmetic abilities. The findings favor the use of the FSIQ scores of the WISC-IV, but not the subscale index scores.

The Response of a Mechanical Oscillator Due to Swept and Dithered Excitation

NASA Technical Reports Server (NTRS)

Davis, R. Benjamin; Durham, R. Caitlyn; Brown, Andrew M.

2010-01-01

A single degree-of-freedom oscillator subject to linearly swept and/or dithered excitation is considered. Dither refers to the variation of an excitation frequency about a given nominal, or primary, frequency. Dither in rocket engine turbopump shaft speeds can be an important consideration when analyzing the dynamic response of turbomachinery components such as turbine blades. Results indicate that the incorporation of dithered excitation into a fatigue analysis may extend the predicted fatigue life of the structure by a factor of two or more.

Prognosis for children with acute liver failure due to Amanita phalloides poisoning

NASA Astrophysics Data System (ADS)

Wachulski, Marcin F.; Kamińska-Gocał, Diana; Dądalski, Maciej; Socha, Piotr; Mulawka, Jan J.

2011-10-01

The primary objective of this article is to find new effective methods of diagnosis of urgent liver transplantation after Amanita phalloides intoxication amongst pediatric patients. The research was carried out using a medical database of pediatric patients who suffered from acute liver failure after amatoxin consumption. After data preprocessing and attribute selection steps, a two-phase experiment was conducted, which incorporated a wide variety of data mining algorithms. The results deliver two equivalent classification models with simple decision structure and reasonable quality of surgery prediction.

Ostertagia circumcincta: isolation of a partial cDNA encoding an unusual member of the mitochondrial processing peptidase subfamily of M16 metallopeptidases.

PubMed

Walker, J; Tait, A

1997-11-01

A reverse-transcriptase polymerase chain reaction (PCR) procedure was used to isolate an Ostertagia circumcincta partial cDNA encoding a protein with general primary sequence features characteristic of members of the mitochondrial processing peptidase (MPP) subfamily of M16 metallopeptidases. The structural relationships of the predicted protein (Oc MPPX) with MPP subfamily proteins from other species (including the model free-living nematode Caenorhabditis elegans) were examined, and Northern analysis confirmed the expression of the Oc mppx gene in adult nematodes.

Imaging of Traumatic Brain Injury.

PubMed

Bodanapally, Uttam K; Sours, Chandler; Zhuo, Jiachen; Shanmuganathan, Kathirkamanathan

2015-07-01

Imaging plays an important role in the management of patients with traumatic brain injury (TBI). Computed tomography (CT) is the first-line imaging technique allowing rapid detection of primary structural brain lesions that require surgical intervention. CT also detects various deleterious secondary insults allowing early medical and surgical management. Serial imaging is critical to identifying secondary injuries. MR imaging is indicated in patients with acute TBI when CT fails to explain neurologic findings. However, MR imaging is superior in patients with subacute and chronic TBI and also predicts neurocognitive outcome. Copyright © 2015 Elsevier Inc. All rights reserved.

Development of a prediction tool for patients presenting with acute cough in primary care: a prognostic study spanning six European countries.

PubMed

Bruyndonckx, Robin; Hens, Niel; Verheij, Theo Jm; Aerts, Marc; Ieven, Margareta; Butler, Christopher C; Little, Paul; Goossens, Herman; Coenen, Samuel

2018-05-01

Accurate prediction of the course of an acute cough episode could curb antibiotic overprescribing, but is still a major challenge in primary care. The authors set out to develop a new prediction rule for poor outcome (re-consultation with new or worsened symptoms, or hospital admission) in adults presenting to primary care with acute cough. Data were collected from 2604 adults presenting to primary care with acute cough or symptoms suggestive of lower respiratory tract infection (LRTI) within the Genomics to combat Resistance against Antibiotics in Community-acquired LRTI in Europe (GRACE; www.grace-lrti.org) Network of Excellence. Important signs and symptoms for the new prediction rule were found by combining random forest and logistic regression modelling. Performance to predict poor outcome in acute cough patients was compared with that of existing prediction rules, using the models' area under the receiver operator characteristic curve (AUC), and any improvement obtained by including additional test results (C-reactive protein [CRP], blood urea nitrogen [BUN], chest radiography, or aetiology) was evaluated using the same methodology. The new prediction rule, included the baseline Risk of poor outcome, Interference with daily activities, number of years stopped Smoking (> or <45 years), severity of Sputum, presence of Crackles, and diastolic blood pressure (> or <85 mmHg) (RISSC85). Though performance of RISSC85 was moderate (sensitivity 62%, specificity 59%, positive predictive value 27%, negative predictive value 86%, AUC 0.63, 95% confidence interval [CI] = 0.61 to 0.67), it outperformed all existing prediction rules used today (highest AUC 0.53, 95% CI = 0.51 to 0.56), and could not be significantly improved by including additional test results (highest AUC 0.64, 95% CI = 0.62 to 0.68). The new prediction rule outperforms all existing alternatives in predicting poor outcome in adult patients presenting to primary care with acute cough and could not be improved by including additional test results. © British Journal of General Practice 2018.

The predictive influence of family and neighborhood assets on fighting and weapon carrying from mid- to late adolescence.

PubMed

Haegerich, Tamara M; Oman, Roy F; Vesely, Sara K; Aspy, Cheryl B; Tolma, Eleni L

2014-08-01

Using a developmental, social-ecological approach to understand the etiology of health-risk behavior and inform primary prevention efforts, we assess the predictive effects of family and neighborhood social processes on youth physical fighting and weapon carrying. Specifically, we focus on relationships among youth and their parents, family communication, parental monitoring, as well as sense of community and neighborhood informal social control, support, concerns, and disorder. This study advances knowledge through its investigation of family and neighborhood structural factors and social processes together, employment of longitudinal models that estimate effects over adolescent development, and use of self-report and observational measures. Data from 1,093 youth/parent pairs were analyzed from the Youth Assets Study using a Generalized Estimating Equation approach; family and neighborhood assets and risks were analyzed as time varying and lagged. Similar family assets affected physical fighting and weapon carrying, whereas different neighborhood social processes influenced the two forms of youth violence. Study findings have implications for the primary prevention of youth violence, including the use of family-based approaches that build relationships and parental monitoring skills and community-level change approaches that promote informal social control and reduce neighborhood concerns about safety.

Changes of soil prokaryotic communities after clear-cutting in a karst forest: evidences for cutting-based disturbance promoting deterministic processes.

PubMed

Zhang, Xiao; Liu, Shirong; Li, Xiangzhen; Wang, Jingxin; Ding, Qiong; Wang, Hui; Tian, Chao; Yao, Minjie; An, Jiaxing; Huang, Yongtao

2016-03-01

To understand the temporal responses of soil prokaryotic communities to clear-cutting disturbance, we examined the changes in soil bacterial and archaeal community composition, structure and diversity along a chronosequence of forest successional restoration using high-throughput 16S rRNA gene sequencing. Our results demonstrated that clear-cutting significantly altered soil bacterial community structure, while no significant shifts of soil archaeal communities were observed. The hypothesis that soil bacterial communities would become similar to those of surrounding intact primary forest with natural regeneration was supported by the shifts in the bacterial community composition and structure. Bacterial community diversity patterns induced by clear-cutting were consistent with the intermediate disturbance hypothesis. Dynamics of bacterial communities was mostly driven by soil properties, which collectively explained more than 70% of the variation in bacterial community composition. Community assembly data revealed that clear-cutting promoted the importance of the deterministic processes in shaping bacterial communities, coinciding with the resultant low resource environments. But assembly processes in the secondary forest returned a similar level compared to the intact primary forest. These findings suggest that bacterial community dynamics may be predictable during the natural recovery process. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

X-ray scattering data and structural genomics

NASA Astrophysics Data System (ADS)

Doniach, Sebastian

2003-03-01

High throughput structural genomics has the ambitious goal of determining the structure of all, or a very large number of protein folds using the high-resolution techniques of protein crystallography and NMR. However, the program is facing significant bottlenecks in reaching this goal, which include problems of protein expression and crystallization. In this talk, some preliminary results on how the low-resolution technique of small-angle X-ray solution scattering (SAXS) can help ameliorate some of these bottlenecks will be presented. One of the most significant bottlenecks arises from the difficulty of crystallizing integral membrane proteins, where only a handful of structures are available compared to thousands of structures for soluble proteins. By 3-dimensional reconstruction from SAXS data, the size and shape of detergent-solubilized integral membrane proteins can be characterized. This information can then be used to classify membrane proteins which constitute some 25% of all genomes. SAXS may also be used to study the dependence of interparticle interference scattering on solvent conditions so that regions of the protein solution phase diagram which favor crystallization can be elucidated. As a further application, SAXS may be used to provide physical constraints on computational methods for protein structure prediction based on primary sequence information. This in turn can help in identifying structural homologs of a given protein, which can then give clues to its function. D. Walther, F. Cohen and S. Doniach. "Reconstruction of low resolution three-dimensional density maps from one-dimensional small angle x-ray scattering data for biomolecules." J. Appl. Cryst. 33(2):350-363 (2000). Protein structure prediction constrained by solution X-ray scattering data and structural homology identification Zheng WJ, Doniach S JOURNAL OF MOLECULAR BIOLOGY , v. 316(#1) pp. 173-187 FEB 8, 2002

Crack Detection in Fibre Reinforced Plastic Structures Using Embedded Fibre Bragg Grating Sensors: Theory, Model Development and Experimental Validation

PubMed Central

Pereira, G. F.; Mikkelsen, L. P.; McGugan, M.

2015-01-01

In a fibre-reinforced polymer (FRP) structure designed using the emerging damage tolerance and structural health monitoring philosophy, sensors and models that describe crack propagation will enable a structure to operate despite the presence of damage by fully exploiting the material’s mechanical properties. When applying this concept to different structures, sensor systems and damage types, a combination of damage mechanics, monitoring technology, and modelling is required. The primary objective of this article is to demonstrate such a combination. This article is divided in three main topics: the damage mechanism (delamination of FRP), the structural health monitoring technology (fibre Bragg gratings to detect delamination), and the finite element method model of the structure that incorporates these concepts into a final and integrated damage-monitoring concept. A novel method for assessing a crack growth/damage event in fibre-reinforced polymer or structural adhesive-bonded structures using embedded fibre Bragg grating (FBG) sensors is presented by combining conventional measured parameters, such as wavelength shift, with parameters associated with measurement errors, typically ignored by the end-user. Conjointly, a novel model for sensor output prediction (virtual sensor) was developed using this FBG sensor crack monitoring concept and implemented in a finite element method code. The monitoring method was demonstrated and validated using glass fibre double cantilever beam specimens instrumented with an array of FBG sensors embedded in the material and tested using an experimental fracture procedure. The digital image correlation technique was used to validate the model prediction by correlating the specific sensor response caused by the crack with the developed model. PMID:26513653

Medium-term electric power demand forecasting based on economic-electricity transmission model

NASA Astrophysics Data System (ADS)

Li, Wenfeng; Bao, Fangmin; Bai, Hongkun; Liu, Wei; Liu, Yongmin; Mao, Yubin; Wang, Jiangbo; Liu, Junhui

2018-06-01

Electric demand forecasting is a basic work to ensure the safe operation of power system. Based on the theories of experimental economics and econometrics, this paper introduces Prognoz Platform 7.2 intelligent adaptive modeling platform, and constructs the economic electricity transmission model that considers the economic development scenarios and the dynamic adjustment of industrial structure to predict the region's annual electricity demand, and the accurate prediction of the whole society's electricity consumption is realized. Firstly, based on the theories of experimental economics and econometrics, this dissertation attempts to find the economic indicator variables that drive the most economical growth of electricity consumption and availability, and build an annual regional macroeconomic forecast model that takes into account the dynamic adjustment of industrial structure. Secondly, it innovatively put forward the economic electricity directed conduction theory and constructed the economic power transfer function to realize the group forecast of the primary industry + rural residents living electricity consumption, urban residents living electricity, the second industry electricity consumption, the tertiary industry electricity consumption; By comparing with the actual value of economy and electricity in Henan province in 2016, the validity of EETM model is proved, and the electricity consumption of the whole province from 2017 to 2018 is predicted finally.

Challenges Facing Design and Analysis Tools

NASA Technical Reports Server (NTRS)

Knight, Norman F., Jr.; Broduer, Steve (Technical Monitor)

2001-01-01

The design and analysis of future aerospace systems will strongly rely on advanced engineering analysis tools used in combination with risk mitigation procedures. The implications of such a trend place increased demands on these tools to assess off-nominal conditions, residual strength, damage propagation, and extreme loading conditions in order to understand and quantify these effects as they affect mission success. Advances in computer hardware such as CPU processing speed, memory, secondary storage, and visualization provide significant resources for the engineer to exploit in engineering design. The challenges facing design and analysis tools fall into three primary areas. The first area involves mechanics needs such as constitutive modeling, contact and penetration simulation, crack growth prediction, damage initiation and progression prediction, transient dynamics and deployment simulations, and solution algorithms. The second area involves computational needs such as fast, robust solvers, adaptivity for model and solution strategies, control processes for concurrent, distributed computing for uncertainty assessments, and immersive technology. Traditional finite element codes still require fast direct solvers which when coupled to current CPU power enables new insight as a result of high-fidelity modeling. The third area involves decision making by the analyst. This area involves the integration and interrogation of vast amounts of information - some global in character while local details are critical and often drive the design. The proposed presentation will describe and illustrate these areas using composite structures, energy-absorbing structures, and inflatable space structures. While certain engineering approximations within the finite element model may be adequate for global response prediction, they generally are inadequate in a design setting or when local response prediction is critical. Pitfalls to be avoided and trends for emerging analysis tools will be described.

Extreme primary and secondary protein structure variability in the chimeric male-transmitted cytochrome c oxidase subunit II protein in freshwater mussels: Evidence for an elevated amino acid substitution rate in the face of domain-specific purifying selection

PubMed Central

2008-01-01

Background Freshwater unionoidean bivalves, and species representing two marine bivalve orders (Mytiloida and Veneroida), exhibit a mode of mtDNA inheritance involving distinct maternal (F) and paternal (M) transmission routes concomitant with highly divergent gender-associated mtDNA genomes. Additionally, male unionoidean bivalves have a ~550 bp 3' coding extension to the cox2 gene (Mcox2e), that is apparently absent from all other metazoan taxa. Results Our molecular sequence analyses of MCOX2e indicate that both the primary and secondary structures of the MCOX2e region are evolving much faster than other regions of the F and M COX2-COX1 gene junction. The near N-terminus ~2/3 of the MCOX2e region contains an interspecifically variable number of predicted transmembrane helices (TMH) and interhelical loops (IHL) whereas the C-terminus ~1/3 is relatively conserved and hydrophilic while containing conserved functional motifs. MCOX2e displays an overall pattern of purifying selection that leads to the preservation of TMH/IHL and C-terminus tail sub-regions. However, 14 amino acid positions in the MCOX2e TMH/IHL sub-region might be targeted by diversifying selection, each representing a site where there exists interspecific variation for the constituent amino acids residing in a TMH or IHL. Conclusion Our results indicate that Mcox2e is unique to unionoidean bivalves, likely the result of a single insertion event that took place over 65 MYA and that MCOX2e is functional. The predicted TMH number, length and position variability likely stems from substitution-based processes rather than the typically implicated insertion/deletion events. MCOX2e has relatively high rates of primary and secondary structure evolution, with some amino acid residues potentially subjected to site-specific positive selection, yet an overall pattern of purifying selection leading to the preservation of the TMH/IHL and hydrophilic C-terminus tail subregions. The more conserved C-terminus tail (relative to the TMH/IHL sub-region of MCOX2e) is likely biologically active because it contains functional motifs. The rapid evolution of primary and secondary structure in MCOX2e, combined with the action of both positive and purifying selection, provide supporting evidence for the hypothesis that MCOX2e has a novel reproductive function within unionoidean bivalves. All tolled, our data indicate that unionoidean bivalve MCOX2 is the first reported chimeric animal mtDNA-encoded protein. PMID:18513440

Goal conflict, goal facilitation, and health professionals' provision of physical activity advice in primary care: an exploratory prospective study.

PubMed

Presseau, Justin; Francis, Jill J; Campbell, Neil C; Sniehotta, Falko F

2011-07-15

The theory of planned behaviour has well-evidenced utility in predicting health professional behaviour, but focuses on a single behaviour isolated from the numerous potentially conflicting and facilitating goal-directed behaviours performed alongside. Goal conflict and goal facilitation may influence whether health professionals engage in guideline-recommended behaviours, and may supplement the predictive power of the theory of planned behaviour. We hypothesised that goal facilitation and goal conflict contribute to predicting primary care health professionals' provision of physical activity advice to patients with hypertension, over and above predictors of behaviour from the theory of planned behaviour. Using a prospective predictive design, at baseline we invited a random sample of 606 primary care health professionals from all primary care practices in NHS Grampian and NHS Tayside (Scotland) to complete postal questionnaires. Goal facilitation and goal conflict were measured alongside theory of planned behaviour constructs at baseline. At follow-up six months later, participants self-reported the number of patients, out of those seen in the preceding two weeks, to whom they provided physical activity advice. Forty-four primary care physicians and nurses completed measures at both time points (7.3% response rate). Goal facilitation and goal conflict improved the prediction of behaviour, accounting for substantial additional variance (5.8% and 8.4%, respectively) in behaviour over and above intention and perceived behavioural control. Health professionals' provision of physical activity advice in primary care can be predicted by perceptions about how their conflicting and facilitating goal-directed behaviours help and hinder giving advice, over and above theory of planned behaviour constructs. Incorporating features of multiple goal pursuit into the theory of planned behaviour may help to better understand health professional behaviour.

Goal conflict, goal facilitation, and health professionals' provision of physical activity advice in primary care: An exploratory prospective study

PubMed Central

2011-01-01

Background The theory of planned behaviour has well-evidenced utility in predicting health professional behaviour, but focuses on a single behaviour isolated from the numerous potentially conflicting and facilitating goal-directed behaviours performed alongside. Goal conflict and goal facilitation may influence whether health professionals engage in guideline-recommended behaviours, and may supplement the predictive power of the theory of planned behaviour. We hypothesised that goal facilitation and goal conflict contribute to predicting primary care health professionals' provision of physical activity advice to patients with hypertension, over and above predictors of behaviour from the theory of planned behaviour. Methods Using a prospective predictive design, at baseline we invited a random sample of 606 primary care health professionals from all primary care practices in NHS Grampian and NHS Tayside (Scotland) to complete postal questionnaires. Goal facilitation and goal conflict were measured alongside theory of planned behaviour constructs at baseline. At follow-up six months later, participants self-reported the number of patients, out of those seen in the preceding two weeks, to whom they provided physical activity advice. Results Forty-four primary care physicians and nurses completed measures at both time points (7.3% response rate). Goal facilitation and goal conflict improved the prediction of behaviour, accounting for substantial additional variance (5.8% and 8.4%, respectively) in behaviour over and above intention and perceived behavioural control. Conclusions Health professionals' provision of physical activity advice in primary care can be predicted by perceptions about how their conflicting and facilitating goal-directed behaviours help and hinder giving advice, over and above theory of planned behaviour constructs. Incorporating features of multiple goal pursuit into the theory of planned behaviour may help to better understand health professional behaviour. PMID:21762486

c-Fos expression predicts long-term social memory retrieval in mice.

PubMed

Lüscher Dias, Thomaz; Fernandes Golino, Hudson; Moura de Oliveira, Vinícius Elias; Dutra Moraes, Márcio Flávio; Schenatto Pereira, Grace

2016-10-15

The way the rodent brain generally processes socially relevant information is rather well understood. How social information is stored into long-term social memory, however, is still under debate. Here, brain c-Fos expression was measured after adult mice were exposed to familiar or novel juveniles and expression was compared in several memory and socially relevant brain areas. Machine Learning algorithm Random Forest was then used to predict the social interaction category of adult mice based on c-Fos expression in these areas. Interaction with a familiar co-specific altered brain activation in the olfactory bulb, amygdala, hippocampus, lateral septum and medial prefrontal cortex. Remarkably, Random Forest was able to predict interaction with a familiar juvenile with 100% accuracy. Activity in the olfactory bulb, amygdala, hippocampus and the medial prefrontal cortex were crucial to this prediction. From our results, we suggest long-term social memory depends on initial social olfactory processing in the medial amygdala and its output connections synergistically with non-social contextual integration by the hippocampus and medial prefrontal cortex top-down modulation of primary olfactory structures. Copyright © 2016 Elsevier B.V. All rights reserved.

Vocabulary learning in primary school children: working memory and long-term memory components.

PubMed

Morra, Sergio; Camba, Roberta

2009-10-01

The goal of this study was to investigate which working memory and long-term memory components predict vocabulary learning. We used a nonword learning paradigm in which 8- to 10-year-olds learned picture-nonword pairs. The nonwords varied in length (two vs. four syllables) and phonology (native sounding vs. including one Russian phoneme). Short, phonologically native nonwords were learned best, whereas learning long nonwords leveled off after a few presentation cycles. Linear structural equation analyses showed an influence of three constructs-phonological sensitivity, vocabulary knowledge, and central attentional resources (M capacity)-on nonword learning, but the extent of their contributions depended on specific characteristics of the nonwords to be learned. Phonological sensitivity predicted learning of all nonword types except short native nonwords, vocabulary predicted learning of only short native nonwords, and M capacity predicted learning of short nonwords but not long nonwords. The discussion considers three learning processes-effortful activation of phonological representations, lexical mediation, and passive associative learning-that use different cognitive resources and could be involved in learning different nonword types.

Using Deep Learning Model for Meteorological Satellite Cloud Image Prediction

NASA Astrophysics Data System (ADS)

Su, X.

2017-12-01

A satellite cloud image contains much weather information such as precipitation information. Short-time cloud movement forecast is important for precipitation forecast and is the primary means for typhoon monitoring. The traditional methods are mostly using the cloud feature matching and linear extrapolation to predict the cloud movement, which makes that the nonstationary process such as inversion and deformation during the movement of the cloud is basically not considered. It is still a hard task to predict cloud movement timely and correctly. As deep learning model could perform well in learning spatiotemporal features, to meet this challenge, we could regard cloud image prediction as a spatiotemporal sequence forecasting problem and introduce deep learning model to solve this problem. In this research, we use a variant of Gated-Recurrent-Unit(GRU) that has convolutional structures to deal with spatiotemporal features and build an end-to-end model to solve this forecast problem. In this model, both the input and output are spatiotemporal sequences. Compared to Convolutional LSTM(ConvLSTM) model, this model has lower amount of parameters. We imply this model on GOES satellite data and the model perform well.

Influence of press-fit parameters on the primary stability of uncemented femoral resurfacing implants.

PubMed

Gebert, A; Peters, J; Bishop, N E; Westphal, F; Morlock, M M

2009-01-01

Primary stability is essential to the success of uncemented prostheses. It is strongly influenced by implantation technique, implant design and bone quality. The goal of this study was to investigate the effect of press-fit parameters on the primary stability of uncemented femoral head resurfacing prostheses. An in vitro study with human specimens and prototype implants (nominal radial interference 170 and 420 microm) was used to investigate the effect of interference on primary stability. A finite element model was used to assess the influence of interference, friction between implant and bone, and bone quality. Primary stability was represented by the torque capacity of the implant. The model predicted increasing stability with actual interference, bone quality and friction coefficient; plastic deformation of the bone began at interferences of less than 100 microm. Experimentally, however, stability was not related to interference. This may be due to abrasion or the collapse of trabecular bone structures at higher interferences, which could not be captured by the model. High nominal interferences as tested experimentally appear unlikely to result in improved stability clinically. An implantation force of about 2,500 N was estimated to be sufficient to achieve a torque capacity of about 30 N m with a small interference (70 microm).

Pre-stimulus thalamic theta power predicts human memory formation.

PubMed

Sweeney-Reed, Catherine M; Zaehle, Tino; Voges, Jürgen; Schmitt, Friedhelm C; Buentjen, Lars; Kopitzki, Klaus; Richardson-Klavehn, Alan; Hinrichs, Hermann; Heinze, Hans-Jochen; Knight, Robert T; Rugg, Michael D

2016-09-01

Pre-stimulus theta (4-8Hz) power in the hippocampus and neocortex predicts whether a memory for a subsequent event will be formed. Anatomical studies reveal thalamus-hippocampal connectivity, and lesion, neuroimaging, and electrophysiological studies show that memory processing involves the dorsomedial (DMTN) and anterior thalamic nuclei (ATN). The small size and deep location of these nuclei have limited real-time study of their activity, however, and it is unknown whether pre-stimulus theta power predictive of successful memory formation is also found in these subcortical structures. We recorded human electrophysiological data from the DMTN and ATN of 7 patients receiving deep brain stimulation for refractory epilepsy. We found that greater pre-stimulus theta power in the right DMTN was associated with successful memory encoding, predicting both behavioral outcome and post-stimulus correlates of successful memory formation. In particular, significant correlations were observed between right DMTN theta power and both frontal theta and right ATN gamma (32-50Hz) phase alignment, and frontal-ATN theta-gamma cross-frequency coupling. We draw the following primary conclusions. Our results provide direct electrophysiological evidence in humans of a role for the DMTN as well as the ATN in memory formation. Furthermore, prediction of subsequent memory performance by pre-stimulus thalamic oscillations provides evidence that post-stimulus differences in thalamic activity that index successful and unsuccessful encoding reflect brain processes specifically underpinning memory formation. Finally, the findings broaden the understanding of brain states that facilitate memory encoding to include subcortical as well as cortical structures. Copyright © 2016 Elsevier Inc. All rights reserved.

Common Prairie feeds with different soluble and insoluble fractions used for CPM diet formulation in dairy cattle: impact of carbohydrate-protein matrix structure on protein and other primary nutrient digestion.

PubMed

Peng, Quanhui; Wang, Zhisheng; Zhang, Xuewei; Yu, Peiqiang

2014-01-01

An experiment was conducted to investigate the relationship of carbohydrates molecular spectral characteristics to rumen degradability of primary nutrients in Prairie feeds in dairy cattle. In total, 12 different types of feeds were selected, each type of feed was from three different source with total 37 samples. Six types of them were energy-sourced feeds and the others were protein-sourced feeds. The carbohydrates molecular spectral intensity of various functional groups were collected using Fourier transform infrared attenuated total reflectance (ATR-FT/IR) spectroscopy. In the in situ study, the results showed that the rumen digestibility and digestible fractions of primary nutrients (DM, OM, NCP, and CP) were significantly different (P<0.05) among the feeds. The spectral bands features were significantly different (P<0.05) among the feeds. Spectral intensities of A_Cell, H_1415 and H_1370 were weakly positively correlated with in situ rumen digestibility and digestible fractions of DM, OM and NCP. Spectral intensities of H_1150, H_1015, A_1, and A_3 were weakly negatively associated with in situ rumen degradation of CP. Spectral intensities of A_1240 and H_1240, mainly associated with cellulosic compounds, were correlated with rumen CP degradation. The multiple regression analysis demonstrated that the spectral intensities of A_3 and H_1415 played the most important role and could be used as a potential tool to predict rumen protein degradation of feeds in dairy cattle. In conclusion, this study showed that the carbohydrates as a whole have an effect on protein rumen degradation, rather than cellulose alone, indicating carbohydrate-protein matrix structure impact protein utilization in dairy cattle. The non-invasive molecular spectral technique (ATR-FT/IR) could be used as a rapid potential tool to predict rumen protein degradation of feedstuffs by using molecular spectral bands intensities in carbohydrate fingerprint region. Copyright © 2013 Elsevier B.V. All rights reserved.

Common Prairie feeds with different soluble and insoluble fractions used for CPM diet formulation in dairy cattle: Impact of carbohydrate-protein matrix structure on protein and other primary nutrient digestion

NASA Astrophysics Data System (ADS)

Peng, Quanhui; Wang, Zhisheng; Zhang, Xuewei; Yu, Peiqiang

2014-03-01

An experiment was conducted to investigate the relationship of carbohydrates molecular spectral characteristics to rumen degradability of primary nutrients in Prairie feeds in dairy cattle. In total, 12 different types of feeds were selected, each type of feed was from three different source with total 37 samples. Six types of them were energy-sourced feeds and the others were protein-sourced feeds. The carbohydrates molecular spectral intensity of various functional groups were collected using Fourier transform infrared attenuated total reflectance (ATR-FT/IR) spectroscopy. In the in situ study, the results showed that the rumen digestibility and digestible fractions of primary nutrients (DM, OM, NCP, and CP) were significantly different (P < 0.05) among the feeds. The spectral bands features were significantly different (P < 0.05) among the feeds. Spectral intensities of A_Cell, H_1415 and H_1370 were weakly positively correlated with in situ rumen digestibility and digestible fractions of DM, OM and NCP. Spectral intensities of H_1150, H_1015, A_1, and A_3 were weakly negatively associated with in situ rumen degradation of CP. Spectral intensities of A_1240 and H_1240, mainly associated with cellulosic compounds, were correlated with rumen CP degradation. The multiple regression analysis demonstrated that the spectral intensities of A_3 and H_1415 played the most important role and could be used as a potential tool to predict rumen protein degradation of feeds in dairy cattle. In conclusion, this study showed that the carbohydrates as a whole have an effect on protein rumen degradation, rather than cellulose alone, indicating carbohydrate-protein matrix structure impact protein utilization in dairy cattle. The non-invasive molecular spectral technique (ATR-FT/IR) could be used as a rapid potential tool to predict rumen protein degradation of feedstuffs by using molecular spectral bands intensities in carbohydrate fingerprint region.

VICTORIA-92 pretest analyses of PHEBUS-FPT0

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bixler, N.E.; Erickson, C.M.

FPT0 is the first of six tests that are scheduled to be conducted in an experimental reactor in Cadarache, France. The test apparatus consists of an in-pile fuel bundle, an upper plenum, a hot leg, a steam generator, a cold leg, and a small containment. Thus, the test is integral in the sense that it attempts to simulate all of the processes that would be operative in a severe nuclear accident. In FPT0, the fuel will be trace irradiated; in subsequent tests high burn-up fuel will be used. This report discusses separate pretest analyses of the FPT0 fuel bundle andmore » primary circuit have been conducted using the USNRC`s source term code, VICTORIA-92. Predictions for release of fission product, control rod, and structural elements from the test section are compared with those given by CORSOR-M. In general, the releases predicted by VICTORIA-92 occur earlier than those predicted by CORSOR-M. The other notable difference is that U release is predicted to be on a par with that of the control rod elements; CORSOR-M predicts U release to be about 2 orders of magnitude greater.« less

Fluoroscopic removal of retrievable self-expandable metal stents in patients with malignant oesophageal strictures: Experience with a non-endoscopic removal system.

PubMed

Kim, Pyeong Hwa; Song, Ho-Young; Park, Jung-Hoon; Zhou, Wei-Zhong; Na, Han Kyu; Cho, Young Chul; Jun, Eun Jung; Kim, Jun Ki; Kim, Guk Bae

2017-03-01

To evaluate clinical outcomes of fluoroscopic removal of retrievable self-expandable metal stents (SEMSs) for malignant oesophageal strictures, to compare clinical outcomes of three different removal techniques, and to identify predictive factors of successful removal by the standard technique (primary technical success). A total of 137 stents were removed from 128 patients with malignant oesophageal strictures. Primary overall technical success and removal-related complications were evaluated. Logistic regression models were constructed to identify predictive factors of primary technical success. Primary technical success rate was 78.8 % (108/137). Complications occurred in six (4.4 %) cases. Stent location in the upper oesophagus (P=0.004), stricture length over 8 cm (P=0.030), and proximal granulation tissue (P<0.001) were negative predictive factors of primary technical success. If granulation tissue was present at the proximal end, eversion technique was more frequently required (P=0.002). Fluoroscopic removal of retrievable SEMSs for malignant oesophageal strictures using three different removal techniques appeared to be safe and easy. The standard technique is safe and effective in the majority of patients. The presence of proximal granulation tissue, stent location in the upper oesophagus, and stricture length over 8 cm were negative predictive factors for primary technical success by standard extraction and may require a modified removal technique. • Fluoroscopic retrievable SEMS removal is safe and effective. • Standard removal technique by traction is effective in the majority of patients. • Three negative predictive factors of primary technical success were identified. • Caution should be exercised during the removal in those situations. • Eversion technique is effective in cases of proximal granulation tissue.

Structure, function, and control of the human musculoskeletal network

PubMed Central

Murphy, Andrew C.; Muldoon, Sarah F.; Baker, David; Lastowka, Adam; Bennett, Brittany; Yang, Muzhi

2018-01-01

The human body is a complex organism, the gross mechanical properties of which are enabled by an interconnected musculoskeletal network controlled by the nervous system. The nature of musculoskeletal interconnection facilitates stability, voluntary movement, and robustness to injury. However, a fundamental understanding of this network and its control by neural systems has remained elusive. Here we address this gap in knowledge by utilizing medical databases and mathematical modeling to reveal the organizational structure, predicted function, and neural control of the musculoskeletal system. We constructed a highly simplified whole-body musculoskeletal network in which single muscles connect to multiple bones via both origin and insertion points. We demonstrated that, using this simplified model, a muscle’s role in this network could offer a theoretical prediction of the susceptibility of surrounding components to secondary injury. Finally, we illustrated that sets of muscles cluster into network communities that mimic the organization of control modules in primary motor cortex. This novel formalism for describing interactions between the muscular and skeletal systems serves as a foundation to develop and test therapeutic responses to injury, inspiring future advances in clinical treatments. PMID:29346370

Development of Testing Methodologies for the Mechanical Properties of MEMS

NASA Technical Reports Server (NTRS)

Ekwaro-Osire, Stephen

2003-01-01

This effort is to investigate and design testing strategies to determine the mechanical properties of MicroElectroMechanical Systems (MEMS) as well as investigate the development of a MEMS Probabilistic Design Methodology (PDM). One item of potential interest is the design of a test for the Weibull size effect in pressure membranes. The Weibull size effect is a consequence of a stochastic strength response predicted from the Weibull distribution. Confirming that MEMS strength is controlled by the Weibull distribution will enable the development of a probabilistic design methodology for MEMS - similar to the GRC developed CARES/Life program for bulk ceramics. However, the primary area of investigation will most likely be analysis and modeling of material interfaces for strength as well as developing a strategy to handle stress singularities at sharp corners, filets, and material interfaces. This will be a continuation of the previous years work. The ultimate objective of this effort is to further develop and verify the ability of the Ceramics Analysis and Reliability Evaluation of Structures Life (CARES/Life) code to predict the time-dependent reliability of MEMS structures subjected to multiple transient loads.

Longitudinal assessment of psychopathological domains over late-stage schizophrenia in relation to duration of initially untreated psychosis: 3-year prospective study in a long-term inpatient population.

PubMed

Meagher, David J; Quinn, John F; Bourke, Stephanie; Linehan, Sally; Murphy, Patrice; Kinsella, Anthony; Mullaney, James; Waddington, John L

2004-05-30

There remains uncertainty regarding any progressive nature of psychopathology and cognitive dysfunction in late-stage schizophrenia, and whether duration of initially untreated psychosis (DUP) might be associated with such 'progression'. This study examines longitudinally, over 3 years, the psychopathology and neuropsychology in 82 inpatients with DSM-IV schizophrenia, many of whom were admitted in the pre-neuroleptic era. Increase in executive dysfunction exceeded that in general cognitive impairment. Positive but not negative symptom severity decreased modestly; the primary predictor of negative symptom severity was DUP. On index assessment, psychopathology evidenced a three-factor structure; at follow-up, psychomotor poverty evidenced greater prominence and cohesion, and was on both occasions predicted primarily by DUP, while reality distortion was altered and disorganisation disassembled into alternative elements. It would appear that as years of chronic, refractory illness accrue, psychomotor poverty becomes more sharply delineated and dominant within the overall structure of psychopathology, and its prominence is predicted enduringly by DUP. Copyright 2004 Elsevier Ireland Ltd.

Assessing the effects of management on forest growth across France: insights from a new functional-structural model.

PubMed

Guillemot, Joannès; Delpierre, Nicolas; Vallet, Patrick; François, Christophe; Martin-StPaul, Nicolas K; Soudani, Kamel; Nicolas, Manuel; Badeau, Vincent; Dufrêne, Eric

2014-09-01

The structure of a forest stand, i.e. the distribution of tree size features, has strong effects on its functioning. The management of the structure is therefore an important tool in mitigating the impact of predicted changes in climate on forests, especially with respect to drought. Here, a new functional-structural model is presented and is used to assess the effects of management on forest functioning at a national scale. The stand process-based model (PBM) CASTANEA was coupled to a stand structure module (SSM) based on empirical tree-to-tree competition rules. The calibration of the SSM was based on a thorough analysis of intersite and interannual variability of competition asymmetry. The coupled CASTANEA-SSM model was evaluated across France using forest inventory data, and used to compare the effect of contrasted silvicultural practices on simulated stand carbon fluxes and growth. The asymmetry of competition varied consistently with stand productivity at both spatial and temporal scales. The modelling of the competition rules enabled efficient prediction of changes in stand structure within the CASTANEA PBM. The coupled model predicted an increase in net primary productivity (NPP) with management intensity, resulting in higher growth. This positive effect of management was found to vary at a national scale across France: the highest increases in NPP were attained in forests facing moderate to high water stress; however, the absolute effect of management on simulated stand growth remained moderate to low because stand thinning involved changes in carbon allocation at the tree scale. This modelling approach helps to identify the areas where management efforts should be concentrated in order to mitigate near-future drought impact on national forest productivity. Around a quarter of the French temperate oak and beech forests are currently in zones of high vulnerability, where management could thus mitigate the influence of climate change on forest yield.

DATA ASSIMILATION APPROACH FOR FORECAST OF SOLAR ACTIVITY CYCLES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kitiashvili, Irina N., E-mail: irina.n.kitiashvili@nasa.gov

Numerous attempts to predict future solar cycles are mostly based on empirical relations derived from observations of previous cycles, and they yield a wide range of predicted strengths and durations of the cycles. Results obtained with current dynamo models also deviate strongly from each other, thus raising questions about criteria to quantify the reliability of such predictions. The primary difficulties in modeling future solar activity are shortcomings of both the dynamo models and observations that do not allow us to determine the current and past states of the global solar magnetic structure and its dynamics. Data assimilation is a relativelymore » new approach to develop physics-based predictions and estimate their uncertainties in situations where the physical properties of a system are not well-known. This paper presents an application of the ensemble Kalman filter method for modeling and prediction of solar cycles through use of a low-order nonlinear dynamo model that includes the essential physics and can describe general properties of the sunspot cycles. Despite the simplicity of this model, the data assimilation approach provides reasonable estimates for the strengths of future solar cycles. In particular, the prediction of Cycle 24 calculated and published in 2008 is so far holding up quite well. In this paper, I will present my first attempt to predict Cycle 25 using the data assimilation approach, and discuss the uncertainties of that prediction.« less

Deposition and reentrainment of Brownian particles in porous media under unfavorable chemical conditions: some concepts and applications.

PubMed

Hahn, Melinda W; O'Meliae, Charles R

2004-01-01

The deposition and reentrainment of particles in porous media have been examined theoretically and experimentally. A Brownian Dynamics/Monte Carlo (MC/BD) model has been developed that simulates the movement of Brownian particles near a collector under "unfavorable" chemical conditions and allows deposition in primary and secondary minima. A simple Maxwell approach has been used to estimate particle attachment efficiency by assuming deposition in the secondary minimum and calculating the probability of reentrainment. The MC/BD simulations and the Maxwell calculations support an alternative view of the deposition and reentrainment of Brownian particles under unfavorable chemical conditions. These calculations indicate that deposition into and subsequent release from secondary minima can explain reported discrepancies between classic model predictions that assume irreversible deposition in a primary well and experimentally determined deposition efficiencies that are orders of magnitude larger than Interaction Force Boundary Layer (IFBL) predictions. The commonly used IFBL model, for example, is based on the notion of transport over an energy barrier into the primary well and does not address contributions of secondary minimum deposition. A simple Maxwell model based on deposition into and reentrainment from secondary minima is much more accurate in predicting deposition rates for column experiments at low ionic strengths. It also greatly reduces the substantial particle size effects inherent in IFBL models, wherein particle attachment rates are predicted to decrease significantly with increasing particle size. This view is consistent with recent work by others addressing the composition and structure of the first few nanometers at solid-water interfaces including research on modeling water at solid-liquid interfaces, surface speciation, interfacial force measurements, and the rheological properties of concentrated suspensions. It follows that deposition under these conditions will depend on the depth of the secondary minimum and that some transition between secondary and primary depositions should occur when the height of the energy barrier is on the order of several kT. When deposition in secondary minima predominates, observed deposition should increase with increasing ionic strength, particle size, and Hamaker constant. Since an equilibrium can develop between bound and bulk particles, the collision efficiency [alpha] can no longer be considered a constant for a given physical and chemical system. Rather, in many cases it can decrease over time until it eventually reaches zero as equilibrium is established.

Novel cis-acting element within the capsid-coding region enhances flavivirus viral-RNA replication by regulating genome cyclization.

PubMed

Liu, Zhong-Yu; Li, Xiao-Feng; Jiang, Tao; Deng, Yong-Qiang; Zhao, Hui; Wang, Hong-Jiang; Ye, Qing; Zhu, Shun-Ya; Qiu, Yang; Zhou, Xi; Qin, E-De; Qin, Cheng-Feng

2013-06-01

cis-Acting elements in the viral genome RNA (vRNA) are essential for the translation, replication, and/or encapsidation of RNA viruses. In this study, a novel conserved cis-acting element was identified in the capsid-coding region of mosquito-borne flavivirus. The downstream of 5' cyclization sequence (5'CS) pseudoknot (DCS-PK) element has a three-stem pseudoknot structure, as demonstrated by structure prediction and biochemical analysis. Using dengue virus as a model, we show that DCS-PK enhances vRNA replication and that its function depends on its secondary structure and specific primary sequence. Mutagenesis revealed that the highly conserved stem 1 and loop 2, which are involved in potential loop-helix interactions, are crucial for DCS-PK function. A predicted loop 1-stem 3 base triple interaction is important for the structural stability and function of DCS-PK. Moreover, the function of DCS-PK depends on its position relative to the 5'CS, and the presence of DCS-PK facilitates the formation of 5'-3' RNA complexes. Taken together, our results reveal that the cis-acting element DCS-PK enhances vRNA replication by regulating genome cyclization, and DCS-PK might interplay with other cis-acting elements to form a functional vRNA cyclization domain, thus playing critical roles during the flavivirus life cycle and evolution.

Novel cis-Acting Element within the Capsid-Coding Region Enhances Flavivirus Viral-RNA Replication by Regulating Genome Cyclization

PubMed Central

Liu, Zhong-Yu; Li, Xiao-Feng; Jiang, Tao; Deng, Yong-Qiang; Zhao, Hui; Wang, Hong-Jiang; Ye, Qing; Zhu, Shun-Ya; Qiu, Yang; Zhou, Xi; Qin, E-De

2013-01-01

cis-Acting elements in the viral genome RNA (vRNA) are essential for the translation, replication, and/or encapsidation of RNA viruses. In this study, a novel conserved cis-acting element was identified in the capsid-coding region of mosquito-borne flavivirus. The downstream of 5′ cyclization sequence (5′CS) pseudoknot (DCS-PK) element has a three-stem pseudoknot structure, as demonstrated by structure prediction and biochemical analysis. Using dengue virus as a model, we show that DCS-PK enhances vRNA replication and that its function depends on its secondary structure and specific primary sequence. Mutagenesis revealed that the highly conserved stem 1 and loop 2, which are involved in potential loop-helix interactions, are crucial for DCS-PK function. A predicted loop 1-stem 3 base triple interaction is important for the structural stability and function of DCS-PK. Moreover, the function of DCS-PK depends on its position relative to the 5′CS, and the presence of DCS-PK facilitates the formation of 5′-3′ RNA complexes. Taken together, our results reveal that the cis-acting element DCS-PK enhances vRNA replication by regulating genome cyclization, and DCS-PK might interplay with other cis-acting elements to form a functional vRNA cyclization domain, thus playing critical roles during the flavivirus life cycle and evolution. PMID:23576500

Computational analysis of EBNA1 ``druggability'' suggests novel insights for Epstein-Barr virus inhibitor design

NASA Astrophysics Data System (ADS)

Gianti, Eleonora; Messick, Troy E.; Lieberman, Paul M.; Zauhar, Randy J.

2016-04-01

The Epstein-Barr Nuclear Antigen 1 (EBNA1) is a critical protein encoded by the Epstein-Barr Virus (EBV). During latent infection, EBNA1 is essential for DNA replication and transcription initiation of viral and cellular genes and is necessary to immortalize primary B-lymphocytes. Nonetheless, the concept of EBNA1 as drug target is novel. Two EBNA1 crystal structures are publicly available and the first small-molecule EBNA1 inhibitors were recently discovered. However, no systematic studies have been reported on the structural details of EBNA1 "druggable" binding sites. We conducted computational identification and structural characterization of EBNA1 binding pockets, likely to accommodate ligand molecules (i.e. "druggable" binding sites). Then, we validated our predictions by docking against a set of compounds previously tested in vitro for EBNA1 inhibition (PubChem AID-2381). Finally, we supported assessments of pocket druggability by performing induced fit docking and molecular dynamics simulations paired with binding affinity predictions by Molecular Mechanics Generalized Born Surface Area calculations for a number of hits belonging to druggable binding sites. Our results establish EBNA1 as a target for drug discovery, and provide the computational evidence that active AID-2381 hits disrupt EBNA1:DNA binding upon interacting at individual sites. Lastly, structural properties of top scoring hits are proposed to support the rational design of the next generation of EBNA1 inhibitors.

A structural equation model analysis of phosphorus transformations in global unfertilized and uncultivated soils

NASA Astrophysics Data System (ADS)

Hou, Enqing; Chen, Chengrong; Kuang, Yuanwen; Zhang, Yuguang; Heenan, Marijke; Wen, Dazhi

2016-09-01

Understanding the soil phosphorus (P) cycle is a prerequisite for predicting how environmental changes may influence the dynamics and availability of P in soil. We compiled a database of P fractions sequentially extracted by the Hedley procedure and its modification in 626 unfertilized and uncultivated soils worldwide. With this database, we applied structural equation modeling to test hypothetical soil P transformation models and to quantify the importance of different soil P pools and P transformation pathways in shaping soil P availability at a global scale. Our models revealed that soluble inorganic P (Pi, a readily available P pool) was positively and directly influenced by labile Pi, labile organic P (Po), and primary mineral P and negatively and directly influenced by secondary mineral P; soluble Pi was not directly influenced by moderately labile Po or occluded P. The overall effect on soluble Pi was greatest for labile Pi followed by the organic P pools, occluded P, and then primary mineral P; the overall influence from secondary mineral P was small. Labile Pi was directly linked to all other soil P pools and was more strongly linked than soluble Pi to labile Po and primary mineral P. Our study highlights the important roles of labile Pi in mediating P transformations and in determining overall P availability in soils throughout the world.

Organic particulate matter formation at varying relative humidity using surrogate secondary and primary organic compounds with activity corrections in the condensed phase obtained using a method based on the Wilson equation

NASA Astrophysics Data System (ADS)

Chang, E. I.; Pankow, J. F.

2010-06-01

Secondary organic aerosol (SOA) formation in the atmosphere is currently often modeled using a multiple lumped "two-product" (N·2p) approach. The N·2p approach neglects: 1) variation of activity coefficient (ζi) values and mean molecular weight MW in the particulate matter (PM) phase; 2) water uptake into the PM; and 3) the possibility of phase separation in the PM. This study considers these effects by adopting an (N·2p)ζpMW,ζ approach (θ is a phase index). Specific chemical structures are assigned to 25 lumped SOA compounds and to 15 representative primary organic aerosol (POA) compounds to allow calculation of ζi and MW values. The SOA structure assignments are based on chamber-derived 2p gas/particle partition coefficient values coupled with known effects of structure on vapor pressure pL,io (atm). To facilitate adoption of the (N·2p)ζpMW,θ approach in large-scale models, this study also develops CP-Wilson.1 (Chang-Pankow-Wilson.1), a group-contribution ζi-prediction method that is more computationally economical than the UNIFAC model of Fredenslund et al. (1975). Group parameter values required by CP-Wilson.1 are obtained by fitting ζi values to predictions from UNIFAC. The (N·2p)ζpMW,θ approach is applied (using CP-Wilson.1) to several real α-pinene/O3 chamber cases for high reacted hydrocarbon levels (ΔHC≈400 to 1000 μg m-3) when relative humidity (RH) ≍50%. Good agreement between the chamber and predicted results is obtained using both the (N·2p)ζpMW,θ and N·2p approaches, indicating relatively small water effects under these conditions. However, for a hypothetical α-pinene/O3 case at ΔHC=30 μg m-3 and RH=50%, the (N·2p)ζpMW,θ approach predicts that water uptake will lead to an organic PM level that is more double that predicted by the N·2p approach. Adoption of the (N·2p)ζpMW,θ approach using reasonable lumped structures for SOA and POA compounds is recommended for ambient PM modeling.

Functional genomics of gam56: characterisation of the role of a 56 kilodalton sexual stage antigen in oocyst wall formation in Eimeria maxima.

PubMed

Belli, Sabina I; Witcombe, David; Wallach, Michael G; Smith, Nicholas C

2002-12-19

Gam56 (M(r) 56,000) is an antigen found in the sexual (macrogametocyte) stage of the intestinal parasite Eimeria maxima that is implicated in protective immunity. The gene (gam56) encoding this protein was cloned and sequenced. It is a single-copy, intronless gene, that localises to a 1,754 bp transcript, and is first detected at 120 h p.i. The gene predicts two distinct protein domains; a tyrosine-serine rich region, composed of amino acids implicated in oocyst wall formation in Eimeria spp., and a proline-methionine rich region often detected in extensins, protein components of plant cell walls. The tyrosine-serine rich region predicts a secondary structure commonly seen in the structural protein fibroin, a component of the cocoon of the caterpillar Bombyx mori. The inference that gam56 is a structural component of the oocyst wall was confirmed when a specific antibody to gam56 recognised the wall forming bodies in macrogametocytes, and the walls of oocysts and sporocysts. Together, these data identify a developmentally regulated, sexual stage gene in E. maxima that shares primary and secondary structure features in common with intrinsic structural proteins in other parasites such as Schistosoma mansoni and Fasciola hepatica, and other organisms across different phyla, including the caterpillar Bombyx mori. In addition, these findings provide evidence for the molecular mechanisms underlying oocyst wall formation in Eimeria and the role of gametocyte antigens in this process.

Advanced Earth-to-orbit propulsion technology program overview: Impact of civil space technology initiative

NASA Technical Reports Server (NTRS)

Stephenson, Frank W., Jr.

1988-01-01

The NASA Earth-to-Orbit (ETO) Propulsion Technology Program is dedicated to advancing rocket engine technologies for the development of fully reusable engine systems that will enable space transportation systems to achieve low cost, routine access to space. The program addresses technology advancements in the areas of engine life extension/prediction, performance enhancements, reduced ground operations costs, and in-flight fault tolerant engine operations. The primary objective is to acquire increased knowledge and understanding of rocket engine chemical and physical processes in order to evolve more realistic analytical simulations of engine internal environments, to derive more accurate predictions of steady and unsteady loads, and using improved structural analyses, to more accurately predict component life and performance, and finally to identify and verify more durable advanced design concepts. In addition, efforts were focused on engine diagnostic needs and advances that would allow integrated health monitoring systems to be developed for enhanced maintainability, automated servicing, inspection, and checkout, and ultimately, in-flight fault tolerant engine operations.

Improving sexual health communication between older women and their providers: how the integrative model of behavioral prediction can help.

PubMed

Hughes, Anne K; Rostant, Ola S; Curran, Paul G

2014-07-01

Talking about sexual health can be a challenge for some older women. This project was initiated to identify key factors that improve communication between aging women and their primary care providers. A sample of women (aged 60+) completed an online survey regarding their intent to communicate with a provider about sexual health. Using the integrative model of behavioral prediction as a guide, the survey instrument captured data on attitudes, perceived norms, self-efficacy, and intent to communicate with a provider about sexual health. Data were analyzed using structural equation modeling. Self-efficacy and perceived norms were the most important factors predicting intent to communicate for this sample of women. Intent did not vary with race, but mean scores of the predictors of intent varied for African American and White women. Results can guide practice and intervention with ethnically diverse older women who may be struggling to communicate about their sexual health concerns. © The Author(s) 2013.

Assessment of Lightning Transients on a De-Iced Rotor Blade with Predictive Tools and Coaxial Return Measurements

NASA Astrophysics Data System (ADS)

Guillet, S.; Gosmain, A.; Ducoux, W.; Ponçon, M.; Fontaine, G.; Desseix, P.; Perraud, P.

2012-05-01

The increasing use of composite materials in aircrafts primary structures has led to different problematics in the field of safety of flight in lightning conditions. The consequences of this technological mutation, which occurs in a parallel context of extension of electrified critical functions, are addressed by aircraft manufacturers through the enhancement of their available assessment means of lightning transient. On the one hand, simulation tools, provided an accurate description of aircraft design, are today valuable assessment tools, in both predictive and operative terms. On the other hand, in-house test means allow confirmation and consolidation of design office hardening solutions. The combined use of predictive simulation tools and in- house test means offers an efficient and reliable support for all aircraft developments in their various life-time stages. The present paper provides PREFACE research project results that illustrate the above introduced strategy on the de-icing system of the NH90 composite main rotor blade.

Predicting Organizational Commitment from Organizational Culture in Turkish Primary Schools

ERIC Educational Resources Information Center

Ipek, Cemalettin

2010-01-01

This study aims to describe organizational culture and commitment and to predict organizational commitment from organizational culture in Turkish primary schools. Organizational Culture Scale (Ipek "1999") and Organizational Commitment Scale (Balay "2000") were used in the data gathering process. The data were collected from…

Evolution of nanoscale zero-valent iron (nZVI) in water: Microscopic and spectroscopic evidence on the formation of nano- and micro-structured iron oxides.

PubMed

Liu, Airong; Liu, Jing; Han, Jinhao; Zhang, Wei-Xian

2017-01-15

Knowledge on the transformation of nanoscale zero-valent iron (nZVI) in water is essential to predict its surface chemistry including surface charge, colloidal stability and aggregation, reduction and sorption of organic contaminants, heavy metal ions and other pollutants in the environment. In this work, transmission electronic microscopy (TEM), X-ray diffraction (XRD) and Raman spectroscopy are applied to study the compositional and structural evolution of nZVI under oxic and anoxic conditions. Under anoxic conditions, the core-shell structure of nZVI is well maintained even after 72h, and the corrosion products usually contain a mixture of wustite (FeO), goethite (α-FeOOH) and akaganeite (β-FeOOH). Under oxic conditions, the core-shell structure quickly collapses to flakes or acicular-shaped structures with crystalline lepidocrocite (γ-FeOOH) as the primary end product. This work provides detailed information and fills an important knowledge gap on the physicochemical characteristics and structural evolution of engineered nanomaterials in the environment. Copyright © 2015 Elsevier B.V. All rights reserved.

A Thermoacidophile-Specific Protein Family, DUF3211, Functions as a Fatty Acid Carrier with Novel Binding Mode

PubMed Central

Miyakawa, Takuya; Sawano, Yoriko; Miyazono, Ken-ichi; Miyauchi, Yumiko; Hatano, Ken-ichi

2013-01-01

STK_08120 is a member of the thermoacidophile-specific DUF3211 protein family from Sulfolobus tokodaii strain 7. Its molecular function remains obscure, and sequence similarities for obtaining functional remarks are not available. In this study, the crystal structure of STK_08120 was determined at 1.79-Å resolution to predict its probable function using structure similarity searches. The structure adopts an α/β structure of a helix-grip fold, which is found in the START domain proteins with cavities for hydrophobic substrates or ligands. The detailed structural features implied that fatty acids are the primary ligand candidates for STK_08120, and binding assays revealed that the protein bound long-chain saturated fatty acids (>C14) and their trans-unsaturated types with an affinity equal to that for major fatty acid binding proteins in mammals and plants. Moreover, the structure of an STK_08120-myristic acid complex revealed a unique binding mode among fatty acid binding proteins. These results suggest that the thermoacidophile-specific protein family DUF3211 functions as a fatty acid carrier with a novel binding mode. PMID:23836863

Proton channel models

PubMed Central

Pupo, Amaury; Baez-Nieto, David; Martínez, Agustín; Latorre, Ramón; González, Carlos

2014-01-01

Voltage-gated proton channels are integral membrane proteins with the capacity to permeate elementary particles in a voltage and pH dependent manner. These proteins have been found in several species and are involved in various physiological processes. Although their primary topology is known, lack of details regarding their structures in the open conformation has limited analyses toward a deeper understanding of the molecular determinants of their function and regulation. Consequently, the function-structure relationships have been inferred based on homology models. In the present work, we review the existing proton channel models, their assumptions, predictions and the experimental facts that support them. Modeling proton channels is not a trivial task due to the lack of a close homolog template. Hence, there are important differences between published models. This work attempts to critically review existing proton channel models toward the aim of contributing to a better understanding of the structural features of these proteins. PMID:24755912

Unjamming and cell shape in the asthmatic airway epithelium

NASA Astrophysics Data System (ADS)

Park, Jin-Ah; Kim, Jae Hun; Bi, Dapeng; Mitchel, Jennifer A.; Qazvini, Nader Taheri; Tantisira, Kelan; Park, Chan Young; McGill, Maureen; Kim, Sae-Hoon; Gweon, Bomi; Notbohm, Jacob; Steward, Robert, Jr.; Burger, Stephanie; Randell, Scott H.; Kho, Alvin T.; Tambe, Dhananjay T.; Hardin, Corey; Shore, Stephanie A.; Israel, Elliot; Weitz, David A.; Tschumperlin, Daniel J.; Henske, Elizabeth P.; Weiss, Scott T.; Manning, M. Lisa; Butler, James P.; Drazen, Jeffrey M.; Fredberg, Jeffrey J.

2015-10-01

From coffee beans flowing in a chute to cells remodelling in a living tissue, a wide variety of close-packed collective systems--both inert and living--have the potential to jam. The collective can sometimes flow like a fluid or jam and rigidify like a solid. The unjammed-to-jammed transition remains poorly understood, however, and structural properties characterizing these phases remain unknown. Using primary human bronchial epithelial cells, we show that the jamming transition in asthma is linked to cell shape, thus establishing in that system a structural criterion for cell jamming. Surprisingly, the collapse of critical scaling predicts a counter-intuitive relationship between jamming, cell shape and cell-cell adhesive stresses that is borne out by direct experimental observations. Cell shape thus provides a rigorous structural signature for classification and investigation of bronchial epithelial layer jamming in asthma, and potentially in any process in disease or development in which epithelial dynamics play a prominent role.

3D CAFE modeling of grain structures: application to primary dendritic and secondary eutectic solidification

NASA Astrophysics Data System (ADS)

Carozzani, T.; Digonnet, H.; Gandin, Ch-A.

2012-01-01

A three-dimensional model is presented for the prediction of grain structures formed in casting. It is based on direct tracking of grain boundaries using a cellular automaton (CA) method. The model is fully coupled with a solution of the heat flow computed with a finite element (FE) method. Several unique capabilities are implemented including (i) the possibility to track the development of several types of grain structures, e.g. dendritic and eutectic grains, (ii) a coupling scheme that permits iterations between the FE method and the CA method, and (iii) tabulated enthalpy curves for the solid and liquid phases that offer the possibility to work with multicomponent alloys. The present CAFE model is also fully parallelized and runs on a cluster of computers. Demonstration is provided by direct comparison between simulated and recorded cooling curves for a directionally solidified aluminum-7 wt% silicon alloy.

Design of a composite wing extension for a general aviation aircraft

NASA Technical Reports Server (NTRS)

Adney, P. S.; Horn, W. J.

1984-01-01

A composite wing extension was designed for a typical general aviation aircraft to improve lift curve slope, dihedral effect, and lift to drag ratio. Advanced composite materials were used in the design to evaluate their use as primary structural components in general aviation aircraft. Extensive wind tunnel tests were used to evaluate six extension shapes. The extension shape chosen as the best choice was 28 inches long with a total area of 17 square feet. Subsequent flight tests showed the wing extension's predicted aerodynamic improvements to be correct. The structural design of the wing extension consisted of a hybrid laminate carbon core with outer layers of Kevlar - layed up over a foam interior which acted as an internal support. The laminate skin of the wing extension was designed from strength requirements, and the foam core was included to prevent buckling. A joint lap was recommended to attach the wing extension to the main wing structure.

Urban habitat fragmentation and genetic population structure of bobcats in coastal southern California

USGS Publications Warehouse

Ruell, E.W.; Riley, S.P.D.; Douglas, M.R.; Antolin, M.F.; Pollinger, J.R.; Tracey, J.A.; Lyren, L.M.; Boydston, E.E.; Fisher, R.N.; Crooks, K.R.

2012-01-01

Although habitat fragmentation is recognized as a primary threat to biodiversity, the effects of urban development on genetic population structure vary among species and landscapes and are not yet well understood. Here we use non-invasive genetic sampling to compare the effects of fragmentation by major roads and urban development on levels of dispersal, genetic diversity, and relatedness between paired bobcat populations in replicate landscapes in coastal southern California. We hypothesized that bobcat populations in sites surrounded by urbanization would experience reduced functional connectivity relative to less isolated nearby populations. Our results show that bobcat genetic population structure is affected by roads and development but not always as predicted by the degree that these landscape features surround fragments. Instead, we suggest that urban development may affect functional connectivity between bobcat populations more by limiting the number and genetic diversity of source populations of migrants than by creating impermeable barriers to dispersal.

Predicting the onset of hazardous alcohol drinking in primary care: development and validation of a simple risk algorithm

PubMed Central

Bellón, Juan Ángel; de Dios Luna, Juan; King, Michael; Nazareth, Irwin; Motrico, Emma; GildeGómez-Barragán, María Josefa; Torres-González, Francisco; Montón-Franco, Carmen; Sánchez-Celaya, Marta; Díaz-Barreiros, Miguel Ángel; Vicens, Catalina; Moreno-Peral, Patricia

2017-01-01

Background Little is known about the risk of progressing to hazardous alcohol use in abstinent or low-risk drinkers. Aim To develop and validate a simple brief risk algorithm for the onset of hazardous alcohol drinking (HAD) over 12 months for use in primary care. Design and setting Prospective cohort study in 32 health centres from six Spanish provinces, with evaluations at baseline, 6 months, and 12 months. Method Forty-one risk factors were measured and multilevel logistic regression and inverse probability weighting were used to build the risk algorithm. The outcome was new occurrence of HAD during the study, as measured by the AUDIT. Results From the lists of 174 GPs, 3954 adult abstinent or low-risk drinkers were recruited. The ‘predictAL-10’ risk algorithm included just nine variables (10 questions): province, sex, age, cigarette consumption, perception of financial strain, having ever received treatment for an alcohol problem, childhood sexual abuse, AUDIT-C, and interaction AUDIT-C*Age. The c-index was 0.886 (95% CI = 0.854 to 0.918). The optimal cutoff had a sensitivity of 0.83 and specificity of 0.80. Excluding childhood sexual abuse from the model (the ‘predictAL-9’), the c-index was 0.880 (95% CI = 0.847 to 0.913), sensitivity 0.79, and specificity 0.81. There was no statistically significant difference between the c-indexes of predictAL-10 and predictAL-9. Conclusion The predictAL-10/9 is a simple and internally valid risk algorithm to predict the onset of hazardous alcohol drinking over 12 months in primary care attendees; it is a brief tool that is potentially useful for primary prevention of hazardous alcohol drinking. PMID:28360074

Vegetation turnover and nitrogen feedback drive temperate forest carbon sequestration in response to elevated CO[2]. A multi-model structural analysis

NASA Astrophysics Data System (ADS)

Walker, A. P.; Zaehle, S.; Medlyn, B. E.; De Kauwe, M. G.; Asao, S.; Hickler, T.; Lomas, M. R.; Pak, B. C.; Parton, W. J.; Quegan, S.; Ricciuto, D. M.; Wang, Y.; Warlind, D.; Norby, R. J.

2013-12-01

Predicting forest carbon (C) sequestration requires understanding the processes leading to rates of biomass C accrual (net primary productivity; NPP) and loss (turnover). In temperate forest ecosystems, experiments and models have shown that feedback via progressive nitrogen limitation (PNL) is a key driver of NPP responses to elevated CO[2]. In this analysis we show that while still important, PNL may not be as severe a constraint on NPP as indicated by some studies and that the response of turnover to elevated CO[2] could be as important, especially in the near to medium term. Seven terrestrial ecosystem and biosphere models that couple C and N cycles with varying assumptions and complexity were used to simulate responses over 300 years to a step change in CO[2] to 550 ppmv. Simulations were run for the evergreen needleleaf Duke forest and the deciduous broadleaf Oak Ridge forest FACE experiments. Whether or not a model simulated PNL under elevated CO[2] depended on model structure and the timescale of observation. Avoiding PNL depended on mechanisms that reduced ecosystem N losses. The two key assumptions that reduced N losses were whether plant N uptake was based on plant N demand and whether ecosystem N losses (volatisation and leaching) were dependent on the concentration of N in the soil solution. Assumptions on allocation and turnover resulted in very different responses of turnover to elevated CO[2], which had profound implications for C sequestration. For example, at equilibrium CABLE2.0 predicted an increase in vegetation C sequestration despite decreased NPP, while O-CN predicted much less vegetation C sequestration than would be expected from predicted NPP increases alone. Generally elevated CO[2] favoured a shift in C partitioning towards longer lived wood biomass, which increased vegetation turnover and enhanced C sequestration. Enhanced wood partitioning was overlaid by increases or decreases in self-thinning depended on whether self-thinning was simply a function of forest structure, or structure and NPP. Self-thinning assumptions altered equilibrium C sequestration and were extremely important for the immediate transient response and near-term prediction of C sequestration.

Elephants, fire, and frost can determine community structure and composition in Kalahari Woodlands.

PubMed

Holdo, Ricardo M

2007-03-01

Fire, elephants, and frost are important disturbance factors in many African savannas, but the relative magnitude of their effects on vegetation and their interactions have not been quantified. Understanding how disturbance shapes savanna structure and composition is critical for predicting changes in tree cover and for formulating management and conservation policy. A simulation model was used to investigate how the disturbance regime determines vegetation structure and composition in a mixed Kalahari sand woodland savanna in western Zimbabwe. The model consisted of submodels for tree growth, tree damage caused by disturbance, mortality, and recruitment that were parameterized from field data collected over a two-year period. The model predicts that, under the current disturbance regime, tree basal area in the study area will decline by two-thirds over the next two decades and become dominated by species unpalatable to elephants. Changes in the disturbance regime are predicted to greatly modify vegetation structure and community composition. Elephants are the primary drivers of woodland change in this community at present-day population densities, and their impacts are exacerbated by the effects of fire and frost. Frost, in particular, does not play an important role when acting independently but appears to be a key secondary factor in the presence of elephants and/or fire. Unlike fire and frost, which cannot suppress the woodland phase on their own in this ecosystem, elephants can independently drive the vegetation to the scrub phase. The results suggest that elephant and fire management may be critical for the persistence of certain woodland communities within dry-season elephant habitats in the eastern Kalahari, particularly those dominated by Brachystegia spiciformis and other palatable species.

Orbitofrontal volumes in early adolescence predict initiation of cannabis use: a 4-year longitudinal and prospective study.

PubMed

Cheetham, Ali; Allen, Nicholas B; Whittle, Sarah; Simmons, Julian G; Yücel, Murat; Lubman, Dan I

2012-04-15

There is growing evidence that long-term, heavy cannabis use is associated with alterations in regional brain volumes. Although these changes are frequently attributed to the neurotoxic effects of cannabis, it is possible that some abnormalities might predate use and represent markers of vulnerability. To date, no studies have examined whether structural brain abnormalities are present before the onset of cannabis use. This study aims to determine whether adolescents who have initiated cannabis use early (i.e., before age 17 years) show premorbid structural abnormalities in the amygdala, hippocampus, orbitofrontal cortex, and anterior cingulate cortex. Participants (n = 121) were recruited from primary schools in Melbourne, Australia, as part of a larger study examining adolescent emotional development. Participants underwent structural magnetic resonance imaging at age 12 years and were assessed for cannabis use 4 years later, at age 16 years. At the follow-up assessment, 28 participants had commenced using cannabis (16 female subjects [57%]), and 93 had not (43 female subjects [46%]). Smaller orbitofrontal cortex volumes at age 12 years predicted initiation of cannabis use by age 16 years. The volumes of other regions (amygdala, hippocampus, and anterior cingulate cortex) did not predict later cannabis use. These findings suggest that structural abnormalities in the orbitofrontal cortex might contribute to risk for cannabis exposure. Although the results have important implications for understanding neurobiological predictors of cannabis use, further research is needed to understand their relationship with heavier patterns of use in adulthood as well as later abuse of other substances. Copyright © 2012 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

A simple web-based risk calculator (www.anastomoticleak.com) is superior to the surgeon's estimate of anastomotic leak after colon cancer resection.

PubMed

Sammour, T; Lewis, M; Thomas, M L; Lawrence, M J; Hunter, A; Moore, J W

2017-01-01

Anastomotic leak can be a devastating complication, and early prediction is difficult. The aim of this study is to prospectively validate a simple anastomotic leak risk calculator and compare its predictive value with the estimate of the primary operating surgeon. Consecutive patients undergoing elective or emergency colon cancer surgery with a primary anastomosis over a 1-year period were prospectively included. A recently published anastomotic leak risk nomogram was converted to an online calculator ( www.anastomoticleak.com ). The calculator-derived risk of anastomotic leak and the risk estimated by the primary operating surgeon were recorded at the completion of surgery. The primary outcome was anastomotic leak within 90 days as defined by previously published criteria. Area under receiver operating characteristic curve analysis (AUROC) was performed for both risk estimates. A total of 105 patients were screened for inclusion during the study period, of whom 83 met the inclusion criteria. The overall anastomotic leak rate was 9.6%. The anastomotic leak calculator was highly predictive of anastomotic leak (AUROC 0.84, P = 0.002), whereas the surgeon estimate was not predictive (AUROC 0.40, P = 0.243). A simple anastomotic leak risk calculator is significantly better at predicting anastomotic leak than the estimate of the primary surgeon. Further external validation on a larger data set is required.

Membrane expression of MRP-1, but not MRP-1 splicing or Pgp expression, predicts survival in patients with ESFT.

PubMed

Roundhill, E; Burchill, S

2013-07-09

Primary Ewing's sarcoma family of tumours (ESFTs) may respond to chemotherapy, although many patients experience subsequent disease recurrence and relapse. The survival of ESFT cells following chemotherapy has been attributed to the development of resistant disease, possibly through the expression of ABC transporter proteins. MRP-1 and Pgp mRNA and protein expression in primary ESFTs was determined by quantitative reverse-transcriptase PCR (RT-qPCR) and immunohistochemistry, respectively, and alternative splicing of MRP-1 by RT-PCR. We observed MRP-1 protein expression in 92% (43 out of 47) of primary ESFTs, and cell membrane MRP-1 was highly predictive of both overall survival (P<0.0001) and event-free survival (P<0.0001). Alternative splicing of MRP-1 was detected in primary ESFTs, although the pattern of splicing variants was not predictive of patient outcome, with the exception of loss of exon 9 in six patients, which predicted relapse (P=0.041). Pgp protein was detected in 6% (38 out of 44) of primary ESFTs and was not associated with patient survival. For the first time we have established that cell membrane expression of MRP-1 or loss of exon 9 is predictive of outcome but not the number of splicing events or expression of Pgp, and both may be valuable factors for the stratification of patients for more intensive therapy.

Human alpha2-macroglobulin is composed of multiple domains, as predicted by homology with complement component C3.

PubMed

Doan, Ninh; Gettins, Peter G W

2007-10-01

Human alpha2M (alpha2-macroglobulin) and the complement components C3 and C4 are thiol ester-containing proteins that evolved from the same ancestral gene. The recent structure determination of human C3 has allowed a detailed prediction of the location of domains within human alpha2M to be made. We describe here the expression and characterization of three alpha(2)M domains predicted to be involved in the stabilization of the thiol ester in native alpha2M and in its activation upon bait region proteolysis. The three newly expressed domains are MG2 (macroglobulin domain 2), TED (thiol ester-containing domain) and CUB (complement protein subcomponents C1r/C1s, urchin embryonic growth factor and bone morphogenetic protein 1) domain. Together with the previously characterized RBD (receptor-binding domain), they represent approx. 42% of the alpha2M polypeptide. Their expression as folded domains strongly supports the predicted domain organization of alpha2M. An X-ray crystal structure of MG2 shows it to have a fibronectin type-3 fold analogous to MG1-MG8 of C3. TED is, as predicted, an alpha-helical domain. CUB is a spliced domain composed of two stretches of polypeptide that flank TED in the primary structure. In intact C3 TED interacts with RBD, where it is in direct contact with the thiol ester, and with MG2 and CUB on opposite, flanking sides. In contrast, these alpha2M domains, as isolated species, show negligible interaction with one another, suggesting that the native conformation of alpha2M, and the consequent thiol ester-stabilizing domain-domain interactions, result from additional restraints imposed by the physical linkage of these domains or by additional domains in the protein.

Human α2-macroglobulin is composed of multiple domains, as predicted by homology with complement component C3

PubMed Central

Doan, Ninh; Gettins, Peter G. W.

2007-01-01

Human α2M (α2-macroglobulin) and the complement components C3 and C4 are thiol ester-containing proteins that evolved from the same ancestral gene. The recent structure determination of human C3 has allowed a detailed prediction of the location of domains within human α2M to be made. We describe here the expression and characterization of three α2M domains predicted to be involved in the stabilization of the thiol ester in native α2M and in its activation upon bait region proteolysis. The three newly expressed domains are MG2 (macroglobulin domain 2), TED (thiol ester-containing domain) and CUB (complement protein subcomponents C1r/C1s, urchin embryonic growth factor and bone morphogenetic protein 1) domain. Together with the previously characterized RBD (receptor-binding domain), they represent approx. 42% of the α2M polypeptide. Their expression as folded domains strongly supports the predicted domain organization of α2M. An X-ray crystal structure of MG2 shows it to have a fibronectin type-3 fold analogous to MG1–MG8 of C3. TED is, as predicted, an α-helical domain. CUB is a spliced domain composed of two stretches of polypeptide that flank TED in the primary structure. In intact C3 TED interacts with RBD, where it is in direct contact with the thiol ester, and with MG2 and CUB on opposite, flanking sides. In contrast, these α2M domains, as isolated species, show negligible interaction with one another, suggesting that the native conformation of α2M, and the consequent thiol ester-stabilizing domain–domain interactions, result from additional restraints imposed by the physical linkage of these domains or by additional domains in the protein. PMID:17608619

Neuropsychological and socio-occupational functioning in young psychiatric outpatients: a longitudinal investigation.

PubMed

Lee, Rico S C; Hermens, Daniel F; Redoblado-Hodge, M Antoinette; Naismith, Sharon L; Porter, Melanie A; Kaur, Manreena; White, Django; Scott, Elizabeth M; Hickie, Ian B

2013-01-01

Clinical symptoms and neuropsychological deficits are longitudinally associated with functional outcome in chronic psychiatric cohorts. The current study extended these findings to young and early-course psychiatric outpatients, with the aim of identifying cognitive markers that predict later socio-occupational functioning. At baseline, 183 young psychiatric outpatients were assessed. Ninety-three returned for follow-up (M = 21.6 years old; SD = 4.5) with an average re-assessment interval of 21.6 months (SD = 7.0), and primary diagnoses of major depressive disorder (n = 34), bipolar disorder (n = 29), or psychosis (n = 30). The primary outcome measure was cross-validated with various other functional measures and structural equation modelling was used to map out the interrelationships between predictors and later functional outcome. Good socio-occupational functioning at follow-up was associated with better quality of life, less disability, current employment and being in a romantic relationship. The final structural equation model explained 47.5% of the variability in functional outcome at follow-up, with baseline neuropsychological functioning (a composite of memory, working memory and attentional switching) the best independent predictor of later functional outcome. Notably, depressive and negative symptoms were only associated with functioning cross-sectionally. Diagnosis at follow-up was not associated with functional outcome. Neuropsychological functioning was the single best predictor of later socio-occupational outcome among young psychiatric outpatients. Therefore, framing psychiatric disorders along a neuropsychological continuum is likely to be more useful in predicting functional trajectory than traditional symptom-based classification systems. The current findings also have implications for early intervention utilising cognitive remediation approaches.

Radiomic biomarkers from PET/CT multi-modality fusion images for the prediction of immunotherapy response in advanced non-small cell lung cancer patients

NASA Astrophysics Data System (ADS)

Mu, Wei; Qi, Jin; Lu, Hong; Schabath, Matthew; Balagurunathan, Yoganand; Tunali, Ilke; Gillies, Robert James

2018-02-01

Purpose: Investigate the ability of using complementary information provided by the fusion of PET/CT images to predict immunotherapy response in non-small cell lung cancer (NSCLC) patients. Materials and methods: We collected 64 patients diagnosed with primary NSCLC treated with anti PD-1 checkpoint blockade. Using PET/CT images, fused images were created following multiple methodologies, resulting in up to 7 different images for the tumor region. Quantitative image features were extracted from the primary image (PET/CT) and the fused images, which included 195 from primary images and 1235 features from the fusion images. Three clinical characteristics were also analyzed. We then used support vector machine (SVM) classification models to identify discriminant features that predict immunotherapy response at baseline. Results: A SVM built with 87 fusion features and 13 primary PET/CT features on validation dataset had an accuracy and area under the ROC curve (AUROC) of 87.5% and 0.82, respectively, compared to a model built with 113 original PET/CT features on validation dataset 78.12% and 0.68. Conclusion: The fusion features shows better ability to predict immunotherapy response prediction compared to individual image features.

Altitudinal variations of ground tissue and xylem tissue in terminal shoot of woody species: implications for treeline formation.

PubMed

Chen, Hong; Wang, Haiyang; Liu, Yanfang; Dong, Li

2013-01-01

1. The terminal shoot (or current-year shoot), as one of the most active parts on a woody plant, is a basic unit determining plant height and is potentially influenced by a variety of environmental factors. It has been predicted that tissues amount and their allocation in plant stems may play a critical role in determining plant size in alpine regions. The primary structure in terminal shoots is a key to our understanding treeline formation. The existing theories on treeline formation, however, are still largely lacking of evidence at the species level, much less from anatomy for the terminal shoot. 2. The primary structures within terminal shoot were measured quantitatively for 100 species from four elevation zones along the eastern slope of Gongga Mountain, southwestern China; one group was sampled from above the treeline. An allometric approach was employed to examine scaling relationships interspecifically, and a principal components analysis (PCA) was performed to test the relation among primary xylem, ground tissue, species growth form and altitude. 3. The results showed that xylem tissue size was closely correlated with ground tissue size isometrically across species, while undergoing significant y- or/and x-intercept shift in response to altitudinal belts. Further, a conspicuous characteristic of terminal shoot was its allocation of contrasting tissues between primary xylem and ground tissues with increasing elevation. The result of the PCA showed correlations between anatomical variation, species growth form/height classes and environment. 4. The current study presents a comparative assessment of the allocation of tissue in terminal shoot across phylogenically and ecologically diverse species, and analyzes tissue, function and climate associations with plant growth forms and height classes among species. The interspecific connection between primary xylem ratio and plant size along an elevation gradient suggests the importance of primary xylem in explaining the treeline formation.

Altitudinal Variations of Ground Tissue and Xylem Tissue in Terminal Shoot of Woody Species: Implications for Treeline Formation

PubMed Central

Chen, Hong; Wang, Haiyang; Liu, Yanfang; Dong, Li

2013-01-01

1. The terminal shoot (or current-year shoot), as one of the most active parts on a woody plant, is a basic unit determining plant height and is potentially influenced by a variety of environmental factors. It has been predicted that tissues amount and their allocation in plant stems may play a critical role in determining plant size in alpine regions. The primary structure in terminal shoots is a key to our understanding treeline formation. The existing theories on treeline formation, however, are still largely lacking of evidence at the species level, much less from anatomy for the terminal shoot. 2. The primary structures within terminal shoot were measured quantitatively for 100 species from four elevation zones along the eastern slope of Gongga Mountain, southwestern China; one group was sampled from above the treeline. An allometric approach was employed to examine scaling relationships interspecifically, and a principal components analysis (PCA) was performed to test the relation among primary xylem, ground tissue, species growth form and altitude. 3. The results showed that xylem tissue size was closely correlated with ground tissue size isometrically across species, while undergoing significant y- or/and x-intercept shift in response to altitudinal belts. Further, a conspicuous characteristic of terminal shoot was its allocation of contrasting tissues between primary xylem and ground tissues with increasing elevation. The result of the PCA showed correlations between anatomical variation, species growth form/height classes and environment. 4. The current study presents a comparative assessment of the allocation of tissue in terminal shoot across phylogenically and ecologically diverse species, and analyzes tissue, function and climate associations with plant growth forms and height classes among species. The interspecific connection between primary xylem ratio and plant size along an elevation gradient suggests the importance of primary xylem in explaining the treeline formation. PMID:23658621

In Infants' Hands: Identification of Preverbal Infants at Risk for Primary Language Delay

ERIC Educational Resources Information Center

Lüke, Carina; Grimminger, Angela; Rohlfing, Katharina J.; Liszkowski, Ulf; Ritterfeld, Ute

2017-01-01

Early identification of primary language delay is crucial to implement effective prevention programs. Available screening instruments are based on parents' reports and have only insufficient predictive validity. This study employed observational measures of preverbal infants' gestural communication to test its predictive validity for identifying…

Experimental transient and permanent deformation studies of steel-sphere-impacted or impulsively-loaded aluminum beams with clamped ends

NASA Technical Reports Server (NTRS)

Witmer, E. A.

1975-01-01

The sheet explosive loading technique (SELT) was employed to obtain elastic-plastic, large-deflection transient and/or permanent strain data on simple well-defined structural specimens and materials: initially-flat 6061-T651 aluminum beams with both ends ideally clamped via integral construction. The SELT loading technique was chosen since it is both convenient and provides forcing function information of small uncertainty. These data will be useful for evaluating pertinent structural response prediction methods. A second objective was to obtain high-quality transient-strain data for a well-defined structural/material model subjected to impact by a rigid body of known mass, impact velocity, and geometry; large-deflection, elastic-plastic transient response conditions are of primary interest. The beam with both ends clamped and a steel sphere as the impacting body were chosen. The steel sphere was launched vertically by explosive propulsion to achieve various desired impact velocities. The sphere/beam impact tests resulted in producing a wide range of structural responses and permanent deformations, including rupture of the beam from excessive structural response in two cases. The transient and permanent strain data as well as the permanent deflection data obtained are of high quality and should be useful for checking and evaluating methods for predicting the responses of simple 2-d structures to fragment (sphere) impact. Transient strain data very close to the point of impact were not obtained over as long a time as desirable because the gage(s) in that region became detached during the transient response.

Structural behavior of the space shuttle SRM Tang-Clevis joint

NASA Technical Reports Server (NTRS)

Greene, W. H.; Knight, N. F., Jr.; Stockwell, A. E.

1986-01-01

The space shuttle Challenger accident investigation focused on the failure of a tang-clevis joint on the right solid rocket motor. The existence of relative motion between the inner arm of the clevis and the O-ring sealing surface on the tang has been identified as a potential contributor to this failure. This motion can cause the O-rings to become unseated and therefore lose their sealing capability. Finite element structural analyses have been performed to predict both deflections and stresses in the joint under the primary, pressure loading condition. These analyses have demonstrated the difficulty of accurately predicting the structural behavior of the tang-clevis joint. Stresses in the vicinity of the connecting pins, obtained from elastic analyses, considerably exceed the material yield allowables indicating that inelastic analyses are probably necessary. Two modifications have been proposed to control the relative motion between the inner clevis arm and the tang at the O-ring sealing surface. One modification, referred to as the capture feature, uses additional material on the inside of the tang to restrict motion of the inner clevis arm. The other modification uses external stiffening rings above and below the joint to control the local bending in the shell near the joint. Both of these modifications are shown to be effective in controlling the relative motion in the joint.

Structural behavior of the space shuttle SRM tang-clevis joint

NASA Technical Reports Server (NTRS)

Greene, William H.; Knight, Norman F., Jr.; Stockwell, Alan E.

1988-01-01

The space shuttle Challenger accident investigation focused on the failure of a tang-clevis joint on the right solid rocket motor. The existence of relative motion between the inner arm of the clevis and the O-ring sealing surface on the tang has been identified as a potential contributor to this failure. This motion can cause the O-rings to become unseated and therefore lose their sealing capability. Finite element structural analyses have been performed to predict both deflections and stresses in the joint under the primary, pressure loading condition. These analyses have demonstrated the difficulty of accurately predicting the structural behavior of the tang-clevis joint. Stresses in the vicinity of the connecting pins, obtained from elastic analyses, considerably exceed the material yield allowables indicating that inelastic analyses are probably necessary. Two modifications have been proposed to control the relative motion between the inner clevis arm and the tang at the O-ring sealing surface. One modification, referred to as the capture feature, uses additional material on the inside of the tang to restrict motion of the inner clevis arm. The other modification uses external stiffening rings above and below the joint to control the local bending in the shell near the joint. Both of these modifications are shown to be effective in controlling the relative motion in the joint.

Structure-based discovery of clinically approved drugs as Zika virus NS2B-NS3 protease inhibitors that potently inhibit Zika virus infection in vitro and in vivo.

PubMed

Yuan, Shuofeng; Chan, Jasper Fuk-Woo; den-Haan, Helena; Chik, Kenn Ka-Heng; Zhang, Anna Jinxia; Chan, Chris Chung-Sing; Poon, Vincent Kwok-Man; Yip, Cyril Chik-Yan; Mak, Winger Wing-Nga; Zhu, Zheng; Zou, Zijiao; Tee, Kah-Meng; Cai, Jian-Piao; Chan, Kwok-Hung; de la Peña, Jorge; Pérez-Sánchez, Horacio; Cerón-Carrasco, José Pedro; Yuen, Kwok-Yung

2017-09-01

Zika virus (ZIKV) infection may be associated with severe complications in fetuses and adults, but treatment options are limited. We performed an in silico structure-based screening of a large chemical library to identify potential ZIKV NS2B-NS3 protease inhibitors. Clinically approved drugs belonging to different drug classes were selected among the 100 primary hit compounds with the highest predicted binding affinities to ZIKV NS2B-NS3-protease for validation studies. ZIKV NS2B-NS3 protease inhibitory activity was validated in most of the selected drugs and in vitro anti-ZIKV activity was identified in two of them (novobiocin and lopinavir-ritonavir). Molecular docking and molecular dynamics simulations predicted that novobiocin bound to ZIKV NS2B-NS3-protease with high stability. Dexamethasone-immunosuppressed mice with disseminated ZIKV infection and novobiocin treatment had significantly (P < 0.05) higher survival rate (100% vs 0%), lower mean blood and tissue viral loads, and less severe histopathological changes than untreated controls. This structure-based drug discovery platform should facilitate the identification of additional enzyme inhibitors of ZIKV. Copyright © 2017 Elsevier B.V. All rights reserved.

Development of thermoplastic composite aircraft structures

NASA Technical Reports Server (NTRS)

Renieri, Michael P.; Burpo, Steven J.; Roundy, Lance M.; Todd, Stephanie A.; Kim, H. J.

1992-01-01

Efforts focused on the use of thermoplastic composite materials in the development of structural details associated with an advanced fighter fuselage section with applicability to transport design. In support of these designs, mechanics developments were conducted in two areas. First, a dissipative strain energy approach to material characterization and failure prediction, developed at the Naval Research Laboratory, was evaluated as a design/analysis tool. Second, a finite element formulation for thick composites was developed and incorporated into a lug analysis method which incorporates pin bending effects. Manufacturing concepts were developed for an upper fuel cell cover. A detailed trade study produced two promising concepts: fiber placement and single-step diaphragm forming. Based on the innovative design/manufacturing concepts for the fuselage section primary structure, elements were designed, fabricated, and structurally tested. These elements focused on key issues such as thick composite lugs and low cost forming of fastenerless, stiffener/moldine concepts. Manufacturing techniques included autoclave consolidation, single diaphragm consolidation (SDCC) and roll-forming.

Critical joints in large composite primary aircraft structures. Volume 2: Technology demonstration test report

NASA Technical Reports Server (NTRS)

Bunin, Bruce L.

1985-01-01

A program was conducted to develop the technology for critical structural joints in composite wing structure that meets all the design requirements of a 1990 commercial transport aircraft. The results of four large composite multirow bolted joint tests are presented. The tests were conducted to demonstrate the technology for critical joints in highly loaded composite structure and to verify the analytical methods that were developed throughout the program. The test consisted of a wing skin-stringer transition specimen representing a stringer runout and skin splice on the wing lower surface at the side of the fuselage attachment. All tests were static tension tests. The composite material was Toray T-300 fiber with Ciba-Geigy 914 resin in 10 mil tape form. The splice members were metallic, using combinations of aluminum and titanium. Discussions are given of the test article, instrumentation, test setup, test procedures, and test results for each of the four specimens. Some of the analytical predictions are also included.

Systematic bioinformatics and experimental validation of yeast complexes reduces the rate of attrition during structural investigations.

PubMed

Brooks, Mark A; Gewartowski, Kamil; Mitsiki, Eirini; Létoquart, Juliette; Pache, Roland A; Billier, Ysaline; Bertero, Michela; Corréa, Margot; Czarnocki-Cieciura, Mariusz; Dadlez, Michal; Henriot, Véronique; Lazar, Noureddine; Delbos, Lila; Lebert, Dorothée; Piwowarski, Jan; Rochaix, Pascal; Böttcher, Bettina; Serrano, Luis; Séraphin, Bertrand; van Tilbeurgh, Herman; Aloy, Patrick; Perrakis, Anastassis; Dziembowski, Andrzej

2010-09-08

For high-throughput structural studies of protein complexes of composition inferred from proteomics data, it is crucial that candidate complexes are selected accurately. Herein, we exemplify a procedure that combines a bioinformatics tool for complex selection with in vivo validation, to deliver structural results in a medium-throughout manner. We have selected a set of 20 yeast complexes, which were predicted to be feasible by either an automated bioinformatics algorithm, by manual inspection of primary data, or by literature searches. These complexes were validated with two straightforward and efficient biochemical assays, and heterologous expression technologies of complex components were then used to produce the complexes to assess their feasibility experimentally. Approximately one-half of the selected complexes were useful for structural studies, and we detail one particular success story. Our results underscore the importance of accurate target selection and validation in avoiding transient, unstable, or simply nonexistent complexes from the outset. Copyright © 2010 Elsevier Ltd. All rights reserved.

Geophysical Factor Resolving of Rainfall Mechanism for Super Typhoons by Using Multiple Spatiotemporal Components Analysis

NASA Astrophysics Data System (ADS)

Huang, Chien-Lin; Hsu, Nien-Sheng

2016-04-01

This study develops a novel methodology to resolve the geophysical cause of typhoon-induced rainfall considering diverse dynamic co-evolution at multiple spatiotemporal components. The multi-order hidden patterns of complex hydrological process in chaos are detected to understand the fundamental laws of rainfall mechanism. The discovered spatiotemporal features are utilized to develop a state-of-the-art descriptive statistical model for mechanism validation, modeling and further prediction during typhoons. The time series of hourly typhoon precipitation from different types of moving track, atmospheric field and landforms are respectively precede the signal analytical process to qualify each type of rainfall cause and to quantify the corresponding affected degree based on the measured geophysical atmospheric-hydrological variables. This study applies the developed methodology in Taiwan Island which is constituted by complex diverse landform formation. The identified driving-causes include: (1) cloud height to ground surface; (2) co-movement effect induced by typhoon wind field with monsoon; (3) stem capacity; (4) interaction between typhoon rain band and terrain; (5) structural intensity variance of typhoon; and (6) integrated cloudy density of rain band. Results show that: (1) for the central maximum wind speed exceeding 51 m/sec, Causes (1) and (3) are the primary ones to generate rainfall; (2) for the typhoon moving toward the direction of 155° to 175°, Cause (2) is the primary one; (3) for the direction of 90° to 155°, Cause (4) is the primary one; (4) for the typhoon passing through mountain chain which above 3500 m, Cause (5) is the primary one; and (5) for the moving speed lower than 18 km/hr, Cause (6) is the primary one. Besides, the multiple geophysical component-based precipitation modeling can achieve 81% of average accuracy and 0.732 of average correlation coefficient (CC) within average 46 hours of duration, that improve their predictability.

Representation of aversive prediction errors in the human periaqueductal gray

PubMed Central

Roy, Mathieu; Shohamy, Daphna; Daw, Nathaniel; Jepma, Marieke; Wimmer, Elliott; Wager, Tor D.

2014-01-01

Pain is a primary driver of learning and motivated action. It is also a target of learning, as nociceptive brain responses are shaped by learning processes. We combined an instrumental pain avoidance task with an axiomatic approach to assessing fMRI signals related to prediction errors (PEs), which drive reinforcement-based learning. We found that pain PEs were encoded in the periaqueductal gray (PAG), an important structure for pain control and learning in animal models. Axiomatic tests combined with dynamic causal modeling suggested that ventromedial prefrontal cortex, supported by putamen, provides an expected value-related input to the PAG, which then conveys PE signals to prefrontal regions important for behavioral regulation, including orbitofrontal, anterior mid-cingulate, and dorsomedial prefrontal cortices. Thus, pain-related learning involves distinct neural circuitry, with implications for behavior and pain dynamics. PMID:25282614

Modeling Lignin Polymerization. I. Simulation Model of Dehydrogenation Polymers1[OA

PubMed Central

van Parijs, Frederik R.D.; Morreel, Kris; Ralph, John; Boerjan, Wout; Merks, Roeland M.H.

2010-01-01

Lignin is a heteropolymer that is thought to form in the cell wall by combinatorial radical coupling of monolignols. Here, we present a simulation model of in vitro lignin polymerization, based on the combinatorial coupling theory, which allows us to predict the reaction conditions controlling the primary structure of lignin polymers. Our model predicts two controlling factors for the β-O-4 content of syringyl-guaiacyl lignins: the supply rate of monolignols and the relative amount of supplied sinapyl alcohol monomers. We have analyzed the in silico degradability of the resulting lignin polymers by cutting the resulting lignin polymers at β-O-4 bonds. These are cleaved in analytical methods used to study lignin composition, namely thioacidolysis and derivatization followed by reductive cleavage, under pulping conditions, and in some lignocellulosic biomass pretreatments. PMID:20472753

Prediction of conformational changes by single mutation in the hepatitis B virus surface antigen (HBsAg) identified in HBsAg-negative blood donors.

PubMed

Ie, Susan I; Thedja, Meta D; Roni, Martono; Muljono, David H

2010-11-18

Selection of hepatitis B virus (HBV) by host immunity has been suggested to give rise to variants with amino acid substitutions at or around the 'a' determinant of the surface antigen (HBsAg), the main target of antibody neutralization and diagnostic assays. However, there have never been successful attempts to provide evidence for this hypothesis, partly because the 3 D structure of HBsAg molecules has not been determined. Tertiary structure prediction of HBsAg solely from its primary amino acid sequence may reveal the molecular energetic of the mutated proteins. We carried out this preliminary study to analyze the predicted HBsAg conformation changes of HBV variants isolated from Indonesian blood donors undetectable by HBsAg assays and its significance, compared to other previously-reported variants that were associated with diagnostic failure. Three HBV variants (T123A, M133L and T143M) and a wild type sequence were analyzed together with frequently emerged variants T123N, M133I, M133T, M133V, and T143L. Based on the Jameson-Wolf algorithm for calculating antigenic index, the first two amino acid substitutions resulted in slight changes in the antigenicity of the 'a' determinant, while all four of the comparative variants showed relatively more significant changes. In the pattern T143M, changes in antigenic index were more significant, both in its coverage and magnitude, even when compared to variant T143L. These data were also partially supported by the tertiary structure prediction, in which the pattern T143M showed larger shift in the HBsAg second loop structure compared to the others. Single amino acid substitutions within or near the 'a' determinant of HBsAg may alter antigenicity properties of variant HBsAg, which can be shown by both its antigenic index and predicted 3 D conformation. Findings in this study emphasize the significance of variant T143M, the prevalent isolate with highest degree of antigenicity changes found in Indonesian blood donors. This highlights the importance of evaluating the effects of protein structure alterations on the sensitivity of screening methods being used in detection of ongoing HBV infection, as well as the use of vaccines and immunoglobulin therapy in contributing to the selection of HBV variants.

A quantitative comparison of precipitation forecasts between the storm-scale numerical weather prediction model and auto-nowcast system in Jiangsu, China

NASA Astrophysics Data System (ADS)

Wang, Gaili; Yang, Ji; Wang, Dan; Liu, Liping

2016-11-01

Extrapolation techniques and storm-scale Numerical Weather Prediction (NWP) models are two primary approaches for short-term precipitation forecasts. The primary objective of this study is to verify precipitation forecasts and compare the performances of two nowcasting schemes: a Beijing Auto-Nowcast system (BJ-ANC) based on extrapolation techniques and a storm-scale NWP model called the Advanced Regional Prediction System (ARPS). The verification and comparison takes into account six heavy precipitation events that occurred in the summer of 2014 and 2015 in Jiangsu, China. The forecast performances of the two schemes were evaluated for the next 6 h at 1-h intervals using gridpoint-based measures of critical success index, bias, index of agreement, root mean square error, and using an object-based verification method called Structure-Amplitude-Location (SAL) score. Regarding gridpoint-based measures, BJ-ANC outperforms ARPS at first, but then the forecast accuracy decreases rapidly with lead time and performs worse than ARPS after 4-5 h of the initial forecast. Regarding the object-based verification method, most forecasts produced by BJ-ANC focus on the center of the diagram at the 1-h lead time and indicate high-quality forecasts. As the lead time increases, BJ-ANC overestimates precipitation amount and produces widespread precipitation, especially at a 6-h lead time. The ARPS model overestimates precipitation at all lead times, particularly at first.

Adaptive compressive learning for prediction of protein-protein interactions from primary sequence.

PubMed

Zhang, Ya-Nan; Pan, Xiao-Yong; Huang, Yan; Shen, Hong-Bin

2011-08-21

Protein-protein interactions (PPIs) play an important role in biological processes. Although much effort has been devoted to the identification of novel PPIs by integrating experimental biological knowledge, there are still many difficulties because of lacking enough protein structural and functional information. It is highly desired to develop methods based only on amino acid sequences for predicting PPIs. However, sequence-based predictors are often struggling with the high-dimensionality causing over-fitting and high computational complexity problems, as well as the redundancy of sequential feature vectors. In this paper, a novel computational approach based on compressed sensing theory is proposed to predict yeast Saccharomyces cerevisiae PPIs from primary sequence and has achieved promising results. The key advantage of the proposed compressed sensing algorithm is that it can compress the original high-dimensional protein sequential feature vector into a much lower but more condensed space taking the sparsity property of the original signal into account. What makes compressed sensing much more attractive in protein sequence analysis is its compressed signal can be reconstructed from far fewer measurements than what is usually considered necessary in traditional Nyquist sampling theory. Experimental results demonstrate that proposed compressed sensing method is powerful for analyzing noisy biological data and reducing redundancy in feature vectors. The proposed method represents a new strategy of dealing with high-dimensional protein discrete model and has great potentiality to be extended to deal with many other complicated biological systems. Copyright © 2011 Elsevier Ltd. All rights reserved.

Progress in the Fabrication and Testing of Telescope Mirrors for The James Webb Space Telescope

NASA Astrophysics Data System (ADS)

Bowers, Charles W.; Clampin, M.; Feinberg, L.; Keski-Kuha, R.; McKay, A.; Chaney, D.; Gallagher, B.; Ha, K.

2012-01-01

The telescope of the James Webb Space Telescope (JWST) is an f/20, three mirror anastigmat design, passively cooled (40K) in an L2 orbit. The design provides diffraction limited performance (Strehl ≥ 0.8) at λ=2μm. To fit within the launch vehicle envelope (Arianne V), the 6.6 meter primary mirror and the secondary mirror support structure are folded for launch, then deployed and aligned in space. The primary mirror is composed of 18 individual, 1.3 meter (flat:flat) hexagonal segments, each adjustable in seven degrees of freedom (six rigid body + radius of curvature) provided by a set of high precision actuators. The actuated secondary mirror ( 0.74m) is similarly positioned in six degrees of rigid body motion. The .70x.51m, fixed tertiary and 0.17m, flat fine steering mirror complete the telescope mirror complement. The telescope is supported by a composite structure optimized for performance at cryogenic temperatures. All telescope mirrors are made of Be with substantial lightweighting (21kg for each 1.3M primary segment). Additional Be mounting and supporting structure for the high precision ( 10nm steps) actuators are attached to the primary segments and secondary mirror. All mirrors undergo a process of thermal stabilization to reduce stress. An extensive series of interferometric measurements guide each step of the polishing process. Final polishing must account for any deformation between the ambient temperature of polishing and the cryogenic, operational temperature. This is accomplished by producing highly precise, cryo deformation target maps of each surface which are incorporated into the final polishing cycle. All flight mirrors have now completed polishing, coating with protected Au and final cryo testing, and the telescope is on track to meet all system requirements. We here review the measured performance of the component mirrors and the predicted performance of the flight telescope.

Stomach Chitinase from Japanese Sardine Sardinops melanostictus: Purification, Characterization, and Molecular Cloning of Chitinase Isozymes with a Long Linker.

PubMed

Kawashima, Satoshi; Ikehata, Hiroki; Tada, Chihiro; Ogino, Tomohiro; Kakizaki, Hiromi; Ikeda, Mana; Fukushima, Hideto; Matsumiya, Masahiro

2016-01-20

Fish express two different chitinases, acidic fish chitinase-1 (AFCase-1) and acidic fish chitinase-2 (AFCase-2), in the stomach. AFCase-1 and AFCase-2 have different degradation patterns, as fish efficiently degrade chitin ingested as food. For a comparison with the enzymatic properties and the primary structures of chitinase isozymes obtained previously from the stomach of demersal fish, in this study, we purified chitinase isozymes from the stomach of Japanese sardine Sardinops melanostictus, a surface fish that feeds on plankton, characterized the properties of these isozymes, and cloned the cDNAs encoding chitinases. We also predicted 3D structure models using the primary structures of S. melanostictus stomach chitinases. Two chitinase isozymes, SmeChiA (45 kDa) and SmeChiB (56 kDa), were purified from the stomach of S. melanostictus. Moreover, two cDNAs, SmeChi-1 encoding SmeChiA, and SmeChi-2 encoding SmeChiB were cloned. The linker regions of the deduced amino acid sequences of SmeChi-1 and SmeChi-2 (SmeChi-1 and SmeChi-2) are the longest among the fish stomach chitinases. In the cleavage pattern groups toward short substrates and the phylogenetic tree analysis, SmeChi-1 and SmeChi-2 were classified into AFCase-1 and AFCase-2, respectively. SmeChi-1 and SmeChi-2 had catalytic domains that consisted of a TIM-barrel (β/α)₈-fold structure and a deep substrate-binding cleft. This is the first study showing the 3D structure models of fish stomach chitinases.

Primary and secondary structural analyses of glutathione S-transferase pi from human placenta.

PubMed

Ahmad, H; Wilson, D E; Fritz, R R; Singh, S V; Medh, R D; Nagle, G T; Awasthi, Y C; Kurosky, A

1990-05-01

The primary structure of glutathione S-transferase (GST) pi from a single human placenta was determined. The structure was established by chemical characterization of tryptic and cyanogen bromide peptides as well as automated sequence analysis of the intact enzyme. The structural analysis indicated that the protein is comprised of 209 amino acid residues and gave no evidence of post-translational modifications. The amino acid sequence differed from that of the deduced amino acid sequence determined by nucleotide sequence analysis of a cDNA clone (Kano, T., Sakai, M., and Muramatsu, M., 1987, Cancer Res. 47, 5626-5630) at position 104 which contained both valine and isoleucine whereas the deduced sequence from nucleotide sequence analysis identified only isoleucine at this position. These results demonstrated that in the one individual placenta studied at least two GST pi genes are coexpressed, probably as a result of allelomorphism. Computer assisted consensus sequence evaluation identified a hydrophobic region in GST pi (residues 155-181) that was predicted to be either a buried transmembrane helical region or a signal sequence region. The significance of this hydrophobic region was interpreted in relation to the mode of action of the enzyme especially in regard to the potential involvement of a histidine in the active site mechanism. A comparison of the chemical similarity of five known human GST complete enzyme structures, one of pi, one of mu, two of alpha, and one microsomal, gave evidence that all five enzymes have evolved by a divergent evolutionary process after gene duplication, with the microsomal enzyme representing the most divergent form.

Evidence for communality in the primary determinants of CYP74 catalysis and of structural similarities between CYP74 and classical mammalian P450 enzymes.

PubMed

Hughes, Richard K; Yousafzai, Faridoon K; Ashton, Ruth; Chechetkin, Ivan R; Fairhurst, Shirley A; Hamberg, Mats; Casey, Rod

2008-09-01

In silico structural analysis of CYP74C3, a membrane-associated P450 enzyme from the plant Medicago truncatula (barrel medic) with hydroperoxide lyase (HPL) specificity, showed that it had strong similarities to the structural folds of the classical microsomal P450 enzyme from rabbits (CYP2C5). It was not only the secondary structure predictions that supported the analysis but site directed mutagenesis of the substrate interacting residues was also consistent with it. This led us to develop a substrate-binding model of CYP74C3 which predicted three amino acid residues, N285, F287, and G288 located in the putative I-helix and distal haem pocket of CYP74C3 to be in close proximity to the preferred substrate 13-HPOTE. These residues were judged to be in equivalent positions to those identified in SRS-4 of CYP2C5. Significance of the residues and their relevance to the model were further assessed by site directed mutagenesis of the three residues followed by EPR spectroscopic and detailed kinetic investigations of the mutated proteins in the presence and absence of detergent. Although point mutation of the residues had no effect on the haem content of the mutated proteins, significant effects on the spin state equilibrium of the haem iron were noted. Kinetic effects of the mutations, which were investigated using three different substrates, were dramatic in nature. In the presence of detergent with the preferred substrate (13-HPOTE), the catalytic center activities and substrate binding affinities of the mutant proteins were reduced by a factor of 8-32 and 4-12, respectively, compared with wild-type--a two orders of magnitude reduction in catalytic efficiencies. We believe this is the first report where primary determinants of catalysis for any CYP74 enzyme, which are fully consistent with our model, have been identified. Our working model predicts that N285 is close enough to suggest that a hydrogen bond with the peroxy group of the enzyme substrate 13-HPOTE is warranted, whereas significance of F287 may arise from a strong hydrophobic interaction between the alkyl group(s) of the substrate and the phenyl ring of F287. We believe that G288 is crucial because of its size. Any other residue with a relatively bulky side chain will hinder the access of substrate to the active site. The effects of the mutations suggests that subtle protein conformational changes in the putative substrate-binding pocket regulate the formation of a fully active monomer-micelle complex with low-spin haem iron and that structural communication exists between the substrate- and micelle-binding sites of CYP74C3. Conservation in CYP74 sequence alignments suggests that N285, F287, and G288 in CYP74C3 and the equivalent residues at positions in other CYP74 enzymes are likely to be critical to catalysis. To support this we show that G324 in CYP74D4 (Arabidopsis AOS), equivalent to G288 in CYP74C3, is a primary determinant of positional specificity. We suggest that the overall structure of CYP74 enzymes is likely to be very similar to those described for classical P450 monooxygenase enzymes. 2008 Wiley-Liss, Inc.

Computational identification of structural factors affecting the mutagenic potential of aromatic amines: study design and experimental validation.

PubMed

Slavov, Svetoslav H; Stoyanova-Slavova, Iva; Mattes, William; Beger, Richard D; Brüschweiler, Beat J

2018-07-01

A grid-based, alignment-independent 3D-SDAR (three-dimensional spectral data-activity relationship) approach based on simulated 13 C and 15 N NMR chemical shifts augmented with through-space interatomic distances was used to model the mutagenicity of 554 primary and 419 secondary aromatic amines. A robust modeling strategy supported by extensive validation including randomized training/hold-out test set pairs, validation sets, "blind" external test sets as well as experimental validation was applied to avoid over-parameterization and build Organization for Economic Cooperation and Development (OECD 2004) compliant models. Based on an experimental validation set of 23 chemicals tested in a two-strain Salmonella typhimurium Ames assay, 3D-SDAR was able to achieve performance comparable to 5-strain (Ames) predictions by Lhasa Limited's Derek and Sarah Nexus for the same set. Furthermore, mapping of the most frequently occurring bins on the primary and secondary aromatic amine structures allowed the identification of molecular features that were associated either positively or negatively with mutagenicity. Prominent structural features found to enhance the mutagenic potential included: nitrobenzene moieties, conjugated π-systems, nitrothiophene groups, and aromatic hydroxylamine moieties. 3D-SDAR was also able to capture "true" negative contributions that are particularly difficult to detect through alternative methods. These include sulphonamide, acetamide, and other functional groups, which not only lack contributions to the overall mutagenic potential, but are known to actively lower it, if present in the chemical structures of what otherwise would be potential mutagens.

Models of protein–ligand crystal structures: trust, but verify

PubMed Central

Deller, Marc C.

2015-01-01

X-ray crystallography provides the most accurate models of protein–ligand structures. These models serve as the foundation of many computational methods including structure prediction, molecular modelling, and structure-based drug design. The success of these computational methods ultimately depends on the quality of the underlying protein–ligand models. X-ray crystallography offers the unparalleled advantage of a clear mathematical formalism relating the experimental data to the protein–ligand model. In the case of X-ray crystallography, the primary experimental evidence is the electron density of the molecules forming the crystal. The first step in the generation of an accurate and precise crystallographic model is the interpretation of the electron density of the crystal, typically carried out by construction of an atomic model. The atomic model must then be validated for fit to the experimental electron density and also for agreement with prior expectations of stereochemistry. Stringent validation of protein–ligand models has become possible as a result of the mandatory deposition of primary diffraction data, and many computational tools are now available to aid in the validation process. Validation of protein–ligand complexes has revealed some instances of overenthusiastic interpretation of ligand density. Fundamental concepts and metrics of protein–ligand quality validation are discussed and we highlight software tools to assist in this process. It is essential that end users select high quality protein–ligand models for their computational and biological studies, and we provide an overview of how this can be achieved. PMID:25665575

Models of protein-ligand crystal structures: trust, but verify.

PubMed

Deller, Marc C; Rupp, Bernhard

2015-09-01

X-ray crystallography provides the most accurate models of protein-ligand structures. These models serve as the foundation of many computational methods including structure prediction, molecular modelling, and structure-based drug design. The success of these computational methods ultimately depends on the quality of the underlying protein-ligand models. X-ray crystallography offers the unparalleled advantage of a clear mathematical formalism relating the experimental data to the protein-ligand model. In the case of X-ray crystallography, the primary experimental evidence is the electron density of the molecules forming the crystal. The first step in the generation of an accurate and precise crystallographic model is the interpretation of the electron density of the crystal, typically carried out by construction of an atomic model. The atomic model must then be validated for fit to the experimental electron density and also for agreement with prior expectations of stereochemistry. Stringent validation of protein-ligand models has become possible as a result of the mandatory deposition of primary diffraction data, and many computational tools are now available to aid in the validation process. Validation of protein-ligand complexes has revealed some instances of overenthusiastic interpretation of ligand density. Fundamental concepts and metrics of protein-ligand quality validation are discussed and we highlight software tools to assist in this process. It is essential that end users select high quality protein-ligand models for their computational and biological studies, and we provide an overview of how this can be achieved.

A machine learning model to predict the risk of 30-day readmissions in patients with heart failure: a retrospective analysis of electronic medical records data.

PubMed

Golas, Sara Bersche; Shibahara, Takuma; Agboola, Stephen; Otaki, Hiroko; Sato, Jumpei; Nakae, Tatsuya; Hisamitsu, Toru; Kojima, Go; Felsted, Jennifer; Kakarmath, Sujay; Kvedar, Joseph; Jethwani, Kamal

2018-06-22

Heart failure is one of the leading causes of hospitalization in the United States. Advances in big data solutions allow for storage, management, and mining of large volumes of structured and semi-structured data, such as complex healthcare data. Applying these advances to complex healthcare data has led to the development of risk prediction models to help identify patients who would benefit most from disease management programs in an effort to reduce readmissions and healthcare cost, but the results of these efforts have been varied. The primary aim of this study was to develop a 30-day readmission risk prediction model for heart failure patients discharged from a hospital admission. We used longitudinal electronic medical record data of heart failure patients admitted within a large healthcare system. Feature vectors included structured demographic, utilization, and clinical data, as well as selected extracts of un-structured data from clinician-authored notes. The risk prediction model was developed using deep unified networks (DUNs), a new mesh-like network structure of deep learning designed to avoid over-fitting. The model was validated with 10-fold cross-validation and results compared to models based on logistic regression, gradient boosting, and maxout networks. Overall model performance was assessed using concordance statistic. We also selected a discrimination threshold based on maximum projected cost saving to the Partners Healthcare system. Data from 11,510 patients with 27,334 admissions and 6369 30-day readmissions were used to train the model. After data processing, the final model included 3512 variables. The DUNs model had the best performance after 10-fold cross-validation. AUCs for prediction models were 0.664 ± 0.015, 0.650 ± 0.011, 0.695 ± 0.016 and 0.705 ± 0.015 for logistic regression, gradient boosting, maxout networks, and DUNs respectively. The DUNs model had an accuracy of 76.4% at the classification threshold that corresponded with maximum cost saving to the hospital. Deep learning techniques performed better than other traditional techniques in developing this EMR-based prediction model for 30-day readmissions in heart failure patients. Such models can be used to identify heart failure patients with impending hospitalization, enabling care teams to target interventions at their most high-risk patients and improving overall clinical outcomes.

Polychlorinated Biphenyl (PCB) Bioaccumulation in Fish: A Look at Michigan's Upper Peninsula

NASA Astrophysics Data System (ADS)

Sokol, E. C.; Urban, N. R.; Perlinger, J. A.; Khan, T.; Friedman, C. L.

2014-12-01

Fish consumption is an important economic, social and cultural component of Michigan's UpperPeninsula, where safe fish consumption is threatened due to polychlorinated biphenyl (PCB)contamination. Despite its predominantly rural nature, the Upper Peninsula has a history of industrialPCB use. PCB congener concentrations in fish vary 50-fold in Upper Peninsula lakes. Several factors maycontribute to this high variability including local point sources, unique watershed and lakecharacteristics, and food web structure. It was hypothesized that the variability in congener distributionscould be used to identify factors controlling concentrations in fish, and then to use those factors topredict PCB contamination in fish from lakes that had not been monitored. Watershed and lakecharacteristics were acquired from several databases for 16 lakes sampled in the State's fishcontaminant survey. Species congener distributions were compared using Principal Component Analysis(PCA) to distinguish between lakes with local vs. regional, atmospheric sources; six lakes were predictedto have local sources and half of those have confirmed local PCB use. For lakes without local PCBsources, PCA indicated that lake size was the primary factor influencing PCB concentrations. The EPA'sbioaccumulation model, BASS, was used to predict PCB contamination in lakes without local sources as afunction of food web characteristics. The model was used to evaluate the hypothesis that deep,oligotrophic lakes have longer food webs and higher PCB concentrations in top predator fish. Based onthese findings, we will develop a mechanistic watershed-lake model to predict PCB concentrations infish as a function of atmospheric PCB concentrations, lake size, and trophic state. Future atmosphericconcentrations, predicted by modeling potential primary and secondary emission scenarios, will be usedto predict the time horizon for safe fish consumption.

Novel Automated Approach to Predict the Outcome of Laser Peripheral Iridotomy for Primary Angle Closure Suspect Eyes Using Anterior Segment Optical Coherence Tomography.

PubMed

Koh, Victor; Swamidoss, Issac Niwas; Aquino, Maria Cecilia D; Chew, Paul T; Sng, Chelvin

2018-04-27

Develop an algorithm to predict the success of laser peripheral iridotomy (LPI) in primary angle closure suspect (PACS), using pre-treatment anterior segment optical coherence tomography (ASOCT) scans. A total of 116 eyes with PACS underwent LPI and time-domain ASOCT scans (temporal and nasal cuts) were performed before and 1 month after LPI. All the post-treatment scans were classified to one of the following categories: (a) both angles open, (b) one of two angles open and (c) both angles closed. After LPI, success is defined as one or more angles changed from close to open. In this proposed method, the pre and post-LPI ASOCT scans were registered at the corresponding angles based on similarities between the respective local descriptor features and random sample consensus technique was used to identify the largest consensus set of correspondences between the pre and post-LPI ASOCT scans. Subsequently, features such as correlation co-efficient (CC) and structural similarity index (SSIM) were extracted and correlated with the success of LPI. We included 116 eyes and 91 (78.44%) eyes fulfilled the criteria for success after LPI. Using the CC and SSIM index scores from this training set of ASOCT images, our algorithm showed that the success of LPI in eyes with narrow angles can be predicted with 89.7% accuracy, specificity of 95.2% and sensitivity of 36.4% based on pre-LPI ASOCT scans only. Using pre-LPI ASOCT scans, our proposed algorithm showed good accuracy in predicting the success of LPI for PACS eyes. This fully-automated algorithm could aid decision making in offering LPI as a prophylactic treatment for PACS.

Changes in the ecosystem structure of the Black Sea under predicted climatological and anthropogenic variations

NASA Astrophysics Data System (ADS)

Akoglu, Ekin; Salihoglu, Baris; Fach Salihoglu, Bettina; Libralato, Simone; Cannaby, Heather; Oguz, Temel; Solidoro, Cosimo

2014-05-01

A dynamic Ecopath with Ecosim higher-trophic-level (HTL) model representation of the Black Sea ecosystem was coupled to the physical (BIMS-CIR) and biogeochemical (BIMS-ECO) models of the Black Sea in order to investigate historical anthropogenic and climatological interactions and feedbacks in the ecosystem. Further, the coupled models were used to assess the likely consequences of these interactions on the ecosystem's structure and functioning under predicted future climate (IPCC A1B) and fishing variability. Therefore, two model scenarios were used; i) a hindcast scenario (1980-1999) to evaluate and understand the impacts of the short-term climate and physical variability and the introduction of invasive species on the Black Sea ecosystem, and ii) a forecast scenario (2080-2099) to investigate the potential implications of climate change and anthropogenic exploitation on living resources of the Black Sea ecosystem by the end of the 21st century. According to the outcomes of the hindcast simulation, fisheries were found to be the main driver in determining the structure and functioning of the Black Sea ecosystem under changing environmental conditions. The coupled physical-biogeochemical forecast simulations predicted a slight but statistically significant basin-wide increase in the Black Sea's primary productivity by the end of the century due to increased stratification induced by basin-wide temperature increase and reduced Cold Intermediate Layer (CIL) formation which increased the residence time of riverine nutrients within the euphotic zone. Despite this increased primary productivity, the HTL model forecast simulation predicted a significant decrease in the commercial fish stocks primarily due to fisheries exploitation if current catch rates are maintained into the future. Results further suggested that some economically important small pelagic fish species are likely to disappear from the ecosystem making the recovery of the already-collapsed piscivorous fish stocks increasingly unlikely. In addition, a further reduction in the proportion of piscivorous fish in the fish community was found to be consequent. From a management perspective, the results of the study suggested that along with managing fishing exploitation levels of the target stocks, monitoring and management of other species in the ecosystem that are tightly coupled with the fish species in terms of food web interactions were found to be the most effective way of applying an ecosystem-based management strategy in the Black Sea. Such an approach will ensure the sustainable utilisation of the fish stocks of the Black Sea by maintaining the ecological integrity of the Black Sea marine food web.

Secondary impact hazard assessment

NASA Technical Reports Server (NTRS)

1986-01-01

A series of light gas gun shots (4 to 7 km/sec) were performed with 5 mg nylon and aluminum projectiles to determine the size, mass, velocity, and spatial distribution of spall and ejecta from a number of graphite/epoxy targets. Similar determinations were also performed on a few aluminum targets. Target thickness and material were chosen to be representative of proposed Space Station structure. The data from these shots and other information were used to predict the hazard to Space Station elements from secondary particles resulting from impacts of micrometeoroids and orbital debris on the Space Station. This hazard was quantified as an additional flux over and above the primary micrometeoroid and orbital debris flux that must be considered in the design process. In order to simplify the calculations, eject and spall mass were assumed to scale directly with the energy of the projectile. Other scaling systems may be closer to reality. The secondary particles considered are only those particles that may impact other structure immediately after the primary impact. The addition to the orbital debris problem from these primary impacts was not addressed. Data from this study should be fed into the orbital debris model to see if Space Station secondaries make a significant contribution to orbital debris. The hazard to a Space Station element from secondary particles above and beyond the micrometeoroid and orbital debris hazard is categorized in terms of two factors: (1) the 'view factor' of the element to other Space Station structure or the geometry of placement of the element, and (2) the sensitivity to damage, stated in terms of energy. Several example cases were chosen, the Space Station module windows, windows of a Shuttle docked to the Space Station, the habitat module walls, and the photovoltaic solar cell arrays. For the examples chosen the secondary flux contributed no more than 10 percent to the total flux (primary and secondary) above a given calculated critical energy. A key assumption in these calculations is that above a certain critical energy, significant damage will be done. This is not true for all structures. Double-walled, bumpered structures are an example for which damage may be reduced as energy goes up. The critical energy assumption is probably conservative, however, in terms of secondary damage. To understand why the secondary impacts seem to, in general, contribute less than 10 percent of the flux above a given critical energy, consider the case of a meteoroid impact of a given energy on a fixed, large surface. This impact results in a variety of secondary particles, all of which have much less energy than the original impact. Conservation of energy prohibits any other situation. Thus if damage is linked to a critical energy of a particle, the primary flux will always deliver particles of much greater energy. Even if all the secondary particles impacted other Space Station structures, none would have a kinetic energy more than a fraction of the primary impact energy.

Emotion Understanding, Social Competence and School Achievement in Children from Primary School in Portugal

PubMed Central

Franco, Maria da Glória; Beja, Maria J.; Candeias, Adelinda; Santos, Natalie

2017-01-01

This study analyzes the relationship between emotion understanding and school achievement in children of primary school, considering age, gender, fluid intelligence, mother’s educational level and social competence. In this study participated 406 children of primary school. The instruments used were the Test of Emotion Comprehension, Colored Progressive Matrices of Raven, Socially Action and Interpersonal Problem Solving Scale. The structural equation model showed the relationship between the emotion understanding and school performance depends on a mediator variable that in the context of the study was designated social competence. Age appear as an explanatory factor of the differences found, the mother’s educational level only predicts significantly social emotional competence, fluid intelligence is a predictor of emotion understanding, school achievement and social emotional competence. Regarding the influence of sex, emotional understanding does not emerge as a significant predictor of social emotional competence in girls or boys. Multiple relationships between the various factors associated with school achievement and social emotional competence are discussed as well as their implications in promoting child development and school success. PMID:28861014

Primary School Text Comprehension Predicts Mathematical Word Problem-Solving Skills in Secondary School

ERIC Educational Resources Information Center

Björn, Piia Maria; Aunola, Kaisa; Nurmi, Jari-Erik

2016-01-01

This longitudinal study aimed to investigate the extent to which primary school text comprehension predicts mathematical word problem-solving skills in secondary school among Finnish students. The participants were 224 fourth graders (9-10 years old at the baseline). The children's text-reading fluency, text comprehension and basic calculation…

Integrative Analysis Reveals an Outcome-associated and Targetable Pattern of p53 and Cell Cycle Deregulation in Diffuse Large B-cell Lymphoma

PubMed Central

Monti, Stefano; Chapuy, Bjoern; Takeyama, Kunihiko; Rodig, Scott J; Hao, Yangsheng; Yeda, Kelly T.; Inguilizian, Haig; Mermel, Craig; Curie, Treeve; Dogan, Ahmed; Kutok, Jeffery L; Beroukim, Rameen; Neuberg, Donna; Habermann, Thomas; Getz, Gad; Kung, Andrew L; Golub, Todd R; Shipp, Margaret A

2013-01-01

Summary Diffuse large B-cell lymphoma (DLBCL) is a clinically and biologically heterogeneous disease with a high proliferation rate. By integrating copy number data with transcriptional profiles and performing pathway analysis in primary DLBCLs, we identified a comprehensive set of copy number alterations (CNAs) that decreased p53 activity and perturbed cell cycle regulation. Primary tumors either had multiple complementary alterations of p53 and cell cycle components or largely lacked these lesions. DLBCLs with p53 and cell cycle pathway CNAs had decreased abundance of p53 target transcripts and increased expression of E2F target genes and the Ki67 proliferation marker. CNAs of the CDKN2A-TP53-RB-E2F axis provide a structural basis for increased proliferation in DLBCL, predict outcome with current therapy and suggest targeted treatment approaches. PMID:22975378

SBLOCA outside containment at Browns Ferry Unit One. Volume 2. Iodine, cesium, and noble gas distribution and release

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wichner, R.P.; Weber, C.F.; Wright, A.L.

1983-09-01

This is the second volume of a two-part study regarding the response of Browns Ferry Unit 1 to a postulated break in the scram discharge volume of the control rod drive hydraulic system immediately following a scram. The material in this second volume pertains to the second aspect of the study, the resultant transport of fission products from their original locations in the fuel to a series of repositories within the primary system, the primary and secondary containment structures, and ultimately the release of a small portion to the environment. Transport models are developed for the noble gases krypton andmore » xenon and for iodine and cesium to describe the release of these fission products from the overheated fuel and their subsequent movement under the conditions predicted to exist in the various repositories during the course of the accident.« less

PredPPCrys: Accurate Prediction of Sequence Cloning, Protein Production, Purification and Crystallization Propensity from Protein Sequences Using Multi-Step Heterogeneous Feature Fusion and Selection

PubMed Central

Wang, Huilin; Wang, Mingjun; Tan, Hao; Li, Yuan; Zhang, Ziding; Song, Jiangning

2014-01-01

X-ray crystallography is the primary approach to solve the three-dimensional structure of a protein. However, a major bottleneck of this method is the failure of multi-step experimental procedures to yield diffraction-quality crystals, including sequence cloning, protein material production, purification, crystallization and ultimately, structural determination. Accordingly, prediction of the propensity of a protein to successfully undergo these experimental procedures based on the protein sequence may help narrow down laborious experimental efforts and facilitate target selection. A number of bioinformatics methods based on protein sequence information have been developed for this purpose. However, our knowledge on the important determinants of propensity for a protein sequence to produce high diffraction-quality crystals remains largely incomplete. In practice, most of the existing methods display poorer performance when evaluated on larger and updated datasets. To address this problem, we constructed an up-to-date dataset as the benchmark, and subsequently developed a new approach termed ‘PredPPCrys’ using the support vector machine (SVM). Using a comprehensive set of multifaceted sequence-derived features in combination with a novel multi-step feature selection strategy, we identified and characterized the relative importance and contribution of each feature type to the prediction performance of five individual experimental steps required for successful crystallization. The resulting optimal candidate features were used as inputs to build the first-level SVM predictor (PredPPCrys I). Next, prediction outputs of PredPPCrys I were used as the input to build second-level SVM classifiers (PredPPCrys II), which led to significantly enhanced prediction performance. Benchmarking experiments indicated that our PredPPCrys method outperforms most existing procedures on both up-to-date and previous datasets. In addition, the predicted crystallization targets of currently non-crystallizable proteins were provided as compendium data, which are anticipated to facilitate target selection and design for the worldwide structural genomics consortium. PredPPCrys is freely available at http://www.structbioinfor.org/PredPPCrys. PMID:25148528

Impact damage and residual strength analysis of composite panels with bonded stiffeners. [for primary aircraft structures

NASA Technical Reports Server (NTRS)

Madan, Ram C.; Shuart, Mark J.

1990-01-01

Blade-stiffened, compression-loaded cover panels were designed, manufactured, analyzed, and tested. All panels were fabricated from IM6/1808I interleafed graphite-epoxy. An orthotropic blade stiffener and an orthotropic skin were selected to satisfy the design requirements for an advanced aircraft configuration. All specimens were impact damaged prior to testing. Experimental results were obtained for three- and five-stiffener panels. Analytical results described interlaminar forces caused by impact and predicted specimen residual strength. The analytical results compared reasonably with the experimental results for residual strength of the specimens.

Membrane expression of MRP-1, but not MRP-1 splicing or Pgp expression, predicts survival in patients with ESFT

PubMed Central

Roundhill, E; Burchill, S

2013-01-01

Background: Primary Ewing's sarcoma family of tumours (ESFTs) may respond to chemotherapy, although many patients experience subsequent disease recurrence and relapse. The survival of ESFT cells following chemotherapy has been attributed to the development of resistant disease, possibly through the expression of ABC transporter proteins. Methods: MRP-1 and Pgp mRNA and protein expression in primary ESFTs was determined by quantitative reverse-transcriptase PCR (RT-qPCR) and immunohistochemistry, respectively, and alternative splicing of MRP-1 by RT-PCR. Results: We observed MRP-1 protein expression in 92% (43 out of 47) of primary ESFTs, and cell membrane MRP-1 was highly predictive of both overall survival (P<0.0001) and event-free survival (P<0.0001). Alternative splicing of MRP-1 was detected in primary ESFTs, although the pattern of splicing variants was not predictive of patient outcome, with the exception of loss of exon 9 in six patients, which predicted relapse (P=0.041). Pgp protein was detected in 6% (38 out of 44) of primary ESFTs and was not associated with patient survival. Conclusion: For the first time we have established that cell membrane expression of MRP-1 or loss of exon 9 is predictive of outcome but not the number of splicing events or expression of Pgp, and both may be valuable factors for the stratification of patients for more intensive therapy. PMID:23799853

Treatment of Five or More Brain Metastases With Stereotactic Radiosurgery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hunter, Grant K.; Suh, John H.; Reuther, Alwyn M.

2012-08-01

Purpose: To examine the outcomes of patients with five or more brain metastases treated in a single session with stereotactic radiosurgery (SRS). Methods and Materials: Sixty-four patients with brain metastases treated with SRS to five or more lesions in a single session were reviewed. Primary disease type, number of lesions, Karnofsky performance score (KPS) at SRS, and status of primary and systemic disease at SRS were included. Patients were treated using dosing as defined by Radiation Therapy Oncology Group Protocol 90-05, with adjustments for critical structures. We defined prior whole-brain radiotherapy (WBRT) as WBRT completed >1 month before SRS andmore » concurrent WBRT as WBRT completed within 1 month before or after SRS. Kaplan-Meier estimates and Cox proportional hazard regression were used to determine which patient and treatment factors predicted overall survival (OS). Results: The median OS after SRS was 7.5 months. The median KPS was 80 (range, 60-100). A KPS of {>=}80 significantly influenced OS (median OS, 4.8 months for KPS {<=}70 vs. 8.8 months for KPS {>=}80, p = 0.0097). The number of lesions treated did not significantly influence OS (median OS, 6.6 months for eight or fewer lesions vs. 9.9 months for more than eight, p = nonsignificant). Primary site histology did not significantly influence median OS. On multivariate Cox modeling, KPS and prior WBRT significantly predicted for OS. Whole-brain radiotherapy before SRS compared with concurrent WBRT significantly influenced survival, with a risk ratio of 0.423 (95% confidence interval 0.191-0.936, p = 0.0338). No significant differences were observed when no WBRT was compared with concurrent WBRT or when the no WBRT group was compared with prior WBRT. A KPS of {<=}70 predicted for poorer outcomes, with a risk ratio of 2.164 (95% confidence interval 1.157-4.049, p = 0.0157). Conclusions: Stereotactic radiosurgery to five or more brain lesions is an effective treatment option for patients with metastatic cancer, especially for patients previously treated with WBRT. A KPS of {>=}80 predicts for an improved outcome.« less

Prediction of movement intention using connectivity within motor-related network: An electrocorticography study.

PubMed

Kang, Byeong Keun; Kim, June Sic; Ryun, Seokyun; Chung, Chun Kee

2018-01-01

Most brain-machine interface (BMI) studies have focused only on the active state of which a BMI user performs specific movement tasks. Therefore, models developed for predicting movements were optimized only for the active state. The models may not be suitable in the idle state during resting. This potential maladaptation could lead to a sudden accident or unintended movement resulting from prediction error. Prediction of movement intention is important to develop a more efficient and reasonable BMI system which could be selectively operated depending on the user's intention. Physical movement is performed through the serial change of brain states: idle, planning, execution, and recovery. The motor networks in the primary motor cortex and the dorsolateral prefrontal cortex are involved in these movement states. Neuronal communication differs between the states. Therefore, connectivity may change depending on the states. In this study, we investigated the temporal dynamics of connectivity in dorsolateral prefrontal cortex and primary motor cortex to predict movement intention. Movement intention was successfully predicted by connectivity dynamics which may reflect changes in movement states. Furthermore, dorsolateral prefrontal cortex is crucial in predicting movement intention to which primary motor cortex contributes. These results suggest that brain connectivity is an excellent approach in predicting movement intention.

Geography of Genetic Structure in Barley Wild Relative Hordeum vulgare subsp. spontaneum in Jordan.

PubMed

Thormann, Imke; Reeves, Patrick; Reilley, Ann; Engels, Johannes M M; Lohwasser, Ulrike; Börner, Andreas; Pillen, Klaus; Richards, Christopher M

2016-01-01

Informed collecting, conservation, monitoring and utilization of genetic diversity requires knowledge of the distribution and structure of the variation occurring in a species. Hordeum vulgare subsp. spontaneum (K. Koch) Thell., a primary wild relative of barley, is an important source of genetic diversity for barley improvement and co-occurs with the domesticate within the center of origin. We studied the current distribution of genetic diversity and population structure in H. vulgare subsp. spontaneum in Jordan and investigated whether it is correlated with either spatial or climatic variation inferred from publically available climate layers commonly used in conservation and ecogeographical studies. The genetic structure of 32 populations collected in 2012 was analyzed with 37 SSRs. Three distinct genetic clusters were identified. Populations were characterized by admixture and high allelic richness, and genetic diversity was concentrated in the northern part of the study area. Genetic structure, spatial location and climate were not correlated. This may point out a limitation in using large scale climatic data layers to predict genetic diversity, especially as it is applied to regional genetic resources collections in H. vulgare subsp. spontaneum.

Kohn-Sham Band Structure Benchmark Including Spin-Orbit Coupling for 2D and 3D Solids

NASA Astrophysics Data System (ADS)

Huhn, William; Blum, Volker

2015-03-01

Accurate electronic band structures serve as a primary indicator of the suitability of a material for a given application, e.g., as electronic or catalytic materials. Computed band structures, however, are subject to a host of approximations, some of which are more obvious (e.g., the treatment of the exchange-correlation of self-energy) and others less obvious (e.g., the treatment of core, semicore, or valence electrons, handling of relativistic effects, or the accuracy of the underlying basis set used). We here provide a set of accurate Kohn-Sham band structure benchmarks, using the numeric atom-centered all-electron electronic structure code FHI-aims combined with the ``traditional'' PBE functional and the hybrid HSE functional, to calculate core, valence, and low-lying conduction bands of a set of 2D and 3D materials. Benchmarks are provided with and without effects of spin-orbit coupling, using quasi-degenerate perturbation theory to predict spin-orbit splittings. This work is funded by Fritz-Haber-Institut der Max-Planck-Gesellschaft.

Geography of Genetic Structure in Barley Wild Relative Hordeum vulgare subsp. spontaneum in Jordan

PubMed Central

Reeves, Patrick; Reilley, Ann; Engels, Johannes M. M.; Lohwasser, Ulrike; Börner, Andreas; Pillen, Klaus; Richards, Christopher M.

2016-01-01

Informed collecting, conservation, monitoring and utilization of genetic diversity requires knowledge of the distribution and structure of the variation occurring in a species. Hordeum vulgare subsp. spontaneum (K. Koch) Thell., a primary wild relative of barley, is an important source of genetic diversity for barley improvement and co-occurs with the domesticate within the center of origin. We studied the current distribution of genetic diversity and population structure in H. vulgare subsp. spontaneum in Jordan and investigated whether it is correlated with either spatial or climatic variation inferred from publically available climate layers commonly used in conservation and ecogeographical studies. The genetic structure of 32 populations collected in 2012 was analyzed with 37 SSRs. Three distinct genetic clusters were identified. Populations were characterized by admixture and high allelic richness, and genetic diversity was concentrated in the northern part of the study area. Genetic structure, spatial location and climate were not correlated. This may point out a limitation in using large scale climatic data layers to predict genetic diversity, especially as it is applied to regional genetic resources collections in H. vulgare subsp. spontaneum. PMID:27513459

The impact of cochlear fine structure on hearing thresholds and DPOAE levels

NASA Astrophysics Data System (ADS)

Lee, Jungmee; Long, Glenis; Talmadge, Carrick L.

2004-05-01

Although otoacoustic emissions (OAE) are used as clinical and research tools, the correlation between OAE behavioral estimates of hearing status is not large. In normal-hearing individuals, the level of OAEs can vary as much as 30 dB when the frequency is changed less than 5%. These pseudoperiodic variations of OAE level with frequency are known as fine structure. Hearing thresholds measured with high-frequency resolution reveals a similar (up to 15 dB) fine structure. We examine the impact of OAE and threshold fine structures on the prediction of auditory thresholds from OAE levels. Distortion product otoacoustic emissions (DPOAEs) were measured with sweeping primary tones. Psychoacoustic detection thresholds were measured using pure tones, sweep tones, FM tones, and narrow-band noise. Sweep DPOAE and narrow-band threshold estimates provide estimates that are less influenced by cochlear fine structure and should lead to a higher correlation between OAE levels and psychoacoustic thresholds. [Research supported by PSC CUNY, NIDCD, National Institute on Disability and Rehabilitation Research in U.S. Department of Education, and The Ministry of Education in Korea.

Predicting primary progressive aphasias with support vector machine approaches in structural MRI data.

PubMed

Bisenius, Sandrine; Mueller, Karsten; Diehl-Schmid, Janine; Fassbender, Klaus; Grimmer, Timo; Jessen, Frank; Kassubek, Jan; Kornhuber, Johannes; Landwehrmeyer, Bernhard; Ludolph, Albert; Schneider, Anja; Anderl-Straub, Sarah; Stuke, Katharina; Danek, Adrian; Otto, Markus; Schroeter, Matthias L

2017-01-01

Primary progressive aphasia (PPA) encompasses the three subtypes nonfluent/agrammatic variant PPA, semantic variant PPA, and the logopenic variant PPA, which are characterized by distinct patterns of language difficulties and regional brain atrophy. To validate the potential of structural magnetic resonance imaging data for early individual diagnosis, we used support vector machine classification on grey matter density maps obtained by voxel-based morphometry analysis to discriminate PPA subtypes (44 patients: 16 nonfluent/agrammatic variant PPA, 17 semantic variant PPA, 11 logopenic variant PPA) from 20 healthy controls (matched for sample size, age, and gender) in the cohort of the multi-center study of the German consortium for frontotemporal lobar degeneration. Here, we compared a whole-brain with a meta-analysis-based disease-specific regions-of-interest approach for support vector machine classification. We also used support vector machine classification to discriminate the three PPA subtypes from each other. Whole brain support vector machine classification enabled a very high accuracy between 91 and 97% for identifying specific PPA subtypes vs. healthy controls, and 78/95% for the discrimination between semantic variant vs. nonfluent/agrammatic or logopenic PPA variants. Only for the discrimination between nonfluent/agrammatic and logopenic PPA variants accuracy was low with 55%. Interestingly, the regions that contributed the most to the support vector machine classification of patients corresponded largely to the regions that were atrophic in these patients as revealed by group comparisons. Although the whole brain approach took also into account regions that were not covered in the regions-of-interest approach, both approaches showed similar accuracies due to the disease-specificity of the selected networks. Conclusion, support vector machine classification of multi-center structural magnetic resonance imaging data enables prediction of PPA subtypes with a very high accuracy paving the road for its application in clinical settings.

Subarachnoid hemorrhage admissions retrospectively identified using a prediction model

PubMed Central

McIntyre, Lauralyn; Fergusson, Dean; Turgeon, Alexis; dos Santos, Marlise P.; Lum, Cheemun; Chassé, Michaël; Sinclair, John; Forster, Alan; van Walraven, Carl

2016-01-01

Objective: To create an accurate prediction model using variables collected in widely available health administrative data records to identify hospitalizations for primary subarachnoid hemorrhage (SAH). Methods: A previously established complete cohort of consecutive primary SAH patients was combined with a random sample of control hospitalizations. Chi-square recursive partitioning was used to derive and internally validate a model to predict the probability that a patient had primary SAH (due to aneurysm or arteriovenous malformation) using health administrative data. Results: A total of 10,322 hospitalizations with 631 having primary SAH (6.1%) were included in the study (5,122 derivation, 5,200 validation). In the validation patients, our recursive partitioning algorithm had a sensitivity of 96.5% (95% confidence interval [CI] 93.9–98.0), a specificity of 99.8% (95% CI 99.6–99.9), and a positive likelihood ratio of 483 (95% CI 254–879). In this population, patients meeting criteria for the algorithm had a probability of 45% of truly having primary SAH. Conclusions: Routinely collected health administrative data can be used to accurately identify hospitalized patients with a high probability of having a primary SAH. This algorithm may allow, upon validation, an easy and accurate method to create validated cohorts of primary SAH from either ruptured aneurysm or arteriovenous malformation. PMID:27629096

Modal testing for model validation of structures with discrete nonlinearities.

PubMed

Ewins, D J; Weekes, B; delli Carri, A

2015-09-28

Model validation using data from modal tests is now widely practiced in many industries for advanced structural dynamic design analysis, especially where structural integrity is a primary requirement. These industries tend to demand highly efficient designs for their critical structures which, as a result, are increasingly operating in regimes where traditional linearity assumptions are no longer adequate. In particular, many modern structures are found to contain localized areas, often around joints or boundaries, where the actual mechanical behaviour is far from linear. Such structures need to have appropriate representation of these nonlinear features incorporated into the otherwise largely linear models that are used for design and operation. This paper proposes an approach to this task which is an extension of existing linear techniques, especially in the testing phase, involving only just as much nonlinear analysis as is necessary to construct a model which is good enough, or 'valid': i.e. capable of predicting the nonlinear response behaviour of the structure under all in-service operating and test conditions with a prescribed accuracy. A short-list of methods described in the recent literature categorized using our framework is given, which identifies those areas in which further development is most urgently required. © 2015 The Authors.

Modal testing for model validation of structures with discrete nonlinearities

PubMed Central

Ewins, D. J.; Weekes, B.; delli Carri, A.

2015-01-01

Model validation using data from modal tests is now widely practiced in many industries for advanced structural dynamic design analysis, especially where structural integrity is a primary requirement. These industries tend to demand highly efficient designs for their critical structures which, as a result, are increasingly operating in regimes where traditional linearity assumptions are no longer adequate. In particular, many modern structures are found to contain localized areas, often around joints or boundaries, where the actual mechanical behaviour is far from linear. Such structures need to have appropriate representation of these nonlinear features incorporated into the otherwise largely linear models that are used for design and operation. This paper proposes an approach to this task which is an extension of existing linear techniques, especially in the testing phase, involving only just as much nonlinear analysis as is necessary to construct a model which is good enough, or ‘valid’: i.e. capable of predicting the nonlinear response behaviour of the structure under all in-service operating and test conditions with a prescribed accuracy. A short-list of methods described in the recent literature categorized using our framework is given, which identifies those areas in which further development is most urgently required. PMID:26303924

Modelling and simulating the forming of new dry automated lay-up reinforcements for primary structures

NASA Astrophysics Data System (ADS)

Bouquerel, Laure; Moulin, Nicolas; Drapier, Sylvain; Boisse, Philippe; Beraud, Jean-Marc

2017-10-01

While weight has been so far the main driver for the development of prepreg based-composites solutions for aeronautics, a new weight-cost trade-off tends to drive choices for next-generation aircrafts. As a response, Hexcel has designed a new dry reinforcement type for aircraft primary structures, which combines the benefits of automation, out-of-autoclave process cost-effectiveness, and mechanical performances competitive to prepreg solutions: HiTape® is a unidirectional (UD) dry carbon reinforcement with thermoplastic veil on each side designed for aircraft primary structures [1-3]. One privileged process route for HiTape® in high volume automated processes consists in forming initially flat dry reinforcement stacks, before resin infusion [4] or injection. Simulation of the forming step aims at predicting the geometry and mechanical properties of the formed stack (so-called preform) for process optimisation. Extensive work has been carried out on prepreg and dry woven fabrics forming behaviour and simulation, but the interest for dry non-woven reinforcements has emerged more recently. Some work has been achieved on non crimp fabrics but studies on the forming behaviour of UDs are seldom and deal with UD prepregs only. Tension and bending in the fibre direction, along with inter-ply friction have been identified as the main mechanisms controlling the HiTape® response during forming. Bending has been characterised using a modified Peirce's flexometer [5] and inter-ply friction study is under development. Anisotropic hyperelastic constitutive models have been selected to represent the assumed decoupled deformation mechanisms. Model parameters are then identified from associated experimental results. For forming simulation, a continuous approach at the macroscopic scale has been selected first, and simulation is carried out in the Zset framework [6] using proper shell finite elements.

Molecular and structural assessment of alveolar bone during tooth eruption and function in the miniature pig, Sus scrofa

PubMed Central

Yeh, Kuang-Dah; Popowics, Tracy

2011-01-01

Summary The development of alveolar bone adjacent to the tooth root during tooth eruption is not well understood. This study tested the hypothesis that predominantly woven bone forms adjacent to tooth roots during tooth eruption, but that this immature structure transitions to lamellar bone when the tooth comes into function. Additionally, bone resorption was predicted to play a key role in transitioning immature bone to more mature, load-bearing tissue. Miniature pigs were compared at two occlusal stages, 13 weeks (n=3), corresponding with the mucosal penetration stage of M1 tooth eruption, and 23 weeks (n=3), corresponding with early occlusion of M1/M1. Bone samples for RNA extraction and qRT-PCR analysis were harvested from the diastema and adjacent to M1 roots on one side. Following euthanasia, bone samples for hematoxylin and eosin and TRAP staining were harvested from these regions on the other side. In contrast to expectations, both erupting and functioning molars had reticular fibrolamellar structure in alveolar bone adjacent to M1. However, the woven bone matrix in older pigs was thicker and had denser primary osteons. Gene expression data and osteoclast cell counts showed a tendency for more bone resorptive activity near the molars than at distant sites, but no differences between eruptive stages. Thus, although resorption does occur, it is not a primary mechanism in the transition in alveolar bone from eruption to function. Incremental growth of existing woven bone and filling in of primary osteons within the mineralized scaffold generated the fortification necessary to support an erupted and functioning tooth. PMID:21434979

Spatial Models for Prediction and Early Warning of Aedes aegypti Proliferation from Data on Climate Change and Variability in Cuba.

PubMed

Ortiz, Paulo L; Rivero, Alina; Linares, Yzenia; Pérez, Alina; Vázquez, Juan R

2015-04-01

Climate variability, the primary expression of climate change, is one of the most important environmental problems affecting human health, particularly vector-borne diseases. Despite research efforts worldwide, there are few studies addressing the use of information on climate variability for prevention and early warning of vector-borne infectious diseases. Show the utility of climate information for vector surveillance by developing spatial models using an entomological indicator and information on predicted climate variability in Cuba to provide early warning of danger of increased risk of dengue transmission. An ecological study was carried out using retrospective and prospective analyses of time series combined with spatial statistics. Several entomological and climatic indicators were considered using complex Bultó indices -1 and -2. Moran's I spatial autocorrelation coefficient specified for a matrix of neighbors with a radius of 20 km, was used to identify the spatial structure. Spatial structure simulation was based on simultaneous autoregressive and conditional autoregressive models; agreement between predicted and observed values for number of Aedes aegypti foci was determined by the concordance index Di and skill factor Bi. Spatial and temporal distributions of populations of Aedes aegypti were obtained. Models for describing, simulating and predicting spatial patterns of Aedes aegypti populations associated with climate variability patterns were put forward. The ranges of climate variability affecting Aedes aegypti populations were identified. Forecast maps were generated for the municipal level. Using the Bultó indices of climate variability, it is possible to construct spatial models for predicting increased Aedes aegypti populations in Cuba. At 20 x 20 km resolution, the models are able to provide warning of potential changes in vector populations in rainy and dry seasons and by month, thus demonstrating the usefulness of climate information for epidemiological surveillance.

Contrast-enhanced [18F] fluorodeoxyglucose-positron emission tomography-computed tomography as an initial imaging modality in patients presenting with metastatic malignancy of undefined primary origin.

PubMed

Jain, Avani; Srivastava, Madhur Kumar; Pawaskar, Alok Suresh; Shelley, Simon; Elangovan, Indirani; Jain, Hasmukh; Pandey, Somnath; Kalal, Shilpa; Amalachandran, Jaykanth

2015-01-01

To evaluate the advantages of contrast enhanced F-18-fluorodeoxyglucose (FDG) positron emission tomography-computed tomography (PET-contrast enhanced CT [CECT]) when used as an initial imaging modality in patients presenting with metastatic malignancy of undefined primary origin (MUO). A total of 243 patients with fine needle aspiration cytology/biopsy proven MUO were included in this prospective study. Patients who were thoroughly evaluated for primary or primary tumor was detected by any other investigation were excluded from the analysis. Totally, 163 patients with pathological diagnosis of malignancy but no apparent sites of the primary tumor were finally selected for analysis. The site of probable primary malignancy suggested by PET-CECT was confirmed by biopsy/follow-up. PET-CECT suggested probable site of primary in 128/163 (78.52%) patients. In 30/35 remaining patients, primary tumor was not detected even after extensive work-up. In 5 patients, where PET-CECT was negative, primary was found on further extensive investigations or follow-up. The sensitivity, specificity, positive predictive value and negative predictive value of the study were 95.76%, 66.67%, 88.28% and 85.71% respectively. F-18 FDG PET-CECT aptly serves the purpose of initial imaging modality owing to high sensitivity, negative and positive predictive value. PET-CECT not only surveys the whole body for the primary malignancy but also stages the disease accurately. Use of contrast improves the diagnostic utility of modality as well as help in staging of the primary tumor. Although benefits of using PET-CECT as initial diagnostic modality are obvious from this study, there is a need for a larger study comparing conventional methods for diagnosing primary in patients with MUO versus PET-CECT.

Statistical Method Based on Confidence and Prediction Regions for Analysis of Volatile Organic Compounds in Human Breath Gas

NASA Astrophysics Data System (ADS)

Wimmer, G.

2008-01-01

In this paper we introduce two confidence and two prediction regions for statistical characterization of concentration measurements of product ions in order to discriminate various groups of persons for prospective better detection of primary lung cancer. Two MATLAB algorithms have been created for more adequate description of concentration measurements of volatile organic compounds in human breath gas for potential detection of primary lung cancer and for evaluation of the appropriate confidence and prediction regions.

Statistical Relational Learning to Predict Primary Myocardial Infarction from Electronic Health Records

PubMed Central

Weiss, Jeremy C; Page, David; Peissig, Peggy L; Natarajan, Sriraam; McCarty, Catherine

2013-01-01

Electronic health records (EHRs) are an emerging relational domain with large potential to improve clinical outcomes. We apply two statistical relational learning (SRL) algorithms to the task of predicting primary myocardial infarction. We show that one SRL algorithm, relational functional gradient boosting, outperforms propositional learners particularly in the medically-relevant high recall region. We observe that both SRL algorithms predict outcomes better than their propositional analogs and suggest how our methods can augment current epidemiological practices. PMID:25360347

RNA secondary structure prediction with pseudoknots: Contribution of algorithm versus energy model.

PubMed

Jabbari, Hosna; Wark, Ian; Montemagno, Carlo

2018-01-01

RNA is a biopolymer with various applications inside the cell and in biotechnology. Structure of an RNA molecule mainly determines its function and is essential to guide nanostructure design. Since experimental structure determination is time-consuming and expensive, accurate computational prediction of RNA structure is of great importance. Prediction of RNA secondary structure is relatively simpler than its tertiary structure and provides information about its tertiary structure, therefore, RNA secondary structure prediction has received attention in the past decades. Numerous methods with different folding approaches have been developed for RNA secondary structure prediction. While methods for prediction of RNA pseudoknot-free structure (structures with no crossing base pairs) have greatly improved in terms of their accuracy, methods for prediction of RNA pseudoknotted secondary structure (structures with crossing base pairs) still have room for improvement. A long-standing question for improving the prediction accuracy of RNA pseudoknotted secondary structure is whether to focus on the prediction algorithm or the underlying energy model, as there is a trade-off on computational cost of the prediction algorithm versus the generality of the method. The aim of this work is to argue when comparing different methods for RNA pseudoknotted structure prediction, the combination of algorithm and energy model should be considered and a method should not be considered superior or inferior to others if they do not use the same scoring model. We demonstrate that while the folding approach is important in structure prediction, it is not the only important factor in prediction accuracy of a given method as the underlying energy model is also as of great value. Therefore we encourage researchers to pay particular attention in comparing methods with different energy models.

Ligatoxin B, a new cytotoxic protein with a novel helix-turn-helix DNA-binding domain from the mistletoe Phoradendron liga.

PubMed Central

Li, Shi-Sheng; Gullbo, Joachim; Lindholm, Petra; Larsson, Rolf; Thunberg, Eva; Samuelsson, Gunnar; Bohlin, Lars; Claeson, Per

2002-01-01

A new basic protein, designated ligatoxin B, containing 46 amino acid residues has been isolated from the mistletoe Phoradendron liga (Gill.) Eichl. (Viscaceae). The protein's primary structure, determined unambiguously using a combination of automated Edman degradation, trypsin enzymic digestion, and tandem MS analysis, was 1-KSCCPSTTAR-NIYNTCRLTG-ASRSVCASLS-GCKIISGSTC-DSGWNH-46. Ligatoxin B exhibited in vitro cytotoxic activities on the human lymphoma cell line U-937-GTB and the primary multidrug-resistant renal adenocarcinoma cell line ACHN, with IC50 values of 1.8 microM and 3.2 microM respectively. Sequence alignment with other thionins identified a new member of the class 3 thionins, ligatoxin B, which is similar to the earlier described ligatoxin A. As predicted by the method of homology modelling, ligatoxin B shares a three-dimensional structure with the viscotoxins and purothionins and so may have the same mode of cytotoxic action. The novel similarities observed by structural comparison of the helix-turn-helix (HTH) motifs of the thionins, including ligatoxin B, and the HTH DNA-binding proteins, led us to propose the working hypothesis that thionins represent a new group of DNA-binding proteins. This working hypothesis could be useful in further dissecting the molecular mechanisms of thionin cytotoxicity and of thionin opposition to multidrug resistance, and useful in clarifying the physiological function of thionins in plants. PMID:12049612

Drosha Promotes Splicing of a Pre-microRNA-like Alternative Exon

PubMed Central

Havens, Mallory A.; Reich, Ashley A.; Hastings, Michelle L.

2014-01-01

The ribonuclease III enzyme Drosha has a central role in the biogenesis of microRNA (miRNA) by binding and cleaving hairpin structures in primary RNA transcripts into precursor miRNAs (pre-miRNAs). Many miRNA genes are located within protein-coding host genes and cleaved by Drosha in a manner that is coincident with splicing of introns by the spliceosome. The close proximity of splicing and pre-miRNA biogenesis suggests a potential for co-regulation of miRNA and host gene expression, though this relationship is not completely understood. Here, we describe a cleavage-independent role for Drosha in the splicing of an exon that has a predicted hairpin structure resembling a Drosha substrate. We find that Drosha can cleave the alternatively spliced exon 5 of the eIF4H gene into a pre-miRNA both in vitro and in cells. However, the primary role of Drosha in eIF4H gene expression is to promote the splicing of exon 5. Drosha binds to the exon and enhances splicing in a manner that depends on RNA structure but not on cleavage by Drosha. We conclude that Drosha can function like a splicing enhancer and promote exon inclusion. Our results reveal a new mechanism of alternative splicing regulation involving a cleavage-independent role for Drosha in splicing. PMID:24786770

Structural basis for collagen recognition by the immune receptor OSCAR.

PubMed

Zhou, Long; Hinerman, Jennifer M; Blaszczyk, Michal; Miller, Jeanette L C; Conrady, Deborah G; Barrow, Alexander D; Chirgadze, Dimitri Y; Bihan, Dominique; Farndale, Richard W; Herr, Andrew B

2016-02-04

The osteoclast-associated receptor (OSCAR) is a collagen-binding immune receptor with important roles in dendritic cell maturation and activation of inflammatory monocytes as well as in osteoclastogenesis. The crystal structure of the OSCAR ectodomain is presented, both free and in complex with a consensus triple-helical peptide (THP). The structures revealed a collagen-binding site in each immunoglobulin-like domain (D1 and D2). The THP binds near a predicted collagen-binding groove in D1, but a more extensive interaction with D2 is facilitated by the unusually wide D1-D2 interdomain angle in OSCAR. Direct binding assays, combined with site-directed mutagenesis, confirm that the primary collagen-binding site in OSCAR resides in D2, in marked contrast to the related collagen receptors, glycoprotein VI (GPVI) and leukocyte-associated immunoglobulin-like receptor-1 (LAIR-1). Monomeric OSCAR D1D2 binds to the consensus THP with a KD of 28 µM measured in solution, but shows a higher affinity (KD 1.5 μM) when binding to a solid-phase THP, most likely due to an avidity effect. These data suggest a 2-stage model for the interaction of OSCAR with a collagen fibril, with transient, low-affinity interactions initiated by the membrane-distal D1, followed by firm adhesion to the primary binding site in D2. © 2016 by The American Society of Hematology.

Maintenance of polygenic sex determination in a fluctuating environment: an individual-based model.

PubMed

Bateman, A W; Anholt, B R

2017-05-01

R. A. Fisher predicted that individuals should invest equally in offspring of both sexes, and that the proportion of males and females produced (the primary sex ratio) should evolve towards 1:1 when unconstrained. For many species, sex determination is dependent on sex chromosomes, creating a strong tendency for balanced sex ratios, but in other cases, multiple autosomal genes interact to determine sex. In such cases, the maintenance of multiple sex-determining alleles at multiple loci and the consequent among-family variability in sex ratios presents a puzzle, as theory predicts that such systems should be unstable. Theory also predicts that environmental influences on sex can complicate outcomes of genetic sex determination, and that population structure may play a role. Tigriopus californicus, a copepod that lives in splash-pool metapopulations and exhibits polygenic and environment-dependent sex determination, presents a test case for relevant theory. We use this species as a model for parameterizing an individual-based simulation to investigate conditions that could maintain polygenic sex determination. We find that metapopulation structure can delay the degradation of polygenic sex determination and that periods of alternating frequency-dependent selection, imposed by seasonal fluctuations in environmental conditions, can maintain polygenic sex determination indefinitely. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

Soot Formation in Laminar Premixed Methane/Oxygen Flames at Atmospheric Pressure

NASA Technical Reports Server (NTRS)

Xu, F.; Lin, K.-C.; Faeth, G. M.

1998-01-01

Flame structure and soot formation were studied within soot-containing laminar premixed mc1hane/oxygen flames at atmospheric pressure. The following measurements were made: soot volume fractions by laser extinction, soot temperatures by multiline emission, gas temperatures (where soot was absent) by corrected fine-wire thermocouples, soot structure by thermophoretic sampling and transmission electron microscope (TEM), major gas species concentrations by sampling and gas chromatography, and gas velocities by laser velocimetry. Present measurements of gas species concentrations were in reasonably good agreement with earlier measurements due to Ramer et al. as well as predictions based on the detailed mechanisms of Frenklach and co-workers and Leung and Lindstedt: the predictions also suggest that H atom concentrations are in local thermodynamic equilibrium throughout the soot formation region. Using this information, it was found that measured soot surface growth rates could be correlated successfully by predictions based on the hydrogen-abstraction/carbon-addition (HACA) mechanisms of both Frenklach and co-workers and Colket and Hall, extending an earlier assessment of these mechanisms for premixed ethylene/air flames to conditions having larger H/C ratios and acetylene concentrations. Measured primary soot particle nucleation rates were somewhat lower than the earlier observations for laminar premixed ethylene/air flames and were significantly lower than corresponding rates in laminar diffusion flames. for reasons that still must be explained.

Soot Formation in Laminar Premixed Methane/Oxygen Flames at Atmospheric Pressure. Appendix H

NASA Technical Reports Server (NTRS)

Xu, F.; Lin, K.-C.; Faeth, G. M.; Urban, D. L. (Technical Monitor); Yuan, Z.-G. (Technical Monitor)

2001-01-01

Flame structure and soot formation were studied within soot-containing laminar premixed methanefoxygen flames at atmospheric pressure. The following measurements were made: soot volume fractions by laser extinction, soot temperatures by multiline emission, gas temperatures (where soot was absent) by corrected fine-wire thermocouples, soot structure by thermophoretic sampling and transmission electron microscope (TEM), major gas species concentrations by sampling and gas chromatography, and gas velocities by laser velocimetry. Present measurements of gas species concentrations were in reasonably good agreement with earlier measurements due to Ramer et al. as well as predictions based on the detailed mechanisms of Frenklach and co-workers and Leung and Lindstedt; the predictions also suggest that H atom concentrations are in local thermodynamic equilibrium throughout the soot formation region. Using this information, it was found that measured soot surface growth rates could be correlated successfully by predictions based on the hydrogenabstraction/carbon-addition (HACA) mechanisms of both Frenklach and co-workers and Colket and Hall, extending an earlier assessment of these mechanisms for premixed ethylene/air flames to conditions having larger H/C ratios and acetylene concentrations. Measured primary soot particle nucleation rates were somewhat lower than the earlier observations for laminar premixed ethylene/air flames and were significantly lower than corresponding rates in laminar diffusion flames, for reasons that still must be explained.

Enzymology under global change: organic nitrogen turnover in alpine and sub-Arctic soils.

PubMed

Weedon, James T; Aerts, Rien; Kowalchuk, George A; van Bodegom, Peter M

2011-01-01

Understanding global change impacts on the globally important carbon storage in alpine, Arctic and sub-Arctic soils requires knowledge of the mechanisms underlying the balance between plant primary productivity and decomposition. Given that nitrogen availability limits both processes, understanding the response of the soil nitrogen cycle to shifts in temperature and other global change factors is crucial for predicting the fate of cold biome carbon stores. Measurements of soil enzyme activities at different positions of the nitrogen cycling network are an important tool for this purpose. We review a selection of studies that provide data on potential enzyme activities across natural, seasonal and experimental gradients in cold biomes. Responses of enzyme activities to increased nitrogen availability and temperature are diverse and seasonal dynamics are often larger than differences due to experimental treatments, suggesting that enzyme expression is regulated by a combination of interacting factors reflecting both nutrient supply and demand. The extrapolation from potential enzyme activities to prediction of elemental nitrogen fluxes under field conditions remains challenging. Progress in molecular '-omics' approaches may eventually facilitate deeper understanding of the links between soil microbial community structure and biogeochemical fluxes. In the meantime, accounting for effects of the soil spatial structure and in situ variations in pH and temperature, better mapping of the network of enzymatic processes and the identification of rate-limiting steps under different conditions should advance our ability to predict nitrogen fluxes.

Personal Characteristics and Experience of Primary Care Predicting Frequent Use of Emergency Department: A Prospective Cohort Study.

PubMed

Hudon, Catherine; Sanche, Steven; Haggerty, Jeannie L

2016-01-01

A small number of patients frequently using the emergency department (ED) account for a disproportionate amount of the total ED workload and are considered using this service inappropriately. The aim of this study was to identify prospectively personal characteristics and experience of organizational and relational dimensions of primary care that predict frequent use of ED. This study was conducted among parallel cohorts of the general population and primary care patients (N = 1,769). The measures were at baseline (T1), 12 (T2) and 24 months (T3): self-administered questionnaire on current health, health behaviours and primary care experience in the previous year. Use of medical services was confirmed using administrative databases. Mixed effect logistic regression modeling identified characteristics predicting frequent ED utilization. A higher likelihood of frequent ED utilization was predicted by lower socioeconomic status, higher disease burden, lower perceived organizational accessibility, higher number of reported healthcare coordination problems and not having a complete annual check-up, above and beyond adjustment for all independent variables. Personal characteristics such as low socioeconomic status and high disease burden as well as experience of organizational dimensions of primary care such as low accessibility, high healthcare coordination problems and low comprehensiveness of care are prospectively associated with frequent ED utilization. Interventions developed to prevent inappropriate ED visits, such as case management for example, should tailor low socioeconomic status and patients with high disease burden and should aim to improve experience of primary care regarding accessibility, coordination and comprehensiveness.

Emergence of Secondary Trigger Sites after Primary Migraine Surgery.

PubMed

Punjabi, Ayesha; Brown, Matthew; Guyuron, Bahman

2016-04-01

Surgical decompression of a migraine headache may unmask headaches originating from secondary sites. A retrospective chart review investigated the incidence and characteristics of secondary trigger sites to identify clinical patterns that could aid in predicting and perhaps reducing postoperative migraines. One hundred eighty-five charts for migraine patients who underwent surgery at the senior author's (B.G.) practice were reviewed. Sites from which migraine headaches initiated or occurred independently were considered primary. The sites that were not active at the time of preoperative evaluation but became active after surgery were considered secondary. Bivariate analysis was performed to characterize postoperative migraines. Of 185 patients, 33 (17.8 percent) developed secondary migraine headache trigger sites. Of patients with primary site I (frontal) symptoms, 20.83 percent had site III (septonasal) symptoms unmasked after surgery (versus 7 percent for patients with other primary sites; p = 0.04). Of the patients with site II (temporal) migraines, 17.14 percent had secondary frontal symptoms (versus 5.68 percent; p = 0.04). Primary site II symptoms predicted postoperative site IV (occipital) symptoms (11.43 versus 1.1 percent; p = 0.008), and primary occipital symptoms predicted postoperative temporal symptoms (11.1 versus 2.33 percent; p = 0.04). The authors observed that 17.8 percent of patients develop postoperative migraine headache triggers that are not reported during the initial assessment. Knowledge of secondary migraine emergence patterns, and the presence of some preoperative symptoms, can aid in predicting the migraines that will arise from a new site postoperatively. Therapeutic, IV.

Emergent Literacy and Reading Acquisition: A Longitudinal Study from Kindergarten to Primary School

ERIC Educational Resources Information Center

Pinto, Giuliana; Bigozzi, Lucia; Vezzani, Claudio; Tarchi, Christian

2017-01-01

This study explores the predictivity of an emergent literacy model on the acquisition of reading in primary school in a language with a transparent writing system. As writing systems have different levels of transparency, results cannot be easily transferred between languages. In this study, we explored the predictivity of phonological awareness,…

Boosted food web productivity through ocean acidification collapses under warming.

PubMed

Goldenberg, Silvan U; Nagelkerken, Ivan; Ferreira, Camilo M; Ullah, Hadayet; Connell, Sean D

2017-10-01

Future climate is forecast to drive bottom-up (resource driven) and top-down (consumer driven) change to food web dynamics and community structure. Yet, our predictive understanding of these changes is hampered by an over-reliance on simplified laboratory systems centred on single trophic levels. Using a large mesocosm experiment, we reveal how future ocean acidification and warming modify trophic linkages across a three-level food web: that is, primary (algae), secondary (herbivorous invertebrates) and tertiary (predatory fish) producers. Both elevated CO 2 and elevated temperature boosted primary production. Under elevated CO 2 , the enhanced bottom-up forcing propagated through all trophic levels. Elevated temperature, however, negated the benefits of elevated CO 2 by stalling secondary production. This imbalance caused secondary producer populations to decline as elevated temperature drove predators to consume their prey more rapidly in the face of higher metabolic demand. Our findings demonstrate how anthropogenic CO 2 can function as a resource that boosts productivity throughout food webs, and how warming can reverse this effect by acting as a stressor to trophic interactions. Understanding the shifting balance between the propagation of resource enrichment and its consumption across trophic levels provides a predictive understanding of future dynamics of stability and collapse in food webs and fisheries production. © 2017 John Wiley & Sons Ltd.

The Predictive Influence of Family and Neighborhood Assets on Fighting and Weapon Carrying from Mid- to Late-Adolescence

PubMed Central

Haegerich, Tamara M.; Oman, Roy F.; Vesely, Sara K.; Aspy, Cheryl B.; Tolma, Eleni L.

2015-01-01

Using a developmental, social-ecological approach to understand the etiology of health risk behavior and inform primary prevention efforts, we assess the predictive effects of family and neighborhood social processes on youth physical fighting and weapon carrying. Specifically, we focus on relationships among youth and their parents, family communication, and parental monitoring, as well as sense of community and neighborhood informal social control, support, concerns, and disorder. This study advances knowledge through its investigation of family and neighborhood structural factors and social processes together, employment of longitudinal models that estimate effects over adolescent development, and use of self-report and observational measures. Data from 1,093 youth/parent pairs were analyzed from the Youth Assets Study using a Generalized Estimating Equation (GEE) approach; family and neighborhood assets and risks were analyzed as time-varying and lagged. Similar family assets affected physical fighting and weapon carrying, whereas different neighborhood social processes influenced the two forms of youth violence. Study findings have implications for the primary prevention of youth violence, including the use of family-based approaches that build relationships and parental monitoring skills, and community-level change approaches that promote informal social control and reduce neighborhood concerns about safety. PMID:23677457

Cold-adapted tubulins in the glacier ice worm, Mesenchytraeus solifugus.

PubMed

Tartaglia, Lawrence J; Shain, Daniel H

2008-11-01

Glacier ice worms, Mesenchytraeus solifugus and related species, are the only known annelids that survive obligately in glacier ice and snow. One fundamental component of cold temperature adaptation is the ability to polymerize tubulin, which typically depolymerizes at low physiological temperatures (e.g., <10 degrees C) in most temperate species. In this study, we isolated two alpha-tubulin (Msalpha1, Msalpha2) and two beta-tubulin (Msbeta1, Msbeta2) subunits from an ice worm cDNA library, and compared their predicted amino acid sequences with homologues from other cold-adapted organisms (e.g., Antarctic fish, ciliate) in an effort to identify species-specific amino acid substitutions that contribute to cold temperature-dependent tubulin polymerization. Our comparisons and predicted protein structures suggest that ice worm-specific amino acid substitutions stabilize lateral contact associations, particularly between beta-tubulin protofilaments, but these substitutions occur at different positions in comparison with other cold-adapted tubulins. The ice worm tubulin gene family appears relatively small, comprising one primary alpha- and one primary beta-tubulin monomers, though minor isoforms and pseudogenes were identified. Our analyses suggest that variation occurs in the strategies (i.e., species-specific amino acid substitutions, gene number) by which cold-adapted taxa have evolved the ability to polymerize tubulin at low physiological temperatures.

Round-robin analysis of the behavior of a 1:6-scale reinforced concrete containment model pressurized to failure: Posttest evaluations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Clauss, D.B.

A 1:6-scale model of a reinforced concrete containment building was pressurized incrementally to failure at a remote site at Sandia National Laboratories. The response of the model was recorded with more than 1000 channels of data (primarily strain and displacement measurements) at 37 discrete pressure levels. The primary objective of this test was to generate data that could be used to validate methods for predicting the performance of containment buildings subject to loads beyond their design basis. Extensive analyses were conducted before the test to predict the behavior of the model. Ten organizations in Europe and the US conducted independentmore » analyses of the model and contributed to a report on the pretest predictions. Predictions included structural response at certain predetermined locations in the model as well as capacity and failure mode. This report discusses comparisons between the pretest predictions and the experimental results. Posttest evaluations that were conducted to provide additional insight into the model behavior are also described. The significance of the analysis and testing of the 1:6-scale model to performance evaluations of actual containments subject to beyond design basis loads is also discussed. 70 refs., 428 figs., 24 tabs.« less

NASA's Evolutionary Xenon Thruster (NEXT) Project Qualification Propellant Throughput Milestone: Performance, Erosion, and Thruster Service Life Prediction After 450 kg

NASA Technical Reports Server (NTRS)

Herman, Daniel A.

2010-01-01

The NASA s Evolutionary Xenon Thruster (NEXT) program is tasked with significantly improving and extending the capabilities of current state-of-the-art NSTAR thruster. The service life capability of the NEXT ion thruster is being assessed by thruster wear test and life-modeling of critical thruster components, such as the ion optics and cathodes. The NEXT Long-Duration Test (LDT) was initiated to validate and qualify the NEXT thruster propellant throughput capability. The NEXT thruster completed the primary goal of the LDT; namely to demonstrate the project qualification throughput of 450 kg by the end of calendar year 2009. The NEXT LDT has demonstrated 28,500 hr of operation and processed 466 kg of xenon throughput--more than double the throughput demonstrated by the NSTAR flight-spare. Thruster performance changes have been consistent with a priori predictions. Thruster erosion has been minimal and consistent with the thruster service life assessment, which predicts the first failure mode at greater than 750 kg throughput. The life-limiting failure mode for NEXT is predicted to be loss of structural integrity of the accelerator grid due to erosion by charge-exchange ions.

Patient and practitioner characteristics predict brief alcohol intervention in primary care.

PubMed

Kaner, E F; Heather, N; Brodie, J; Lock, C A; McAvoy, B R

2001-10-01

The effectiveness of an evidence-based health care intervention depends on it being delivered consistently to appropriate patients. Brief alcohol intervention is known to be effective at reducing excessive drinking and its concomitant health and social problems. However, a recent implementation trial reported partial delivery of brief alcohol intervention by general practitioners (GPs) which is likely to have reduced its impact. To investigate patient-practitioner characteristics influencing brief alcohol intervention in primary care. Cross-sectional analysis of 12,814 completed Alcohol Use Disorders Identification Test (AUDIT) screening questionnaires. Eighty-four GPs who had implemented a brief alcohol intervention programme in a previous trial based in the Northeast of England. GPs were requested to screen all adults (aged over 16 years) presenting to their surgery and follow a structured protocol to give a brief intervention (five minutes of advice plus an information booklet) to all 'risk' drinkers. Anonymized carbon copies of the screening questionnaire were collected from all practices after a three-month implementation period. Although AUDIT identified 4080 'risk' drinkers, only 2043 (50%) received brief intervention. Risk drinkers that were most likely to receive brief intervention were males (58%), unemployed (61%), and technically-trained patients (55%). Risk drinkers that were least likely to receive brief intervention were females (44%), students (38%), and university educated patients (46%). Logistic regression modelling showed that patients' risk status was the most influential predictor of brief intervention. Also, GPs' experience of relevant training and longer average practice consultations predicted brief intervention. However, personal characteristics relating to patients and GPs also predicted brief intervention in routine practice. Interpersonal factors relating to patients and practitioners contributed to the selective provision of brief alcohol intervention in primary care. Ways should be found to remedy this situation or the impact of this evidence-based intervention may be reduced when implemented in routine practice.

Damage Tolerance Testing of a NASA TransHab Derivative Woven Inflatable Module

NASA Technical Reports Server (NTRS)

Edgecombe, John; delaFuente, Horacio; Valle, Gerard

2009-01-01

Current options for Lunar habitat architecture include inflatable habitats and airlocks. Inflatable structures can have mass and volume advantages over conventional structures. However, inflatable structures carry different inherent risks and are at a lower Technical Readiness Level (TRL) than more conventional metallic structures. One of the risks associated with inflatable structures is in understanding the tolerance to induced damage. The Damage Tolerance Test (DTT) is designed to study the structural integrity of an expandable structure. TransHab (Figure 1) was an experimental inflatable module developed at the NASA/Johnson Space Center in the 1990 s. The TransHab design was originally envisioned for use in Mars Transits but was also studied as a potential habitat for the International Space Station (ISS). The design of the TransHab module was based on a woven design using an Aramid fabric. Testing of this design demonstrated a high level of predictability and repeatability with analytical predictions of stresses and deflections. Based on JSC s experience with the design and analysis of woven inflatable structures, the Damage Tolerance Test article was designed and fabricated using a woven design. The DTT article was inflated to 45 psig, representing 25% of the ultimate burst pressure, and one of the one-inch wide longitudinal structural members was severed by initiating a Linear Shaped Charge (LSC). Strain gage measurements, at the interface between the expandable elements (straps) and the nonexpandable metallic elements for pre-selected longitudinal straps, were taken throughout pressurization of the module and strap separation. Strain gage measurements show no change in longitudinal strap loading at the bulkhead interface after strap separation indicating loads in the restraint layer were re-distributed local to the damaged area due to the effects of friction under high internal pressure loading. The test completed all primary objectives with better than expected results. This paper will discuss space inflatable structures, damage tolerance analysis, test results, and applicability to the Lunar architecture.

An accelerated non-Gaussianity based multichannel predictive deconvolution method with the limited supporting region of filters

NASA Astrophysics Data System (ADS)

Li, Zhong-xiao; Li, Zhen-chun

2016-09-01

The multichannel predictive deconvolution can be conducted in overlapping temporal and spatial data windows to solve the 2D predictive filter for multiple removal. Generally, the 2D predictive filter can better remove multiples at the cost of more computation time compared with the 1D predictive filter. In this paper we first use the cross-correlation strategy to determine the limited supporting region of filters where the coefficients play a major role for multiple removal in the filter coefficient space. To solve the 2D predictive filter the traditional multichannel predictive deconvolution uses the least squares (LS) algorithm, which requires primaries and multiples are orthogonal. To relax the orthogonality assumption the iterative reweighted least squares (IRLS) algorithm and the fast iterative shrinkage thresholding (FIST) algorithm have been used to solve the 2D predictive filter in the multichannel predictive deconvolution with the non-Gaussian maximization (L1 norm minimization) constraint of primaries. The FIST algorithm has been demonstrated as a faster alternative to the IRLS algorithm. In this paper we introduce the FIST algorithm to solve the filter coefficients in the limited supporting region of filters. Compared with the FIST based multichannel predictive deconvolution without the limited supporting region of filters the proposed method can reduce the computation burden effectively while achieving a similar accuracy. Additionally, the proposed method can better balance multiple removal and primary preservation than the traditional LS based multichannel predictive deconvolution and FIST based single channel predictive deconvolution. Synthetic and field data sets demonstrate the effectiveness of the proposed method.

Mode localization in the cooperative dynamics of protein recognition

NASA Astrophysics Data System (ADS)

Copperman, J.; Guenza, M. G.

2016-07-01

The biological function of proteins is encoded in their structure and expressed through the mediation of their dynamics. This paper presents a study on the correlation between local fluctuations, binding, and biological function for two sample proteins, starting from the Langevin Equation for Protein Dynamics (LE4PD). The LE4PD is a microscopic and residue-specific coarse-grained approach to protein dynamics, which starts from the static structural ensemble of a protein and predicts the dynamics analytically. It has been shown to be accurate in its prediction of NMR relaxation experiments and Debye-Waller factors. The LE4PD is solved in a set of diffusive modes which span a vast range of time scales of the protein dynamics, and provides a detailed picture of the mode-dependent localization of the fluctuation as a function of the primary structure of the protein. To investigate the dynamics of protein complexes, the theory is implemented here to treat the coarse-grained dynamics of interacting macromolecules. As an example, calculations of the dynamics of monomeric and dimerized HIV protease and the free Insulin Growth Factor II Receptor (IGF2R) domain 11 and its IGF2R:IGF2 complex are presented. Either simulation-derived or experimentally measured NMR conformers are used as input structural ensembles to the theory. The picture that emerges suggests a dynamical heterogeneous protein where biologically active regions provide energetically comparable conformational states that are trapped by a reacting partner in agreement with the conformation-selection mechanism of binding.

Reduced wind speed improves plant growth in a desert city.

PubMed

Bang, Christofer; Sabo, John L; Faeth, Stanley H

2010-06-10

The often dramatic effects of urbanization on community and ecosystem properties, such as primary productivity, abundances, and diversity are now well-established. In most cities local primary productivity increases and this extra energy flows upwards to alter diversity and relative abundances in higher trophic levels. The abiotic mechanisms thought to be responsible for increases in urban productivity are altered temperatures and light regimes, and increased nutrient and water inputs. However, another abiotic factor, wind speed, is also influenced by urbanization and well known for altering primary productivity in agricultural systems. Wind effects on primary productivity have heretofore not been studied in the context of urbanization. We designed a field experiment to test if increased plant growth often observed in cities is explained by the sheltering effects of built structures. Wind speed was reduced by protecting Encelia farinosa (brittlebush) plants in urban, desert remnant and outlying desert localities via windbreaks while controlling for water availability and nutrient content. In all three habitats, we compared E. farinosa growth when protected by experimental windbreaks and in the open. E. farinosa plants protected against ambient wind in the desert and remnant areas grew faster in terms of biomass and height than exposed plants. As predicted, sheltered plants did not differ from unprotected plants in urban areas where wind speed is already reduced. Our results indicate that reductions in wind speed due to built structures in cities contribute to increased plant productivity and thus also to changes in abundances and diversity of higher trophic levels. Our study emphasizes the need to incorporate wind speed in future urban ecological studies, as well as in planning for green space and sustainable cities.

Interpretation of light scattering and turbidity measurements in aggregated systems: effect of intra-cluster multiple-light scattering.

PubMed

Soos, Miroslav; Lattuada, Marco; Sefcik, Jan

2009-11-12

In this work we studied the effect of intracluster multiple-light scattering on the scattering properties of a population of fractal aggregates. To do so, experimental data of diffusion-limited aggregation for three polystyrene latexes with similar surface properties but different primary particle diameters (equal to 118, 420, and 810 nm) were obtained by static light scattering and by means of a spectrophotometer. In parallel, a population balance equation (PBE) model, which takes into account the effect of intracluster multiple-light scattering by solving the T-matrix and the mean-field version of T-matrix, was formulated and validated against time evolution of the root mean radius of gyration, , of the zero angle intensity of scattered light, I(0), and of the turbidity, tau. It was found that the mean-field version of the T-matrix theory is able to correctly predict the time evolution of all measured light scattering quantities for all sizes of primary particles without any adjustable parameter. The structure of the aggregates, characterized by fractal dimension, d(f), was independent of the primary particle size and equal to 1.7, which is in agreement with values found in literature. Since the mean-field version of the T-matrix theory used is rather complicated and requires advanced knowledge of cluster structure (i.e., the particle-particle correlation function), a simplified version of the light scattering model was proposed and tested. It was found that within the range of operating conditions investigated, the simplified version of the light scattering model was able to describe with reasonable accuracy the time evolution of all measured light scattering quantities of the cluster mass distribution (CMD) for all three sizes of primary particles and two values of the laser wavelength.

RNA-SSPT: RNA Secondary Structure Prediction Tools.

PubMed

Ahmad, Freed; Mahboob, Shahid; Gulzar, Tahsin; Din, Salah U; Hanif, Tanzeela; Ahmad, Hifza; Afzal, Muhammad

2013-01-01

The prediction of RNA structure is useful for understanding evolution for both in silico and in vitro studies. Physical methods like NMR studies to predict RNA secondary structure are expensive and difficult. Computational RNA secondary structure prediction is easier. Comparative sequence analysis provides the best solution. But secondary structure prediction of a single RNA sequence is challenging. RNA-SSPT is a tool that computationally predicts secondary structure of a single RNA sequence. Most of the RNA secondary structure prediction tools do not allow pseudoknots in the structure or are unable to locate them. Nussinov dynamic programming algorithm has been implemented in RNA-SSPT. The current studies shows only energetically most favorable secondary structure is required and the algorithm modification is also available that produces base pairs to lower the total free energy of the secondary structure. For visualization of RNA secondary structure, NAVIEW in C language is used and modified in C# for tool requirement. RNA-SSPT is built in C# using Dot Net 2.0 in Microsoft Visual Studio 2005 Professional edition. The accuracy of RNA-SSPT is tested in terms of Sensitivity and Positive Predicted Value. It is a tool which serves both secondary structure prediction and secondary structure visualization purposes.

RNA-SSPT: RNA Secondary Structure Prediction Tools

PubMed Central

Ahmad, Freed; Mahboob, Shahid; Gulzar, Tahsin; din, Salah U; Hanif, Tanzeela; Ahmad, Hifza; Afzal, Muhammad

2013-01-01

The prediction of RNA structure is useful for understanding evolution for both in silico and in vitro studies. Physical methods like NMR studies to predict RNA secondary structure are expensive and difficult. Computational RNA secondary structure prediction is easier. Comparative sequence analysis provides the best solution. But secondary structure prediction of a single RNA sequence is challenging. RNA-SSPT is a tool that computationally predicts secondary structure of a single RNA sequence. Most of the RNA secondary structure prediction tools do not allow pseudoknots in the structure or are unable to locate them. Nussinov dynamic programming algorithm has been implemented in RNA-SSPT. The current studies shows only energetically most favorable secondary structure is required and the algorithm modification is also available that produces base pairs to lower the total free energy of the secondary structure. For visualization of RNA secondary structure, NAVIEW in C language is used and modified in C# for tool requirement. RNA-SSPT is built in C# using Dot Net 2.0 in Microsoft Visual Studio 2005 Professional edition. The accuracy of RNA-SSPT is tested in terms of Sensitivity and Positive Predicted Value. It is a tool which serves both secondary structure prediction and secondary structure visualization purposes. PMID:24250115

Neural predictors of individual differences in response to math tutoring in primary-grade school children

PubMed Central

Supekar, Kaustubh; Swigart, Anna G.; Tenison, Caitlin; Jolles, Dietsje D.; Rosenberg-Lee, Miriam; Fuchs, Lynn; Menon, Vinod

2013-01-01

Now, more than ever, the ability to acquire mathematical skills efficiently is critical for academic and professional success, yet little is known about the behavioral and neural mechanisms that drive some children to acquire these skills faster than others. Here we investigate the behavioral and neural predictors of individual differences in arithmetic skill acquisition in response to 8-wk of one-to-one math tutoring. Twenty-four children in grade 3 (ages 8–9 y), a critical period for acquisition of basic mathematical skills, underwent structural and resting-state functional MRI scans pretutoring. A significant shift in arithmetic problem-solving strategies from counting to fact retrieval was observed with tutoring. Notably, the speed and accuracy of arithmetic problem solving increased with tutoring, with some children improving significantly more than others. Next, we examined whether pretutoring behavioral and brain measures could predict individual differences in arithmetic performance improvements with tutoring. No behavioral measures, including intelligence quotient, working memory, or mathematical abilities, predicted performance improvements. In contrast, pretutoring hippocampal volume predicted performance improvements. Furthermore, pretutoring intrinsic functional connectivity of the hippocampus with dorsolateral and ventrolateral prefrontal cortices and the basal ganglia also predicted performance improvements. Our findings provide evidence that individual differences in morphometry and connectivity of brain regions associated with learning and memory, and not regions typically involved in arithmetic processing, are strong predictors of responsiveness to math tutoring in children. More generally, our study suggests that quantitative measures of brain structure and intrinsic brain organization can provide a more sensitive marker of skill acquisition than behavioral measures. PMID:23630286

Neural predictors of individual differences in response to math tutoring in primary-grade school children.

PubMed

Supekar, Kaustubh; Swigart, Anna G; Tenison, Caitlin; Jolles, Dietsje D; Rosenberg-Lee, Miriam; Fuchs, Lynn; Menon, Vinod

2013-05-14

Now, more than ever, the ability to acquire mathematical skills efficiently is critical for academic and professional success, yet little is known about the behavioral and neural mechanisms that drive some children to acquire these skills faster than others. Here we investigate the behavioral and neural predictors of individual differences in arithmetic skill acquisition in response to 8-wk of one-to-one math tutoring. Twenty-four children in grade 3 (ages 8-9 y), a critical period for acquisition of basic mathematical skills, underwent structural and resting-state functional MRI scans pretutoring. A significant shift in arithmetic problem-solving strategies from counting to fact retrieval was observed with tutoring. Notably, the speed and accuracy of arithmetic problem solving increased with tutoring, with some children improving significantly more than others. Next, we examined whether pretutoring behavioral and brain measures could predict individual differences in arithmetic performance improvements with tutoring. No behavioral measures, including intelligence quotient, working memory, or mathematical abilities, predicted performance improvements. In contrast, pretutoring hippocampal volume predicted performance improvements. Furthermore, pretutoring intrinsic functional connectivity of the hippocampus with dorsolateral and ventrolateral prefrontal cortices and the basal ganglia also predicted performance improvements. Our findings provide evidence that individual differences in morphometry and connectivity of brain regions associated with learning and memory, and not regions typically involved in arithmetic processing, are strong predictors of responsiveness to math tutoring in children. More generally, our study suggests that quantitative measures of brain structure and intrinsic brain organization can provide a more sensitive marker of skill acquisition than behavioral measures.

Physical Fitness and Aortic Stiffness Explain the Reduced Cognitive Performance Associated with Increasing Age in Older People.

PubMed

Kennedy, Greg; Meyer, Denny; Hardman, Roy J; Macpherson, Helen; Scholey, Andrew B; Pipingas, Andrew

2018-01-01

Greater physical fitness is associated with reduced rates of cognitive decline in older people; however, the mechanisms by which this occurs are still unclear. One potential mechanism is aortic stiffness, with increased stiffness resulting in higher pulsatile pressures reaching the brain and possibly causing progressive micro-damage. There is limited evidence that those who regularly exercise may have lower aortic stiffness. To investigate whether greater fitness and lower aortic stiffness predict better cognitive performance in older people and, if so, whether aortic stiffness mediates the relationship between fitness and cognition. Residents of independent living facilities, aged 60-90, participated in the study (N = 102). Primary measures included a computerized cognitive assessment battery, pulse wave velocity analysis to measure aortic stiffness, and the Six-Minute Walk test to assess fitness. Based on hierarchical regression analyses, structural equation modelling was used to test the mediation hypothesis. Both fitness and aortic stiffness independently predicted Spatial Working Memory (SWM) performance, however no mediating relationship was found. Additionally, the derived structural equation model shows that, in conjunction with BMI and sex, fitness and aortic stiffness explain 33% of the overall variation in SWM, with age no longer directly predicting any variation. Greater fitness and lower aortic stiffness both independently predict better SWM in older people. The strong effect of age on cognitive performance is totally mediated by fitness and aortic stiffness. This suggests that addressing both physical fitness and aortic stiffness may be important to reduce the rate of age associated cognitive decline.

Personality domains and traits that predict self-reported aberrant driving behaviours in a southeastern US university sample.

PubMed

Beanland, Vanessa; Sellbom, Martin; Johnson, Alexandria K

2014-11-01

Personality traits are meaningful predictors of many significant life outcomes, including mortality. Several studies have investigated the relationship between specific personality traits and driving behaviours, e.g., aggression and speeding, in an attempt to identify traits associated with elevated crash risk. These studies, while valuable, are limited in that they examine only a narrow range of personality constructs and thus do not necessarily reveal which traits in constellation best predict aberrant driving behaviours. The primary aim of this study was to use a comprehensive measure of personality to investigate which personality traits are most predictive of four types of aberrant driving behaviour (Aggressive Violations, Ordinary Violations, Errors, Lapses) as indicated by the Manchester Driver Behaviour Questionnaire (DBQ). We recruited 285 young adults (67% female) from a university in the southeastern US. They completed self-report questionnaires including the DBQ and the Personality Inventory for DSM-5, which indexes 5 broad personality domains (Antagonism, Detachment, Disinhibition, Negative Affectivity, Psychoticism) and 25 specific trait facets. Confirmatory factor analysis showed adequate evidence for the DBQ internal structure. Structural regression analyses revealed that the personality domains of Antagonism and Negative Affectivity best predicted both Aggressive Violations and Ordinary Violations, whereas the best predictors of both Errors and Lapses were Negative Affectivity, Disinhibition and to a lesser extent Antagonism. A more nuanced analysis of trait facets revealed that Hostility was the best predictor of Aggressive Violations; Risk-taking and Hostility of Ordinary Violations; Irresponsibility, Separation Insecurity and Attention Seeking of Errors; and Perseveration and Irresponsibility of Lapses. Copyright © 2014 Elsevier Ltd. All rights reserved.

A new biodegradation prediction model specific to petroleum hydrocarbons.

PubMed

Howard, Philip; Meylan, William; Aronson, Dallas; Stiteler, William; Tunkel, Jay; Comber, Michael; Parkerton, Thomas F

2005-08-01

A new predictive model for determining quantitative primary biodegradation half-lives of individual petroleum hydrocarbons has been developed. This model uses a fragment-based approach similar to that of several other biodegradation models, such as those within the Biodegradation Probability Program (BIOWIN) estimation program. In the present study, a half-life in days is estimated using multiple linear regression against counts of 31 distinct molecular fragments. The model was developed using a data set consisting of 175 compounds with environmentally relevant experimental data that was divided into training and validation sets. The original fragments from the Ministry of International Trade and Industry BIOWIN model were used initially as structural descriptors and additional fragments were then added to better describe the ring systems found in petroleum hydrocarbons and to adjust for nonlinearity within the experimental data. The training and validation sets had r2 values of 0.91 and 0.81, respectively.

Theoretical model of impact damage in structural ceramics

NASA Technical Reports Server (NTRS)

Liaw, B. M.; Kobayashi, A. S.; Emery, A. G.

1984-01-01

This paper presents a mechanistically consistent model of impact damage based on elastic failures due to tensile and shear overloading. An elastic axisymmetric finite element model is used to determine the dynamic stresses generated by a single particle impact. Local failures in a finite element are assumed to occur when the primary/secondary principal stresses or the maximum shear stress reach critical tensile or shear stresses, respectively. The succession of failed elements thus models macrocrack growth. Sliding motions of cracks, which closed during unloading, are resisted by friction and the unrecovered deformation represents the 'plastic deformation' reported in the literature. The predicted ring cracks on the contact surface, as well as the cone cracks, median cracks, radial cracks, lateral cracks, and damage-induced porous zones in the interior of hot-pressed silicon nitride plates, matched those observed experimentally. The finite element model also predicted the uplifting of the free surface surrounding the impact site.

Performance Enhancements Under Dual-task Conditions

NASA Technical Reports Server (NTRS)

Kramer, A. F.; Wickens, C. D.; Donchin, E.

1984-01-01

Research on dual-task performance has been concerned with delineating the antecedent conditions which lead to dual-task decrements. Capacity models of attention, which propose that a hypothetical resource structure underlies performance, have been employed as predictive devices. These models predict that tasks which require different processing resources can be more successfully time shared than tasks which require common resources. The conditions under which such dual-task integrality can be fostered were assessed in a study in which three factors likely to influence the integrality between tasks were manipulated: inter-task redundancy, the physical proximity of tasks and the task relevant objects. Twelve subjects participated in three experimental sessions in which they performed both single and dual-tasks. The primary task was a pursuit step tracking task. The secondary tasks required the discrimination between different intensities or different spatial positions of a stimulus. The results are discussed in terms of a model of dual-task integrality.

CFD Predictions for Transonic Performance of the ERA Hybrid Wing-Body Configuration

NASA Technical Reports Server (NTRS)

Deere, Karen A.; Luckring, James M.; McMillin, S. Naomi; Flamm, Jeffrey D.; Roman, Dino

2016-01-01

A computational study was performed for a Hybrid Wing Body configuration that was focused at transonic cruise performance conditions. In the absence of experimental data, two fully independent computational fluid dynamics analyses were conducted to add confidence to the estimated transonic performance predictions. The primary analysis was performed by Boeing with the structured overset-mesh code OVERFLOW. The secondary analysis was performed by NASA Langley Research Center with the unstructured-mesh code USM3D. Both analyses were performed at full-scale flight conditions and included three configurations customary to drag buildup and interference analysis: a powered complete configuration, the configuration with the nacelle/pylon removed, and the powered nacelle in isolation. The results in this paper are focused primarily on transonic performance up to cruise and through drag rise. Comparisons between the CFD results were very good despite some minor geometric differences in the two analyses.

Sensory experience modifies feature map relationships in visual cortex

PubMed Central

Cloherty, Shaun L; Hughes, Nicholas J; Hietanen, Markus A; Bhagavatula, Partha S

2016-01-01

The extent to which brain structure is influenced by sensory input during development is a critical but controversial question. A paradigmatic system for studying this is the mammalian visual cortex. Maps of orientation preference (OP) and ocular dominance (OD) in the primary visual cortex of ferrets, cats and monkeys can be individually changed by altered visual input. However, the spatial relationship between OP and OD maps has appeared immutable. Using a computational model we predicted that biasing the visual input to orthogonal orientation in the two eyes should cause a shift of OP pinwheels towards the border of OD columns. We then confirmed this prediction by rearing cats wearing orthogonally oriented cylindrical lenses over each eye. Thus, the spatial relationship between OP and OD maps can be modified by visual experience, revealing a previously unknown degree of brain plasticity in response to sensory input. DOI: http://dx.doi.org/10.7554/eLife.13911.001 PMID:27310531

Kindergarten Predictors of Third Grade Writing

PubMed Central

Kim, Young-Suk; Al Otaiba, Stephanie; Wanzek, Jeanne

2015-01-01

The primary goal of the present study was to examine the relations of kindergarten transcription, oral language, word reading, and attention skills to writing skills in third grade. Children (N = 157) were assessed on their letter writing automaticity, spelling, oral language, word reading, and attention in kindergarten. Then, they were assessed on writing in third grade using three writing tasks – one narrative and two expository prompts. Children’s written compositions were evaluated in terms of writing quality (the extent to which ideas were developed and presented in an organized manner). Structural equation modeling showed that kindergarten oral language and lexical literacy skills (i.e., word reading and spelling) were independently predicted third grade narrative writing quality, and kindergarten literacy skill uniquely predicted third grade expository writing quality. In contrast, attention and letter writing automaticity were not directly related to writing quality in either narrative or expository genre. These results are discussed in light of theoretical and practical implications. PMID:25642118

Molecular cloning and characterization of chitinase genes from Candida albicans.

PubMed

McCreath, K J; Specht, C A; Robbins, P W

1995-03-28

Chitinase (EC 3.2.1.14) is an important enzyme for the remodeling of chitin in the cell wall of fungi. We have cloned three chitinase genes (CHT1, CHT2, and CHT3) from the dimorphic human pathogen Candida albicans. CHT2 and CHT3 have been sequenced in full and their primary structures have been analyzed: CHT2 encodes a protein of 583 aa with a predicted size of 60.8 kDa; CHT3 encodes a protein of 567 aa with a predicted size of 60 kDa. All three genes show striking similarity to other chitinase genes in the literature, especially in the proposed catalytic domain. Transcription of CHT2 and CHT3 was greater when C. albicans was grown in a yeast phase as compared to a mycelial phase. A transcript of CHT1 could not be detected in either growth condition.

A Business Analytics Software Tool for Monitoring and Predicting Radiology Throughput Performance.

PubMed

Jones, Stephen; Cournane, Seán; Sheehy, Niall; Hederman, Lucy

2016-12-01

Business analytics (BA) is increasingly being utilised by radiology departments to analyse and present data. It encompasses statistical analysis, forecasting and predictive modelling and is used as an umbrella term for decision support and business intelligence systems. The primary aim of this study was to determine whether utilising BA technologies could contribute towards improved decision support and resource management within radiology departments. A set of information technology requirements were identified with key stakeholders, and a prototype BA software tool was designed, developed and implemented. A qualitative evaluation of the tool was carried out through a series of semi-structured interviews with key stakeholders. Feedback was collated, and emergent themes were identified. The results indicated that BA software applications can provide visibility of radiology performance data across all time horizons. The study demonstrated that the tool could potentially assist with improving operational efficiencies and management of radiology resources.

Are hypomineralised lesions on second primary molars (HSPM) a predictive sign of molar incisor hypomineralisation (MIH)? A systematic review and a meta-analysis.

PubMed

Garot, Elsa; Denis, Alice; Delbos, Yves; Manton, David; Silva, Mihiri; Rouas, Patrick

2018-05-01

Molar Incisor Hypomineralisation (MIH) and Hypomineralised Second Primary Molars (HSPM) involve qualitative structural developmental anomalies of tooth enamel affecting the first permanent molars (and often incisors) and the second primary molars, respectively. A putative relationship between HSPM and MIH has been reported in the scientific literature. The aim was to determine whether children with HSPM are more likely to develop MIH. A systematic search using PubMed/Medline, Embase and Cochrane Library electronic databases for publications from 2001 to August 2017 investigating the link between MIH and HSPM was undertaken. Four reviewers selected the studies independently, extracted the data according to PRISMA statement, and assessed the bias risk with the Newcastle-Ottawa Scale (NOS) criteria. From 645 potentially eligible studies, 14 were selected for full text analysis and 5 were included in the meta-analysis. Cross-sectional and cohort studies were reported and 4662 participants were included. The meta-analyses were performed with a random model calculated an OR total of 4.66 (95% CI 2.11-10.26; P < 0.001). The weighted mean of the co-occurrence of HSPM and MIH prevalence was 19.94%. The high heterogeneity (I 2  = 88%) can be explained by the great variation present in number of participants and variable caries risk. Despite the limitations of the study, the presence of HSPM is predictive for MIH, with greater MIH prevalence in the presence of mild HSPM. Early detection and preventive intervention could reduce MIH complications. Copyright © 2018 Elsevier Ltd. All rights reserved.

STRUCTURAL AND HIDDEN BARRIERS TO A LOCAL PRIMARY HEALTH CARE INFRASTRUCTURE: AUTONOMY, DECISIONS ABOUT PRIMARY HEALTH CARE, AND THE CENTRALITY AND SIGNIFICANCE OF POWER.

PubMed

Freed, Christopher R; Hansberry, Shantisha T; Arrieta, Martha I

2013-09-01

To examine a local primary health care infrastructure and the reality of primary health care from the perspective of residents of a small, urban community in the southern United States. Data derive from 13 semi-structured focus groups, plus three semi-structured interviews, and were analyzed inductively consistent with a grounded theory approach. Structural barriers to the local primary health care infrastructure include transportation, clinic and appointment wait time, and co-payments and health insurance. Hidden barriers consist of knowledge about local health care services, non-physician gatekeepers, and fear of medical care. Community residents have used home remedies and the emergency department at the local academic medical center to manage these structural and hidden barriers. Findings might not generalize to primary health care infrastructures in other communities, respondent perspectives can be biased, and the data are subject to various interpretations and conceptual and thematic frameworks. Nevertheless, the structural and hidden barriers to the local primary health care infrastructure have considerably diminished the autonomy community residents have been able to exercise over their decisions about primary health care, ultimately suggesting that efforts concerned with increasing the access of medically underserved groups to primary health care in local communities should recognize the centrality and significance of power. This study addresses a gap in the sociological literature regarding the impact of specific barriers to primary health care among medically underserved groups.

Primary mirror and mount technology for the Stratospheric Observatory for Infrared Astronomy (SOFIA) telescope

NASA Technical Reports Server (NTRS)

Melugin, Ramsey K.; Chang, L. S.; Mansfield, J. A.; Howard, Steven D.

1989-01-01

Candidate technologies for a lightweight primary mirror for the SOFIA telescope are evaluated for both mirror blank fabrication and polishing. Two leading candidates for the type mirror blank are considered: the frit-bonded, structured form, and the thin meniscus form. The feasible mirror is required to be very lightweight with an areal density of approximately 100 kg/sq m, have an f/ratio near 1.0, and have surface quality that permits imaging in the visible as well as the infrared. Also considered are the results of a study conducted to assess the feasibility of designing a suitable mounting system for the primary mirror. The requirements for the mount design are given both in terms of the environmental conditions and the expected optical performance. PATRAN and NASTRAN programs are used to model mirror and mounting. The sandwich-type mirror made of ultra low expansion silica with square cells in the core, is modeled using equivalent solid elements for the core. The design study produces primary mirror surface deflections in 1g as a function of mirror elevation angles. The surface is analyzed using an optical analysis program, FRINGE, to give a prediction of the mirror optical performance. Results from this analysis are included.

Evaluation of Ground-Motion Modeling Techniques for Use in Global ShakeMap - A Critique of Instrumental Ground-Motion Prediction Equations, Peak Ground Motion to Macroseismic Intensity Conversions, and Macroseismic Intensity Predictions in Different Tectonic Settings

USGS Publications Warehouse

Allen, Trevor I.; Wald, David J.

2009-01-01

Regional differences in ground-motion attenuation have long been thought to add uncertainty in the prediction of ground motion. However, a growing body of evidence suggests that regional differences in ground-motion attenuation may not be as significant as previously thought and that the key differences between regions may be a consequence of limitations in ground-motion datasets over incomplete magnitude and distance ranges. Undoubtedly, regional differences in attenuation can exist owing to differences in crustal structure and tectonic setting, and these can contribute to differences in ground-motion attenuation at larger source-receiver distances. Herein, we examine the use of a variety of techniques for the prediction of several ground-motion metrics (peak ground acceleration and velocity, response spectral ordinates, and macroseismic intensity) and compare them against a global dataset of instrumental ground-motion recordings and intensity assignments. The primary goal of this study is to determine whether existing ground-motion prediction techniques are applicable for use in the U.S. Geological Survey's Global ShakeMap and Prompt Assessment of Global Earthquakes for Response (PAGER). We seek the most appropriate ground-motion predictive technique, or techniques, for each of the tectonic regimes considered: shallow active crust, subduction zone, and stable continental region.

A group evolving-based framework with perturbations for link prediction

NASA Astrophysics Data System (ADS)

Si, Cuiqi; Jiao, Licheng; Wu, Jianshe; Zhao, Jin

2017-06-01

Link prediction is a ubiquitous application in many fields which uses partially observed information to predict absence or presence of links between node pairs. The group evolving study provides reasonable explanations on the behaviors of nodes, relations between nodes and community formation in a network. Possible events in group evolution include continuing, growing, splitting, forming and so on. The changes discovered in networks are to some extent the result of these events. In this work, we present a group evolving-based characterization of node's behavioral patterns, and via which we can estimate the probability they tend to interact. In general, the primary aim of this paper is to offer a minimal toy model to detect missing links based on evolution of groups and give a simpler explanation on the rationality of the model. We first introduce perturbations into networks to obtain stable cluster structures, and the stable clusters determine the stability of each node. Then fluctuations, another node behavior, are assumed by the participation of each node to its own belonging group. Finally, we demonstrate that such characteristics allow us to predict link existence and propose a model for link prediction which outperforms many classical methods with a decreasing computational time in large scales. Encouraging experimental results obtained on real networks show that our approach can effectively predict missing links in network, and even when nearly 40% of the edges are missing, it also retains stationary performance.

An examination of the factors affecting people's participation in future health examinations based on community health exam interventions.

PubMed

Tu, Shih-Kai; Liao, Hung-En

2014-01-01

Community-based intervention health examinations were implemented at a health care facility to comply with the government's primary health care promotion policy. The theory of planned behavior model was applied to examine the effect that community-based health examinations had on people's health concepts regarding seeking future health examinations. The research participants were individuals who had received a health examination provided at two branches of a hospital in central Taiwan in 2012. The hospital's two branches held a total of 14 free community-based health examination sessions. The hospital provided health examination equipment and staff to perform health examinations during public holidays. We conducted an exploratory questionnaire survey to collect data and implemented cross-sectional research based on anonymous self-ratings to examine the public's intention to receive future community-based or hospital-based health examinations. Including of 807 valid questionnaires, accounting for 89.4% of the total number of questionnaires distributed. The correlation coefficients of the second-order structural model indicate that attitudes positively predict behavioral intentions (γ = .66, p < .05), and subjective norms also positively predict behavioral intentions (γ = .66, p < .01). By contrast, perceived behavioral control has no significant relationship with behavioral intentions (γ = -.71, p > .05). The results of the first-order structural model indicated that the second-order constructs had a high explanatory power for the first-order constructs. People's health concepts regarding health examinations and their desire to continue receiving health examinations must be considered when promoting health examinations in the community. Regarding hospital management and the government's implementation of primary health care, health examination services should address people's medical needs to increase coverage and participation rates and reduce the waste of medical resources.

Stress-Induced Accumulation of DcAOX1 and DcAOX2a Transcripts Coincides with Critical Time Point for Structural Biomass Prediction in Carrot Primary Cultures (Daucus carota L.)

PubMed Central

Campos, M. Doroteia; Nogales, Amaia; Cardoso, Hélia G.; Kumar, Sarma R.; Nobre, Tânia; Sathishkumar, Ramalingam; Arnholdt-Schmitt, Birgit

2016-01-01

Stress-adaptive cell plasticity in target tissues and cells for plant biomass growth is important for yield stability. In vitro systems with reproducible cell plasticity can help to identify relevant metabolic and molecular events during early cell reprogramming. In carrot, regulation of the central root meristem is a critical target for yield-determining secondary growth. Calorespirometry, a tool previously identified as promising for predictive growth phenotyping has been applied to measure the respiration rate in carrot meristem. In a carrot primary culture system (PCS), this tool allowed identifying an early peak related with structural biomass formation during lag phase of growth, around the 4th day of culture. In the present study, we report a dynamic and correlated expression of carrot AOX genes (DcAOX1 and DcAOX2a) during PCS lag phase and during exponential growth. Both genes showed an increase in transcript levels until 36 h after explant inoculation, and a subsequent down-regulation, before the initiation of exponential growth. In PCS growing at two different temperatures (21°C and 28°C), DcAOX1 was also found to be more expressed in the highest temperature. DcAOX genes’ were further explored in a plant pot experiment in response to chilling, which confirmed the early AOX transcript increase prior to the induction of a specific anti-freezing gene. Our findings point to DcAOX1 and DcAOX2a as being reasonable candidates for functional marker development related to early cell reprogramming. While the genomic sequence of DcAOX2a was previously described, we characterize here the complete genomic sequence of DcAOX1. PMID:26858746

Comparison of diagnostic capability of macular ganglion cell complex and retinal nerve fiber layer among primary open angle glaucoma, ocular hypertension, and normal population using Fourier-domain optical coherence tomography and determining their functional correlation in Indian population

PubMed Central

Barua, Nabanita; Sitaraman, Chitra; Goel, Sonu; Chakraborti, Chandana; Mukherjee, Sonai; Parashar, Hemandra

2016-01-01

Context: Analysis of diagnostic ability of macular ganglionic cell complex and retinal nerve fiber layer (RNFL) in glaucoma. Aim: To correlate functional and structural parameters and comparing predictive value of each of the structural parameters using Fourier-domain (FD) optical coherence tomography (OCT) among primary open angle glaucoma (POAG) and ocular hypertension (OHT) versus normal population. Setting and Design: Single centric, cross-sectional study done in 234 eyes. Materials and Methods: Patients were enrolled in three groups: POAG, ocular hypertensive and normal (40 patients in each group). After comprehensive ophthalmological examination, patients underwent standard automated perimetry and FD-OCT scan in optic nerve head and ganglion cell mode. The relationship was assessed by correlating ganglion cell complex (GCC) parameters with mean deviation. Results were compared with RNFL parameters. Statistical Analysis: Data were analyzed with SPSS, analysis of variance, t-test, Pearson's coefficient, and receiver operating curve. Results: All parameters showed strong correlation with visual field (P < 0.001). Inferior GCC had highest area under curve (AUC) for detecting glaucoma (0.827) in POAG from normal population. However, the difference was not statistically significant (P > 0.5) when compared with other parameters. None of the parameters showed significant diagnostic capability to detect OHT from normal population. In diagnosing early glaucoma from OHT and normal population, only inferior GCC had statistically significant AUC value (0.715). Conclusion: In this study, GCC and RNFL parameters showed equal predictive capability in perimetric versus normal group. In early stage, inferior GCC was the best parameter. In OHT population, single day cross-sectional imaging was not valuable. PMID:27221682

Ontogenetic functional diversity: size structure of a keystone predator drives functioning of a complex ecosystem.

PubMed

Rudolf, Volker H W; Rasmussen, Nick L

2013-05-01

A central challenge in community ecology is to understand the connection between biodiversity and the functioning of ecosystems. While traditional approaches have largely focused on species-level diversity, increasing evidence indicates that there exists substantial ecological diversity among individuals within species. By far, the largest source of this intraspecific diversity stems from variation among individuals in ontogenetic stage and size. Although such ontogenetic shifts are ubiquitous in natural communities, whether and how they scale up to influence the structure and functioning of complex ecosystems is largely unknown. Here we take an experimental approach to examine the consequences of ontogenetic niche shifts for the structure of communities and ecosystem processes. In particular we experimentally manipulated the stage structure in a keystone predator, larvae of the dragonfly Anax junius, in complex experimental pond communities to test whether changes in the population stage or size structure of a keystone species scale up to alter community structure and ecosystem processes, and how functional differences scale with relative differences in size among stages. We found that the functional role of A. junius was stage-specific. Altering what stages were present in a pond led to concurrent changes in community structure, primary producer biomass (periphyton and phytoplankton), and ultimately altered ecosystem processes (respiration and net primary productivity), indicating a strong, but stage-specific, trophic cascade. Interestingly, the stage-specific effects did not simply scale with size or biomass of the predator, but instead indicated clear ontogenetic niche shifts in ecological interactions. Thus, functional differences among stages within a keystone species scaled up to alter the functioning of entire ecosystems. Therefore, our results indicate that the classical approach of assuming an average functional role of a species can be misleading because functional roles are dynamic and will change with shifts in the stage structure of the species. In general this emphasizes the importance of accounting for functional diversity below the species level to predict how natural and anthropogenic changes alter the functioning of natural ecosystems.

Predicting high school truancy among students in the Appalachian south.

PubMed

Hunt, Melissa K; Hopko, Derek R

2009-09-01

Truancy is a considerable problem among adolescents. Considering the historical emphasis on studying truancy in urban regions, a concerted effort is needed to extend this research into rural areas to examine cultural generalizability of findings. The purpose of this study was to assess variables associated with truancy in a rural sample (N = 367) of students attending high school in a southern rural region of the Appalachian Mountains. The primary objective was to assess the relative predictive strength of the following variables: academic performance, religiosity, environmental factors (family structure, parental education, and adolescent perceptions of family functioning), internalizing problems (anxiety, depression, thought problems, attentional problems), externalizing problems (substance use and rule-breaking behaviors), and prosocial overt behaviors (participation in school and leadership activities). Regression analysis indicated that truancy was significantly associated with poor school performance, increased depression, social problems, having a less educated mother, a less structured home environment, higher grade, and decreased participation in school sports. EDITORS' STRATEGIC IMPLICATIONS: These findings are critical for the understanding of truancy in rural areas, and they highlight contextual factors that must be identified and addressed through systematic prevention programs targeting adolescents at risk for truancy.

Motor pathway convergence predicts syllable repertoire size in oscine birds

PubMed Central

Moore, Jordan M.; Székely, Tamás; Büki, József; DeVoogd, Timothy J.

2011-01-01

Behavioral specializations are frequently associated with expansions of the brain regions controlling them. This principle of proper mass spans sensory, motor, and cognitive abilities and has been observed in a wide variety of vertebrate species. Yet, it is unknown if this concept extrapolates to entire neural pathways or how selection on a behavioral capacity might otherwise shape circuit structure. We investigate these questions by comparing the songs and neuroanatomy of 49 species from 17 families of songbirds, which vary immensely in the number of unique song components they produce and possess a conserved neural network dedicated to this behavior. We find that syllable repertoire size is strongly related to the degree of song motor pathway convergence. Repertoire size is more accurately predicted by the number of neurons in higher motor areas relative to that in their downstream targets than by the overall number of neurons in the song motor pathway. Additionally, the convergence values along serial premotor and primary motor projections account for distinct portions of the behavioral variation. These findings suggest that selection on song has independently shaped different components of this hierarchical pathway, and they elucidate how changes in pathway structure could have underlain elaborations of this learned motor behavior. PMID:21918109

Macrodamage Accumulation Model for a Human Femur

PubMed Central

2017-01-01

The objective of this study was to more fully understand the mechanical behavior of bone tissue that is important to find an alternative material to be used as an implant and to develop an accurate model to predict the fracture of the bone. Predicting and preventing bone failure is an important area in orthopaedics. In this paper, the macrodamage accumulation models in the bone tissue have been investigated. Phenomenological models for bone damage have been discussed in detail. In addition, 3D finite element model of the femur prepared from imaging data with both cortical and trabecular structures is delineated using MIMICS and ANSYS® and simulated as a composite structure. The damage accumulation occurring during cyclic loading was analyzed for fatigue scenario. We found that the damage accumulates sooner in the multiaxial than in the uniaxial loading condition for the same number of cycles, and the failure starts in the cortical bone. The damage accumulation behavior seems to follow a three-stage growth: a primary phase, a secondary phase of damage growth marked by linear damage growth, and a tertiary phase that leads to failure. Finally, the stiffness of the composite bone comprising the cortical and trabecular bone was significantly different as expected. PMID:28951659

Small-scale spatial variability in phylogenetic community structure during early plant succession depends on soil properties.

PubMed

Ulrich, Werner; Piwczyński, Marcin; Zaplata, Markus Klemens; Winter, Susanne; Schaaf, Wolfgang; Fischer, Anton

2014-07-01

During early plant succession, the phylogenetic structure of a community changes in response to important environmental filters and emerging species interactions. We traced the development of temperate-zone plant communities during the first 7 years of primary succession on catchment soils to explore patterns of initial species assembly. We found pronounced small-scale differences in the phylogenetic composition of neighbouring plant assemblages and a large-scale trend towards phylogenetic evenness. This small-scale variability appears to be mediated by soil properties, particularly carbonate content. Therefore, abiotic environmental conditions might counteract or even supersede the effects of interspecific competition among closely related species, which are usually predicted to exhibit patterns of phylogenetic evenness. We conclude that theories on phylogenetic community composition need to incorporate effects of small-scale variability of environmental factors.

Multilevel Assessment of the Predictive Validity of Teacher Made Tests in the Zimbabwean Primary Education Sector

ERIC Educational Resources Information Center

Machingambi, Zadzisai

2017-01-01

The principal focus of this study was to undertake a multilevel assessment of the predictive validity of teacher made tests in the Zimbabwean primary education sector. A correlational research design was adopted for the study, mainly to allow for statistical treatment of data and subsequent classical hypotheses testing using the spearman's rho.…

Intrinsic Motivation and Its Determinants as Factors Enhancing the Prediction of Job Performance from Ability. Research Report No. 11.

ERIC Educational Resources Information Center

Howard, Ann

The primary purpose of the present research was to explore the relationship of ability and intrinsic motivation in the prediction of job performance. Intrinsic motivation was traced to two primary determinants. One, an organizational factor, is the extent to which an employee's job is "enriched," or incorporates challenging elements such as…

The Role of Socio-Cognitive Variables in Predicting Learning Satisfaction in Smart Schools

ERIC Educational Resources Information Center

Firoozi, Mohammad Reza; Kazemi, Ali; Jokar, Maryam

2017-01-01

The present study aimed to investigate the role of Socio-Cognitive variables in predicting learning satisfaction in Smart Schools. The population was all the primary school students studying in smart schools in the city of Shiraz in the school year 2014-2015. The sample, randomly chosen through multi-stage cluster sampling, was 383 primary school…

Amino acid pair- and triplet-wise groupings in the interior of α-helical segments in proteins.

PubMed

de Sousa, Miguel M; Munteanu, Cristian R; Pazos, Alejandro; Fonseca, Nuno A; Camacho, Rui; Magalhães, A L

2011-02-21

A statistical approach has been applied to analyse primary structure patterns at inner positions of α-helices in proteins. A systematic survey was carried out in a recent sample of non-redundant proteins selected from the Protein Data Bank, which were used to analyse α-helix structures for amino acid pairing patterns. Only residues more than three positions apart from both termini of the α-helix were considered as inner. Amino acid pairings i, i+k (k=1, 2, 3, 4, 5), were analysed and the corresponding 20×20 matrices of relative global propensities were constructed. An analysis of (i, i+4, i+8) and (i, i+3, i+4) triplet patterns was also performed. These analysis yielded information on a series of amino acid patterns (pairings and triplets) showing either high or low preference for α-helical motifs and suggested a novel approach to protein alphabet reduction. In addition, it has been shown that the individual amino acid propensities are not enough to define the statistical distribution of these patterns. Global pair propensities also depend on the type of pattern, its composition and orientation in the protein sequence. The data presented should prove useful to obtain and refine useful predictive rules which can further the development and fine-tuning of protein structure prediction algorithms and tools. Copyright © 2010 Elsevier Ltd. All rights reserved.

The relationship between dental implant stability and trabecular bone structure using cone-beam computed tomography

PubMed Central

2016-01-01

Purpose The objective of this study was to investigate the relationships between primary implant stability as measured by impact response frequency and the structural parameters of trabecular bone using cone-beam computed tomography(CBCT), excluding the effect of cortical bone thickness. Methods We measured the impact response of a dental implant placed into swine bone specimens composed of only trabecular bone without the cortical bone layer using an inductive sensor. The peak frequency of the impact response spectrum was determined as an implant stability criterion (SPF). The 3D microstructural parameters were calculated from CT images of the bone specimens obtained using both micro-CT and CBCT. Results SPF had significant positive correlations with trabecular bone structural parameters (BV/TV, BV, BS, BSD, Tb.Th, Tb.N, FD, and BS/BV) (P<0.01) while SPF demonstrated significant negative correlations with other microstructural parameters (Tb.Sp, Tb.Pf, and SMI) using micro-CT and CBCT (P<0.01). Conclusions There was an increase in implant stability prediction by combining BV/TV and SMI in the stepwise forward regression analysis. Bone with high volume density and low surface density shows high implant stability. Well-connected thick bone with small marrow spaces also shows high implant stability. The combination of bone density and architectural parameters measured using CBCT can predict the implant stability more accurately than the density alone in clinical diagnoses. PMID:27127692

Why does working memory capacity predict variation in reading comprehension? On the influence of mind wandering and executive attention.

PubMed

McVay, Jennifer C; Kane, Michael J

2012-05-01

Some people are better readers than others, and this variation in comprehension ability is predicted by measures of working memory capacity (WMC). The primary goal of this study was to investigate the mediating role of mind-wandering experiences in the association between WMC and normal individual differences in reading comprehension, as predicted by the executive-attention theory of WMC (e.g., Engle & Kane, 2004). We used a latent-variable, structural-equation-model approach, testing skilled adult readers on 3 WMC span tasks, 7 varied reading-comprehension tasks, and 3 attention-control tasks. Mind wandering was assessed using experimenter-scheduled thought probes during 4 different tasks (2 reading, 2 attention-control). The results support the executive-attention theory of WMC. Mind wandering across the 4 tasks loaded onto a single latent factor, reflecting a stable individual difference. Most important, mind wandering was a significant mediator in the relationship between WMC and reading comprehension, suggesting that the WMC-comprehension correlation is driven, in part, by attention control over intruding thoughts. We discuss implications for theories of WMC, attention control, and reading comprehension.

New Stagnation Arc Jet Model Design for Testing ADEPT 3-D Carbon Cloth

NASA Technical Reports Server (NTRS)

Beck, R.; Chen, Y.-K.; Wercinski, P.; Agrawal, P.; Chavez-Garcia, J.

2017-01-01

The ADEPT concept has been considered as an entry, descent and landing system to enable Human Mars class missions. Ground rules for the Mars studies required aerocapture, orbit, and then entry. The design utilizes a 3-D woven carbon cloth fabric as both heatshield and primary structure and design guidelines required 6 layers remaining after all entry events. The peak heating predicted for the ADEPT carbon cloth was 35 Wcm2 and resulting temperatures were predicted to be 1400K. Predictions for carbon mass loss were performed using equilibrium thermochemistry, which is only accurate for T2000K. Carbon oxidation is kinetically controlled at T2000K, and mass loss drops off considerably from equilibrium values. Design of the cloth thickness and mass would be significantly reduced if kinetics were considered. This effort was to design a stagnation test article design that could be used in the AHF with varying levels of oxygen where the results could be used to develop an engineering model to describe the recession rate of the carbon as a function of the partial pressure of monotomic oxygen.

Leaf-on canopy closure in broadleaf deciduous forests predicted during winter

USGS Publications Warehouse

Twedt, Daniel J.; Ayala, Andrea J.; Shickel, Madeline R.

2015-01-01

Forest canopy influences light transmittance, which in turn affects tree regeneration and survival, thereby having an impact on forest composition and habitat conditions for wildlife. Because leaf area is the primary impediment to light penetration, quantitative estimates of canopy closure are normally made during summer. Studies of forest structure and wildlife habitat that occur during winter, when deciduous trees have shed their leaves, may inaccurately estimate canopy closure. We estimated percent canopy closure during both summer (leaf-on) and winter (leaf-off) in broadleaf deciduous forests in Mississippi and Louisiana using gap light analysis of hemispherical photographs that were obtained during repeat visits to the same locations within bottomland and mesic upland hardwood forests and hardwood plantation forests. We used mixed-model linear regression to predict leaf-on canopy closure from measurements of leaf-off canopy closure, basal area, stem density, and tree height. Competing predictive models all included leaf-off canopy closure (relative importance = 0.93), whereas basal area and stem density, more traditional predictors of canopy closure, had relative model importance of ≤ 0.51.

Life prediction and constitutive behavior

NASA Technical Reports Server (NTRS)

Halford, G. R.

1983-01-01

One of the primary drivers that prompted the initiation of the hot section technology (HOST) program was the recognized need for improved cyclic durability of costly hot section components. All too frequently, fatigue in one form or another was directly responsible for the less than desired durability, and prospects for the future weren't going to improve unless a significant effort was mounted to increase our knowledge and understanding of the elements governing cyclic crack initiation and propagation lifetime. Certainly one of the important factors is the ability to perform accurate structural stress-strain analyses on a routine basis to determine the magnitudes of the localized stresses and strains since it is these localized conditions that govern the initiation and crack growth processes. Developing the ability to more accurately predict crack initiation lifetimes and cyclic crack growth rates for the complex loading conditions found in turbine engine hot sections is of course the ultimate goal of the life prediction research efforts. It has been found convenient to divide the research efforts into those dealing with nominally isotropic and anisotropic alloys; the latter for application to directionally solidified and single crystal turbine blades.

Stomach Chitinase from Japanese Sardine Sardinops melanostictus: Purification, Characterization, and Molecular Cloning of Chitinase Isozymes with a Long Linker

PubMed Central

Kawashima, Satoshi; Ikehata, Hiroki; Tada, Chihiro; Ogino, Tomohiro; Kakizaki, Hiromi; Ikeda, Mana; Fukushima, Hideto; Matsumiya, Masahiro

2016-01-01

Fish express two different chitinases, acidic fish chitinase-1 (AFCase-1) and acidic fish chitinase-2 (AFCase-2), in the stomach. AFCase-1 and AFCase-2 have different degradation patterns, as fish efficiently degrade chitin ingested as food. For a comparison with the enzymatic properties and the primary structures of chitinase isozymes obtained previously from the stomach of demersal fish, in this study, we purified chitinase isozymes from the stomach of Japanese sardine Sardinops melanostictus, a surface fish that feeds on plankton, characterized the properties of these isozymes, and cloned the cDNAs encoding chitinases. We also predicted 3D structure models using the primary structures of S. melanostictus stomach chitinases. Two chitinase isozymes, SmeChiA (45 kDa) and SmeChiB (56 kDa), were purified from the stomach of S. melanostictus. Moreover, two cDNAs, SmeChi-1 encoding SmeChiA, and SmeChi-2 encoding SmeChiB were cloned. The linker regions of the deduced amino acid sequences of SmeChi-1 and SmeChi-2 (SmeChi-1 and SmeChi-2) are the longest among the fish stomach chitinases. In the cleavage pattern groups toward short substrates and the phylogenetic tree analysis, SmeChi-1 and SmeChi-2 were classified into AFCase-1 and AFCase-2, respectively. SmeChi-1 and SmeChi-2 had catalytic domains that consisted of a TIM-barrel (β/α)8–fold structure and a deep substrate-binding cleft. This is the first study showing the 3D structure models of fish stomach chitinases. PMID:26805857

Hippocampal dose volume histogram predicts Hopkins Verbal Learning Test scores after brain irradiation.

PubMed

Okoukoni, Catherine; McTyre, Emory R; Ayala Peacock, Diandra N; Peiffer, Ann M; Strowd, Roy; Cramer, Christina; Hinson, William H; Rapp, Steve; Metheny-Barlow, Linda; Shaw, Edward G; Chan, Michael D

2017-01-01

Radiation-induced cognitive decline is relatively common after treatment for primary and metastatic brain tumors; however, identifying dosimetric parameters that are predictive of radiation-induced cognitive decline is difficult due to the heterogeneity of patient characteristics. The memory function is especially susceptible to radiation effects after treatment. The objective of this study is to correlate volumetric radiation doses received by critical neuroanatomic structures to post-radiation therapy (RT) memory impairment. Between 2008 and 2011, 53 patients with primary brain malignancies were treated with conventionally fractionated RT in prospectively accrued clinical trials performed at our institution. Dose-volume histogram analysis was performed for the hippocampus, parahippocampus, amygdala, and fusiform gyrus. Hopkins Verbal Learning Test-Revised scores were obtained at least 6 months after RT. Impairment was defined as an immediate recall score ≤15. For each anatomic region, serial regression was performed to correlate volume receiving a given dose (V D(Gy) ) with memory impairment. Hippocampal V 53.4Gy to V 60.9Gy significantly predicted post-RT memory impairment ( P  < .05). Within this range, the hippocampal V 55Gy was the most significant predictor ( P  = .004). Hippocampal V 55Gy of 0%, 25%, and 50% was associated with tumor-induced impairment rates of 14.9% (95% confidence interval [CI], 7.2%-28.7%), 45.9% (95% CI, 24.7%-68.6%), and 80.6% (95% CI, 39.2%-96.4%), respectively. The hippocampal V 55Gy is a significant predictor for impairment, and a limiting dose below 55 Gy may minimize radiation-induced cognitive impairment.

Development and Validation of an HIV Risk Exposure and Indicator Conditions Questionnaire to Support Targeted HIV Screening.

PubMed

Elías, María Jesús Pérez; Gómez-Ayerbe, Cristina; Elías, Pilar Pérez; Muriel, Alfonso; de Santiago, Alberto Diaz; Martinez-Colubi, María; Moreno, Ana; Santos, Cristina; Polo, Lidia; Barea, Rafa; Robledillo, Gema; Uranga, Almudena; Espín, Agustina Cano; Quereda, Carmen; Dronda, Fernando; Casado, Jose Luis; Moreno, Santiago

2016-02-01

The aim of our study was to develop a Spanish-structured HIV risk of exposure and indicator conditions (RE&IC) questionnaire. People attending to an emergency room or to a primary clinical care center were offered to participate in a prospective, 1 arm, open label study, in which all enrolled patients filled out our developed questionnaire and were HIV tested. Questionnaire accuracy, feasibility, and reliability were evaluated.Valid paired 5329 HIV RE&IC questionnaire and rapid HIV tests were performed, 69.3% in the primary clinical care center, 49.6% women, median age 37 years old, 74.9% Spaniards, 20.1% Latin-Americans. Confirmed hidden HIV infection was detected in 4.1%, while HIV RE&IC questionnaire was positive in 51.2%. HIV RE&IC questionnaire sensitivity was 100% to predict HIV infection, with a 100% negative predictive value. When considered separately, RE or IC items sensitivity decreases to 86.4% or 91%, and similarly their negative predictive value to 99.9% for both of them. The majority of people studied, 90.8% self-completed HIV RE&IC questionnaire. Median time to complete was 3 minutes. Overall HIV RE&IC questionnaire test-retest Kappa agreement was 0.82 (almost perfect), likewise for IC items 0.89, while for RE items was lower 0.78 (substantial).A feasible and reliable Spanish HIV RE&IC self questionnaire accurately discriminated all non-HIV-infected people without missing any HIV diagnoses, in a low prevalence HIV infection area. The best accuracy and reliability were obtained when combining HIV RE&IC items.

Development and Validation of an HIV Risk Exposure and Indicator Conditions Questionnaire to Support Targeted HIV Screening

PubMed Central

Elías, María Jesús Pérez; Gómez-Ayerbe, Cristina; Elías, Pilar Pérez; Muriel, Alfonso; de Santiago, Alberto Diaz; Martinez-Colubi, María; Moreno, Ana; Santos, Cristina; Polo, Lidia; Barea, Rafa; Robledillo, Gema; Uranga, Almudena; Espín, Agustina Cano; Quereda, Carmen; Dronda, Fernando; Casado, Jose Luis; Moreno, Santiago

2016-01-01

Abstract The aim of our study was to develop a Spanish-structured HIV risk of exposure and indicator conditions (RE&IC) questionnaire. People attending to an emergency room or to a primary clinical care center were offered to participate in a prospective, 1 arm, open label study, in which all enrolled patients filled out our developed questionnaire and were HIV tested. Questionnaire accuracy, feasibility, and reliability were evaluated. Valid paired 5329 HIV RE&IC questionnaire and rapid HIV tests were performed, 69.3% in the primary clinical care center, 49.6% women, median age 37 years old, 74.9% Spaniards, 20.1% Latin-Americans. Confirmed hidden HIV infection was detected in 4.1%, while HIV RE&IC questionnaire was positive in 51.2%. HIV RE&IC questionnaire sensitivity was 100% to predict HIV infection, with a 100% negative predictive value. When considered separately, RE or IC items sensitivity decreases to 86.4% or 91%, and similarly their negative predictive value to 99.9% for both of them. The majority of people studied, 90.8% self-completed HIV RE&IC questionnaire. Median time to complete was 3 minutes. Overall HIV RE&IC questionnaire test-retest Kappa agreement was 0.82 (almost perfect), likewise for IC items 0.89, while for RE items was lower 0.78 (substantial). A feasible and reliable Spanish HIV RE&IC self questionnaire accurately discriminated all non–HIV-infected people without missing any HIV diagnoses, in a low prevalence HIV infection area. The best accuracy and reliability were obtained when combining HIV RE&IC items. PMID:26844471

SCPRED: accurate prediction of protein structural class for sequences of twilight-zone similarity with predicting sequences.

PubMed

Kurgan, Lukasz; Cios, Krzysztof; Chen, Ke

2008-05-01

Protein structure prediction methods provide accurate results when a homologous protein is predicted, while poorer predictions are obtained in the absence of homologous templates. However, some protein chains that share twilight-zone pairwise identity can form similar folds and thus determining structural similarity without the sequence similarity would be desirable for the structure prediction. The folding type of a protein or its domain is defined as the structural class. Current structural class prediction methods that predict the four structural classes defined in SCOP provide up to 63% accuracy for the datasets in which sequence identity of any pair of sequences belongs to the twilight-zone. We propose SCPRED method that improves prediction accuracy for sequences that share twilight-zone pairwise similarity with sequences used for the prediction. SCPRED uses a support vector machine classifier that takes several custom-designed features as its input to predict the structural classes. Based on extensive design that considers over 2300 index-, composition- and physicochemical properties-based features along with features based on the predicted secondary structure and content, the classifier's input includes 8 features based on information extracted from the secondary structure predicted with PSI-PRED and one feature computed from the sequence. Tests performed with datasets of 1673 protein chains, in which any pair of sequences shares twilight-zone similarity, show that SCPRED obtains 80.3% accuracy when predicting the four SCOP-defined structural classes, which is superior when compared with over a dozen recent competing methods that are based on support vector machine, logistic regression, and ensemble of classifiers predictors. The SCPRED can accurately find similar structures for sequences that share low identity with sequence used for the prediction. The high predictive accuracy achieved by SCPRED is attributed to the design of the features, which are capable of separating the structural classes in spite of their low dimensionality. We also demonstrate that the SCPRED's predictions can be successfully used as a post-processing filter to improve performance of modern fold classification methods.

SCPRED: Accurate prediction of protein structural class for sequences of twilight-zone similarity with predicting sequences

PubMed Central

Kurgan, Lukasz; Cios, Krzysztof; Chen, Ke

2008-01-01

Background Protein structure prediction methods provide accurate results when a homologous protein is predicted, while poorer predictions are obtained in the absence of homologous templates. However, some protein chains that share twilight-zone pairwise identity can form similar folds and thus determining structural similarity without the sequence similarity would be desirable for the structure prediction. The folding type of a protein or its domain is defined as the structural class. Current structural class prediction methods that predict the four structural classes defined in SCOP provide up to 63% accuracy for the datasets in which sequence identity of any pair of sequences belongs to the twilight-zone. We propose SCPRED method that improves prediction accuracy for sequences that share twilight-zone pairwise similarity with sequences used for the prediction. Results SCPRED uses a support vector machine classifier that takes several custom-designed features as its input to predict the structural classes. Based on extensive design that considers over 2300 index-, composition- and physicochemical properties-based features along with features based on the predicted secondary structure and content, the classifier's input includes 8 features based on information extracted from the secondary structure predicted with PSI-PRED and one feature computed from the sequence. Tests performed with datasets of 1673 protein chains, in which any pair of sequences shares twilight-zone similarity, show that SCPRED obtains 80.3% accuracy when predicting the four SCOP-defined structural classes, which is superior when compared with over a dozen recent competing methods that are based on support vector machine, logistic regression, and ensemble of classifiers predictors. Conclusion The SCPRED can accurately find similar structures for sequences that share low identity with sequence used for the prediction. The high predictive accuracy achieved by SCPRED is attributed to the design of the features, which are capable of separating the structural classes in spite of their low dimensionality. We also demonstrate that the SCPRED's predictions can be successfully used as a post-processing filter to improve performance of modern fold classification methods. PMID:18452616

Expansion of Coverage under the Patient Protection and Affordable Care Act and Primary Care Utilization

PubMed Central

Hofer, Adam N; Abraham, Jean Marie; Moscovice, Ira

2011-01-01

Context: Provisions of the Patient Protection and Affordable Care Act of 2010 (PPACA) expand Medicaid to all individuals in families earning less than 133 percent of the federal poverty level (FPL) and make available subsidies to uninsured lower-income Americans (133 to 400 percent of FPL) without access to employer-based coverage to purchase insurance in new exchanges. Since primary care physicians typically serve as the point of entry into the health care delivery system, an adequate supply of them is critical to meeting the anticipated increase in demand for medical care resulting from the expansion of coverage. This article provides state-level estimates of the anticipated increases in primary care utilization given the PPACA's provisions for expanded coverage. Methods: Using the Medical Expenditure Panel Survey, this article estimates a multivariate regression model of annual primary care utilization. Using the model estimates and state-level information regarding the number of uninsured, it predicts, by state, the change in primary care visits expected from the expanded coverage. Finally, the article predicts the number of primary care physicians needed to accommodate this change in utilization. Findings: This expanded coverage is predicted to increase by 2019 the number of annual primary care visits between 15.07 million and 24.26 million. Assuming stable levels of physicians’ productivity, between 4,307 and 6,940 additional primary care physicians would be needed to accommodate this increase. Conclusions: The PPACA's health insurance expansion parameters are expected to significantly increase the use of primary care. Two strategies that policymakers may consider are creating stronger financial incentives to attract medical school students to primary care and changing the delivery of care in ways that lead to operational improvements, higher throughput, and better quality of care. PMID:21418313

Arc Jet Testing of the TIRS Cover Thermal Protection System for Mars Exploration Rover

NASA Technical Reports Server (NTRS)

Szalai, Christine E.; Chen, Y.-K.; Loomis, Mark; Hui, Frank; Scrivens, Larry

2002-01-01

This paper summarizes the arc jet test results of the Mars Exploration Rover (MER) Silicone Impregnated Reusable Ceramic Ablator (SIRCA) Transverse Impulse Rocket System (TIRS) Cover test series in the Panel Test Facility (PTF) at NASA Ames Research Center (ARC). NASA ARC performed aerothermal environment analyses, TPS sizing and thermal response analyses, and arc jet testing to evaluate the MER SIRCA TIRS Cover design and interface to the aeroshell structure. The primary objective of this arc jet test series was to evaluate specific design details of the SIRCA TIRS Cover interface to the MER aeroshell under simulated atmospheric entry heating conditions. Four test articles were tested in an arc jet environment with various sea] configurations. The test condition was designed to match the predicted peak flight heat load at the gap region between the SIRCA and the backshell TPS material, SLA-561S, and resulted in an over-test (with respect to heat flux and heat load) for the apex region of the SIRCA TIRS Cover. The resulting pressure differential was as much as twenty times that predicted for the flight case, depending on the location, and there was no post-test visual evidence of over-heating or damage to the seal, bracket, or backshell structure. The exposed titanium bolts were in good condition at post-test and showed only a small amount of oxidation at the leading edge locations. Repeatable thermocouple data were obtained and SIRCA thermal response analyses were compared to applicable thermocouple data. For the apex region of the SIRCA TIRS Cover, a one-dimensional thermal response prediction proved overly conservative, as there were strong multi-dimensional conduction effects evident from the thermocouple data. The one-dimensional thermal response prediction compared well with the thermocouple data for the leading edge "lip" region at the bolt location. In general, the test results yield confidence in the baseline seal design to prevent hot gas ingestion at the bracket and composite aeroshell structure interface.

Revisiting the concept of recalcitrance and organic matter persistence in soils and aquatic systems: Does environment trump chemistry?

NASA Astrophysics Data System (ADS)

Marin-Spiotta, E.

2014-12-01

Most ecological models of decomposition rely on plant litter chemistry. However, growing evidence suggests that the chemical composition of organic matter (OM) is not a good predictor of its eventual fate in terrestrial or aquatic environments. New data on variable decomposition rates of select organic compounds challenge concepts of chemical recalcitrance, i.e. the inherent ability of certain molecular structures to resist biodegradation. The role of environmental or "ecosystem" properties on influencing decomposition dates back to some of the earliest research on soil OM. Despite early recognition that the physical and aqueous matrices are critical in determining the fate of organic compounds, the prevailing paradigm hinges on intrinsic chemical properties as principal predictors of decay rate. Here I build upon recent reviews and discuss new findings that contribute to three major transformations in our understanding of OM persistence: (1) a shift away from an emphasis on chemical recalcitrance as a primary predictor of turnover, (2) new interpretations of radiocarbon ages which challenge predictions of reactivity, and (3) the recognition that most detrital OM accumulating in soils and in water has been microbially processed. Predictions of OM persistence due to aromaticity are challenged by high variability in lignin and black C turnover observed in terrestrial and aquatic environments. Contradictions in the behavior of lignin are, in part, influenced by inconsistent methodologies among research communities. Even black C, long considered to be one of the most recalcitrant components of OM, is susceptible to biodegradation, challenging predictions of the stability of aromatic structures. At the same time, revised interpretations of radiocarbon data suggest that organic compounds can acquire long mean residence times by various mechanisms independent of their molecular structure. Understanding interactions between environmental conditions and biological reactivity can improve predictions of how disturbance events can further stabilize or destabilize organic C pools, with implications for terrestrial C storage, aquatic C cycling, and climate change.

Combining joint models for biomedical event extraction

PubMed Central

2012-01-01

Background We explore techniques for performing model combination between the UMass and Stanford biomedical event extraction systems. Both sub-components address event extraction as a structured prediction problem, and use dual decomposition (UMass) and parsing algorithms (Stanford) to find the best scoring event structure. Our primary focus is on stacking where the predictions from the Stanford system are used as features in the UMass system. For comparison, we look at simpler model combination techniques such as intersection and union which require only the outputs from each system and combine them directly. Results First, we find that stacking substantially improves performance while intersection and union provide no significant benefits. Second, we investigate the graph properties of event structures and their impact on the combination of our systems. Finally, we trace the origins of events proposed by the stacked model to determine the role each system plays in different components of the output. We learn that, while stacking can propose novel event structures not seen in either base model, these events have extremely low precision. Removing these novel events improves our already state-of-the-art F1 to 56.6% on the test set of Genia (Task 1). Overall, the combined system formed via stacking ("FAUST") performed well in the BioNLP 2011 shared task. The FAUST system obtained 1st place in three out of four tasks: 1st place in Genia Task 1 (56.0% F1) and Task 2 (53.9%), 2nd place in the Epigenetics and Post-translational Modifications track (35.0%), and 1st place in the Infectious Diseases track (55.6%). Conclusion We present a state-of-the-art event extraction system that relies on the strengths of structured prediction and model combination through stacking. Akin to results on other tasks, stacking outperforms intersection and union and leads to very strong results. The utility of model combination hinges on complementary views of the data, and we show that our sub-systems capture different graph properties of event structures. Finally, by removing low precision novel events, we show that performance from stacking can be further improved. PMID:22759463

Deterministic and Probabilistic Creep and Creep Rupture Enhancement to CARES/Creep: Multiaxial Creep Life Prediction of Ceramic Structures Using Continuum Damage Mechanics and the Finite Element Method

NASA Technical Reports Server (NTRS)

Jadaan, Osama M.; Powers, Lynn M.; Gyekenyesi, John P.

1998-01-01

High temperature and long duration applications of monolithic ceramics can place their failure mode in the creep rupture regime. A previous model advanced by the authors described a methodology by which the creep rupture life of a loaded component can be predicted. That model was based on the life fraction damage accumulation rule in association with the modified Monkman-Grant creep ripture criterion However, that model did not take into account the deteriorating state of the material due to creep damage (e.g., cavitation) as time elapsed. In addition, the material creep parameters used in that life prediction methodology, were based on uniaxial creep curves displaying primary and secondary creep behavior, with no tertiary regime. The objective of this paper is to present a creep life prediction methodology based on a modified form of the Kachanov-Rabotnov continuum damage mechanics (CDM) theory. In this theory, the uniaxial creep rate is described in terms of stress, temperature, time, and the current state of material damage. This scalar damage state parameter is basically an abstract measure of the current state of material damage due to creep deformation. The damage rate is assumed to vary with stress, temperature, time, and the current state of damage itself. Multiaxial creep and creep rupture formulations of the CDM approach are presented in this paper. Parameter estimation methodologies based on nonlinear regression analysis are also described for both, isothermal constant stress states and anisothermal variable stress conditions This creep life prediction methodology was preliminarily added to the integrated design code CARES/Creep (Ceramics Analysis and Reliability Evaluation of Structures/Creep), which is a postprocessor program to commercially available finite element analysis (FEA) packages. Two examples, showing comparisons between experimental and predicted creep lives of ceramic specimens, are used to demonstrate the viability of this methodology and the CARES/Creep program.

[Analysis of the primary and secondary structure of the mitochondrial serine transfer RNA in seven species of Lutzomyia].

PubMed

Vivero, Rafael José; Contreras-Gutiérrez, Maria Angélica; Bejarano, Eduar Elías

2007-09-01

Lutzomyia sand flies are involved in the transmission of the parasite Leishmania spp. in America. The taxonomy of these vectors is traditionally based on morphological features of the adult stage, particularly the paired structures of the head and genitalia. Although these characters are useful to distinguish most species of Lutzomyia, morphological identification may be complicated by the similarities within subgenera and species group. To evaluate the utility of mitochondrial serine transfer RNA tRNA Ser for taxonomic identification of Lutzomyia. Seven sand fly species, each representing one of the 27 taxonomic subdivisions in genus Lutzomyia, were analyzed including L. trinidadensis (Oswaldoi group), L. (Psychodopygus) panamensis, L.(Micropygomyia) cayennensis cayennensis, L. dubitans (Migonei group), L. (Lutzomyia) gomezi, L. rangeliana (ungrouped) and L. evansi (Verrucarum group). The mitochondrial tRNA Ser gene, flanked by the cytochrome b and NAD dehydrogenase subunit one genes, was extracted, amplified and sequenced from each specimen. Secondary structure of the tRNA Ser was predicted by comparisons with previously described homologous structures from other dipteran species. The tRNA Ser gene ranged in size from 66 base pairs in L. gomezi to 69 base pairs in L. trinidadensis. Fourteen polymorphic sites, including four insertion-deletion events, were observed in the aligned 70 nucleotide positions. The majority of the substitutions were located in the dihydrouridine, ribothymidine-pseudouridine-cytosine and variable loops, as well as in the basal extreme of the anticodon arm. Changes of primary sequence of the tRNASer provided useful molecular characters for taxonomic identification of the sand fly species under consideration.

Secondary foundation species as drivers of trophic and functional diversity: evidence from a tree-epiphyte system.

PubMed

Angelini, Christine; Silliman, Brian R

2014-01-01

Facilitation cascades arise where primary foundation species facilitate secondary (dependent) foundation species, and collectively, they increase habitat complexity and quality to enhance biodiversity. Whether such phenomena occur in nonmarine systems and if secondary foundation species enhance food web structure (e.g., support novel feeding guilds) and ecosystem function (e.g., provide nursery for juveniles) remain unclear. Here we report on field experiments designed to test whether trees improve epiphyte survival and epiphytes secondarily increase the number and diversity of adult and juvenile invertebrates in a potential live oak-Tillandsia usneoides (Spanish moss) facilitation cascade. Our results reveal that trees reduce physical stress to facilitate Tillandsia, which, in turn, reduces desiccation and predation stress to facilitate invertebrates. In experimental removals, invertebrate total density, juvenile density, species richness and H' diversity were 16, 60, 1.7, and 1.5 times higher, and feeding guild richness and H' were 5 and 11 times greater in Tillandsia-colonized relative to Tillandsia-removal limb plots. Tillandsia enhanced communities similarly in a survey across the southeastern United States. These findings reveal that a facilitation cascade organizes this widespread terrestrial assemblage and expand the role of secondary foundation species as drivers of trophic structure and ecosystem function. We conceptualize the relationship between foundation species' structural attributes and associated species abundance and composition in a Foundation Species-Biodiversity (FSB) model. Importantly, the FSB predicts that, where secondary foundation species form expansive and functionally distinct structures that increase habitat availability and complexity within primary foundation species, they generate and maintain hot spots of biodiversity and trophic interactions.

Low attendance at structured education for people with newly diagnosed type 2 diabetes: General practice characteristics and individual patient factors predict uptake.

PubMed

Winkley, Kirsty; Stahl, Daniel; Chamley, Mark; Stopford, Rosanna; Boughdady, Monica; Thomas, Stephen; Amiel, Stephanie A; Forbes, Angus; Ismail, Khalida

2016-01-01

The aims were to determine the association between individual and neighbourhood factors and attendance at structured education amongst people with newly diagnosed type 2 diabetes (T2DM). Multi-level analysis of questionnaire data from a prospective cohort of adults newly diagnosed T2DM. Setting was primary care, London, UK. Main outcome was attendance at structured education within 2 years. Of 1790 people recruited, attendance data were available for 1626 (91%). Only 22.4% (n=365/1626) attended education. Attendance was independently associated with female gender (OR 1.28, 95% CI 1.05-1.46), lower HbA1c (OR 0.98 mmol/mol 95% CI 0.97-0.99) and non-smoker status (OR 1.36, 95% CI 1.07-1.55). General practice covariates, achievement of primary care targets for glycaemic control (OR 1.05, 95% C.I. 1.01-1.08) and recording of retinal screening (OR 0.96, 95% C.I. 0.93-0.99) were independently associated with attendance but unexplained general practice clustering accounted for 17% of the variance. Education uptake is low amongst people with new onset T2DM. Attenders are more likely to be female, non-smokers with better HbA1c. General practices achieving glycaemic targets are more likely to have patients who attend education. Strategies are needed to improve attendance at structured diabetes education particularly amongst hard to reach groups. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

External validation of ADO, DOSE, COTE and CODEX at predicting death in primary care patients with COPD using standard and machine learning approaches.

PubMed

Morales, Daniel R; Flynn, Rob; Zhang, Jianguo; Trucco, Emmanuel; Quint, Jennifer K; Zutis, Kris

2018-05-01

Several models for predicting the risk of death in people with chronic obstructive pulmonary disease (COPD) exist but have not undergone large scale validation in primary care. The objective of this study was to externally validate these models using statistical and machine learning approaches. We used a primary care COPD cohort identified using data from the UK Clinical Practice Research Datalink. Age-standardised mortality rates were calculated for the population by gender and discrimination of ADO (age, dyspnoea, airflow obstruction), COTE (COPD-specific comorbidity test), DOSE (dyspnoea, airflow obstruction, smoking, exacerbations) and CODEX (comorbidity, dyspnoea, airflow obstruction, exacerbations) at predicting death over 1-3 years measured using logistic regression and a support vector machine learning (SVM) method of analysis. The age-standardised mortality rate was 32.8 (95%CI 32.5-33.1) and 25.2 (95%CI 25.4-25.7) per 1000 person years for men and women respectively. Complete data were available for 54879 patients to predict 1-year mortality. ADO performed the best (c-statistic of 0.730) compared with DOSE (c-statistic 0.645), COTE (c-statistic 0.655) and CODEX (c-statistic 0.649) at predicting 1-year mortality. Discrimination of ADO and DOSE improved at predicting 1-year mortality when combined with COTE comorbidities (c-statistic 0.780 ADO + COTE; c-statistic 0.727 DOSE + COTE). Discrimination did not change significantly over 1-3 years. Comparable results were observed using SVM. In primary care, ADO appears superior at predicting death in COPD. Performance of ADO and DOSE improved when combined with COTE comorbidities suggesting better models may be generated with additional data facilitated using novel approaches. Copyright © 2018. Published by Elsevier Ltd.

Direct Calculation of Protein Fitness Landscapes through Computational Protein Design

PubMed Central

Au, Loretta; Green, David F.

2016-01-01

Naturally selected amino-acid sequences or experimentally derived ones are often the basis for understanding how protein three-dimensional conformation and function are determined by primary structure. Such sequences for a protein family comprise only a small fraction of all possible variants, however, representing the fitness landscape with limited scope. Explicitly sampling and characterizing alternative, unexplored protein sequences would directly identify fundamental reasons for sequence robustness (or variability), and we demonstrate that computational methods offer an efficient mechanism toward this end, on a large scale. The dead-end elimination and A∗ search algorithms were used here to find all low-energy single mutant variants, and corresponding structures of a G-protein heterotrimer, to measure changes in structural stability and binding interactions to define a protein fitness landscape. We established consistency between these algorithms with known biophysical and evolutionary trends for amino-acid substitutions, and could thus recapitulate known protein side-chain interactions and predict novel ones. PMID:26745411

Robust Fault Detection for Aircraft Using Mixed Structured Singular Value Theory and Fuzzy Logic

NASA Technical Reports Server (NTRS)

Collins, Emmanuel G.

2000-01-01

The purpose of fault detection is to identify when a fault or failure has occurred in a system such as an aircraft or expendable launch vehicle. The faults may occur in sensors, actuators, structural components, etc. One of the primary approaches to model-based fault detection relies on analytical redundancy. That is the output of a computer-based model (actually a state estimator) is compared with the sensor measurements of the actual system to determine when a fault has occurred. Unfortunately, the state estimator is based on an idealized mathematical description of the underlying plant that is never totally accurate. As a result of these modeling errors, false alarms can occur. This research uses mixed structured singular value theory, a relatively recent and powerful robustness analysis tool, to develop robust estimators and demonstrates the use of these estimators in fault detection. To allow qualitative human experience to be effectively incorporated into the detection process fuzzy logic is used to predict the seriousness of the fault that has occurred.

Active vibration absorber for CSI evolutionary model: Design and experimental results

NASA Technical Reports Server (NTRS)

Bruner, Anne M.; Belvin, W. Keith; Horta, Lucas G.; Juang, Jer-Nan

1991-01-01

The development of control of large flexible structures technology must include practical demonstration to aid in the understanding and characterization of controlled structures in space. To support this effort, a testbed facility was developed to study practical implementation of new control technologies under realistic conditions. The design is discussed of a second order, acceleration feedback controller which acts as an active vibration absorber. This controller provides guaranteed stability margins for collocated sensor/actuator pairs in the absence of sensor/actuator dynamics and computational time delay. The primary performance objective considered is damping augmentation of the first nine structural modes. Comparison of experimental and predicted closed loop damping is presented, including test and simulation time histories for open and closed loop cases. Although the simulation and test results are not in full agreement, robustness of this design under model uncertainty is demonstrated. The basic advantage of this second order controller design is that the stability of the controller is model independent.

Structure elucidation of a bioactive polysaccharide from fruiting bodies of Hericium erinaceus in different maturation stages.

PubMed

Li, Qiao-Zhen; Wu, Di; Zhou, Shuai; Liu, Yan-Fang; Li, Zheng-Peng; Feng, Jie; Yang, Yan

2016-06-25

HPB-3, a heteropolysaccharide, with a mean molecular weight of 1.5×10(4)Da, was obtained from the maturating-stage IV, V and VI fruiting body of Hericium erinaceus, exhibited higher macrophages stimulation activities, was able to upregulate the functional events mediated by activated macrophages, such as production of nitric oxide (NO). Monosaccharide composition analysis showed that HPB-3 comprised l-fucose, d-galactose and d-glucose in the ratio of 5.2:23.9:1. Its chemical structure was characterized by sugar and methylation analysis, along with (1)H and (13)C NMR spectroscopy, including (1)H-(1)H COSY, TOCSY, NOESY, HMQC and HMBC experiments. The results indicated that HPB-3 contained a-(1/6)-linked galactopyranosyl backbone, partially with a side chain composed of α-l-fucopyranose at the O-2 position. The predicted primary structure of the polysaccharide was established as below. Copyright © 2016 Elsevier Ltd. All rights reserved.

Critical Features of Fragment Libraries for Protein Structure Prediction

PubMed Central

dos Santos, Karina Baptista

2017-01-01

The use of fragment libraries is a popular approach among protein structure prediction methods and has proven to substantially improve the quality of predicted structures. However, some vital aspects of a fragment library that influence the accuracy of modeling a native structure remain to be determined. This study investigates some of these features. Particularly, we analyze the effect of using secondary structure prediction guiding fragments selection, different fragments sizes and the effect of structural clustering of fragments within libraries. To have a clearer view of how these factors affect protein structure prediction, we isolated the process of model building by fragment assembly from some common limitations associated with prediction methods, e.g., imprecise energy functions and optimization algorithms, by employing an exact structure-based objective function under a greedy algorithm. Our results indicate that shorter fragments reproduce the native structure more accurately than the longer. Libraries composed of multiple fragment lengths generate even better structures, where longer fragments show to be more useful at the beginning of the simulations. The use of many different fragment sizes shows little improvement when compared to predictions carried out with libraries that comprise only three different fragment sizes. Models obtained from libraries built using only sequence similarity are, on average, better than those built with a secondary structure prediction bias. However, we found that the use of secondary structure prediction allows greater reduction of the search space, which is invaluable for prediction methods. The results of this study can be critical guidelines for the use of fragment libraries in protein structure prediction. PMID:28085928

Critical Features of Fragment Libraries for Protein Structure Prediction.

PubMed

Trevizani, Raphael; Custódio, Fábio Lima; Dos Santos, Karina Baptista; Dardenne, Laurent Emmanuel

2017-01-01

The use of fragment libraries is a popular approach among protein structure prediction methods and has proven to substantially improve the quality of predicted structures. However, some vital aspects of a fragment library that influence the accuracy of modeling a native structure remain to be determined. This study investigates some of these features. Particularly, we analyze the effect of using secondary structure prediction guiding fragments selection, different fragments sizes and the effect of structural clustering of fragments within libraries. To have a clearer view of how these factors affect protein structure prediction, we isolated the process of model building by fragment assembly from some common limitations associated with prediction methods, e.g., imprecise energy functions and optimization algorithms, by employing an exact structure-based objective function under a greedy algorithm. Our results indicate that shorter fragments reproduce the native structure more accurately than the longer. Libraries composed of multiple fragment lengths generate even better structures, where longer fragments show to be more useful at the beginning of the simulations. The use of many different fragment sizes shows little improvement when compared to predictions carried out with libraries that comprise only three different fragment sizes. Models obtained from libraries built using only sequence similarity are, on average, better than those built with a secondary structure prediction bias. However, we found that the use of secondary structure prediction allows greater reduction of the search space, which is invaluable for prediction methods. The results of this study can be critical guidelines for the use of fragment libraries in protein structure prediction.

Structure of granzyme C reveals an unusual mechanism of protease autoinhibition

PubMed Central

Kaiserman, Dion; Buckle, Ashley M.; Van Damme, Petra; Irving, James A.; Law, Ruby H. P.; Matthews, Antony Y.; Bashtannyk-Puhalovich, Tanya; Langendorf, Chris; Thompson, Philip; Vandekerckhove, Joël; Gevaert, Kris; Whisstock, James C.; Bird, Phillip I.

2009-01-01

Proteases act in important homeostatic pathways and are tightly regulated. Here, we report an unusual structural mechanism of regulation observed by the 2.5-Å X-ray crystal structure of the serine protease, granzyme C. Although the active-site triad residues adopt canonical conformations, the oxyanion hole is improperly formed, and access to the primary specificity (S1) pocket is blocked through a reversible rearrangement involving Phe-191. Specifically, a register shift in the 190-strand preceding the active-site serine leads to Phe-191 filling the S1 pocket. Mutation of a unique Glu–Glu motif at positions 192–193 unlocks the enzyme, which displays chymase activity, and proteomic analysis confirms that activity of the wild-type protease can be released through interactions with an appropriate substrate. The 2.5-Å structure of the unlocked enzyme reveals unprecedented flexibility in the 190-strand preceding the active-site serine that results in Phe-191 vacating the S1 pocket. Overall, these observations describe a broadly applicable mechanism of protease regulation that cannot be predicted by template-based modeling or bioinformatic approaches alone. PMID:19299505

Predicting protein crystallization propensity from protein sequence

PubMed Central

2011-01-01

The high-throughput structure determination pipelines developed by structural genomics programs offer a unique opportunity for data mining. One important question is how protein properties derived from a primary sequence correlate with the protein’s propensity to yield X-ray quality crystals (crystallizability) and 3D X-ray structures. A set of protein properties were computed for over 1,300 proteins that expressed well but were insoluble, and for ~720 unique proteins that resulted in X-ray structures. The correlation of the protein’s iso-electric point and grand average hydropathy (GRAVY) with crystallizability was analyzed for full length and domain constructs of protein targets. In a second step, several additional properties that can be calculated from the protein sequence were added and evaluated. Using statistical analyses we have identified a set of the attributes correlating with a protein’s propensity to crystallize and implemented a Support Vector Machine (SVM) classifier based on these. We have created applications to analyze and provide optimal boundary information for query sequences and to visualize the data. These tools are available via the web site http://bioinformatics.anl.gov/cgi-bin/tools/pdpredictor. PMID:20177794

Conserved thioredoxin fold is present in Pisum sativum L. sieve element occlusion-1 protein

PubMed Central

Umate, Pavan; Tuteja, Renu

2010-01-01

Homology-based three-dimensional model for Pisum sativum sieve element occlusion 1 (Ps.SEO1) (forisomes) protein was constructed. A stretch of amino acids (residues 320 to 456) which is well conserved in all known members of forisomes proteins was used to model the 3D structure of Ps.SEO1. The structural prediction was done using Protein Homology/analogY Recognition Engine (PHYRE) web server. Based on studies of local sequence alignment, the thioredoxin-fold containing protein [Structural Classification of Proteins (SCOP) code d1o73a_], a member of the glutathione peroxidase family was selected as a template for modeling the spatial structure of Ps.SEO1. Selection was based on comparison of primary sequence, higher match quality and alignment accuracy. Motif 1 (EVF) is conserved in Ps.SEO1, Vicia faba (Vf.For1) and Medicago truncatula (MT.SEO3); motif 2 (KKED) is well conserved across all forisomes proteins and motif 3 (IGYIGNP) is conserved in Ps.SEO1 and Vf.For1. PMID:20404566

Summary of Research through Phase II/Year 2 of Initially Approved 3 Phase/3 Year Project - Establishing the Relationship between Fracture-Related Dolomite and Primary Rock Fabric on the Distribution of Reservoirs in the Michigan Basin

DOE Office of Scientific and Technical Information (OSTI.GOV)

G. Grammer

2007-09-30

This final scientific/technical report covers the first 2 years (Phases I and II of an originally planned 3 Year/3 Phase program). The project was focused on evaluating the relationship between fracture-related dolomite and dolomite constrained by primary rock fabric in the 3 most prolific reservoir intervals in the Michigan Basin. The characterization of select dolomite reservoirs was the major focus of our efforts in Phases I and II of the project. Structural mapping and log analysis in the Dundee (Devonian) and Trenton/Black River (Ordovician) suggest a close spatial relationship among gross dolomite distribution and regional-scale, wrench fault-related NW-SE and NE-SWmore » structural trends. A high temperature origin for much of the dolomite in these 2 studied intervals (based upon fluid inclusion homogenization temperatures and stable isotopic analyses,) coupled with persistent association of this dolomite in reservoirs coincident with wrench fault-related features, is strong evidence for these reservoirs being influenced by hydrothermal dolomitization. In the Niagaran (Silurian), there is a general trend of increasing dolomitization shelfward, with limestone predominant in more basinward positions. A major finding is that facies types, when analyzed at a detailed level, are directly related to reservoir porosity and permeability in these dolomites which increases the predictability of reservoir quality in these units. This pattern is consistent with our original hypothesis of primary facies control on dolomitization and resulting reservoir quality at some level. The identification of distinct and predictable vertical stacking patterns within a hierarchical sequence and cycle framework provides a high degree of confidence at this point that the results should be exportable throughout the basin. Much of the data synthesis and modeling for the project was scheduled to be part of Year 3/Phase III, but the discontinuation of funding after Year 2 precluded those efforts. Therefore, the results presented in this document are not final, and in many cases represent a report of 'progress to date' as numerous tasks were scheduled to extend into Year 3.« less

Studies of QCD structure in high-energy collisions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nadolsky, Pavel M.

2016-06-26

”Studies of QCD structure in high-energy collisions” is a research project in theoretical particle physics at Southern Methodist University funded by US DOE Award DE-SC0013681. The award furnished bridge funding for one year (2015/04/15-2016/03/31) between the periods funded by Nadolsky’s DOE Early Career Research Award DE-SC0003870 (in 2010-2015) and a DOE grant DE-SC0010129 for SMU Department of Physics (starting in April 2016). The primary objective of the research is to provide theoretical predictions for Run-2 of the CERN Large Hadron Collider (LHC). The LHC physics program relies on state-of-the-art predictions in the field of quantum chromodynamics. The main effort ofmore » our group went into the global analysis of parton distribution functions (PDFs) employed by the bulk of LHC computations. Parton distributions describe internal structure of protons during ultrarelivistic collisions. A new generation of CTEQ parton distribution functions (PDFs), CT14, was released in summer 2015 and quickly adopted by the HEP community. The new CT14 parametrizations of PDFs were obtained using benchmarked NNLO calculations and latest data from LHC and Tevatron experiments. The group developed advanced methods for the PDF analysis and estimation of uncertainties in LHC predictions associated with the PDFs. We invented and refined a new ’meta-parametrization’ technique that streamlines usage of PDFs in Higgs boson production and other numerous LHC processes, by combining PDFs from various groups using multivariate stochastic sampling. In 2015, the PDF4LHC working group recommended to LHC experimental collaborations to use ’meta-parametrizations’ as a standard technique for computing PDF uncertainties. Finally, to include new QCD processes into the global fits, our group worked on several (N)NNLO calculations.« less

Modeling Particle Exposure in US Trucking Terminals

PubMed Central

Davis, ME; Smith, TJ; Laden, F; Hart, JE; Ryan, LM; Garshick, E

2007-01-01

Multi-tiered sampling approaches are common in environmental and occupational exposure assessment, where exposures for a given individual are often modeled based on simultaneous measurements taken at multiple indoor and outdoor sites. The monitoring data from such studies is hierarchical by design, imposing a complex covariance structure that must be accounted for in order to obtain unbiased estimates of exposure. Statistical methods such as structural equation modeling (SEM) represent a useful alternative to simple linear regression in these cases, providing simultaneous and unbiased predictions of each level of exposure based on a set of covariates specific to the exposure setting. We test the SEM approach using data from a large exposure assessment of diesel and combustion particles in the US trucking industry. The exposure assessment includes data from 36 different trucking terminals across the United States sampled between 2001 and 2005, measuring PM2.5 and its elemental carbon (EC), organic carbon (OC) components, by personal monitoring, and sampling at two indoor work locations and an outdoor “background” location. Using the SEM method, we predict: 1) personal exposures as a function of work related exposure and smoking status; 2) work related exposure as a function of terminal characteristics, indoor ventilation, job location, and background exposure conditions; and 3) background exposure conditions as a function of weather, nearby source pollution, and other regional differences across terminal sites. The primary advantage of SEMs in this setting is the ability to simultaneously predict exposures at each of the sampling locations, while accounting for the complex covariance structure among the measurements and descriptive variables. The statistically significant results and high R2 values observed from the trucking industry application supports the broader use of this approach in exposure assessment modeling. PMID:16856739

Influences of acute alcohol consumption, sexual precedence, and relationship motivation on women’s relationship and sex appraisals and unprotected sex intentions

PubMed Central

Jacques-Tiura, Angela J.; Norris, Jeanette; Kiekel, Preston A.; Davis, Kelly Cue; Zawacki, Tina; Morrison, Diane M.; George, William H.; Abdallah, Devon Alisa

2014-01-01

Guided by the cognitive mediation model of sexual decision making (Norris, Masters, & Zawacki, 2004. Cognitive mediation of women’s sexual decision making: The influence of alcohol, contextual factors, and background variables. Annual Review of Sex Research, 15, 258–296), we examined female social drinkers’ (N = 162) in-the-moment risky sexual decision making by testing how individual differences (relationship motivation) and situational factors (alcohol consumption and sexual precedence conditions) influenced cognitive appraisals and sexual outcomes in a hypothetical sexual scenario. In a path model, acute intoxication, sexual precedence, and relationship motivation interactively predicted primary relationship appraisals and independently predicted primary sex appraisals. Primary appraisals predicted secondary appraisals related to relationship and unprotected sex, which predicted unprotected sex intentions. Sexual precedence directly increased unprotected sex intentions. Findings support the cognitive mediation model and suggest that sexual risk reduction interventions should address alcohol, relationship, sexual, and cognitive factors. PMID:25755302

[Validity and concordance of electronic health records in primary care (AP-Madrid) for surveillance of diabetes mellitus. PREDIMERC study].

PubMed

Gil Montalbán, Elisa; Ortiz Marrón, Honorato; López-Gay Lucio-Villegas, Dulce; Zorrilla Torrás, Belén; Arrieta Blanco, Francisco; Nogales Aguado, Pedro

2014-01-01

To assess the validity and concordance of diabetes data in the electronic health records of primary care (Madrid-PC) by comparing with those from the PREDIMERC study. The sensitivity, specificity, positive predictive value, negative predictive value and kappa index of diabetes cases recorded in the health records of Madrid-PC were calculated by using data from PREDIMERC as the gold standard. The prevalence of diabetes was also determined according to each data source. The sensitivity of diabetes recorded in Madrid-PC was 74%, the specificity was 98.8%, the positive predictive value was 87.9%, the negative predictive value was 97.3%, and the kappa index was 0.78. The prevalence of diabetes recorded in Madrid-PC was 6.7% versus 8.1% by PREDIMERC, where known diabetes was 6.3%. The electronic health records of primary care are a valid source for epidemiological surveillance of diabetes in Madrid. Copyright © 2013 SESPAS. Published by Elsevier Espana. All rights reserved.

Personality Assessment Screener, Childhood Abuse, and Adult Partner Violence in African American Women Using Primary Care.

PubMed

Porcerelli, John H; Hurrell, Kristen; Cogan, Rosemary; Jeffries, Keturah; Markova, Tsveti

2015-12-01

This study assessed the relationship between psychopathology with the Personality Assessment Screener (PAS) and childhood physical and sexual abuse and adult physical and sexual partner violence in a primary care sample of 98 urban-dwelling African American women. Patients completed the PAS, the Childhood Trauma Questionnaire, and the Conflict Tactics Scale. The PAS total score significantly correlated with all measures of childhood and adult abuse. Stepwise regression analyses revealed that PAS element scores of Suicidal Thinking and Hostile Control significantly predicted a history of childhood physical abuse; Suicidal Thinking, Hostile Control, and Acting Out significantly predicted a history of childhood sexual abuse; Suicidal Thinking, Negative Affect, and Alienation significantly predicted current adult partner physical violence; and Psychotic Features, Alcohol Problems, and Anger Control significantly predicted current adult sexual partner violence. The PAS appears to be a useful measure for fast-paced primary care settings for identifying patients who need a more thorough assessment for abuse. © The Author(s) 2015.

Thioesterases: A new perspective based on their primary and tertiary structures

PubMed Central

Cantu, David C; Chen, Yingfei; Reilly, Peter J

2010-01-01

Thioesterases (TEs) are classified into EC 3.1.2.1 through EC 3.1.2.27 based on their activities on different substrates, with many remaining unclassified (EC 3.1.2.–). Analysis of primary and tertiary structures of known TEs casts a new light on this enzyme group. We used strong primary sequence conservation based on experimentally proved proteins as the main criterion, followed by verification with tertiary structure superpositions, mechanisms, and catalytic residue positions, to accurately define TE families. At present, TEs fall into 23 families almost completely unrelated to each other by primary structure. It is assumed that all members of the same family have essentially the same tertiary structure; however, TEs in different families can have markedly different folds and mechanisms. Conversely, the latter sometimes have very similar tertiary structures and catalytic mechanisms despite being only slightly or not at all related by primary structure, indicating that they have common distant ancestors and can be grouped into clans. At present, four clans encompass 12 TE families. The new constantly updated ThYme (Thioester-active enzYmes) database contains TE primary and tertiary structures, classified into families and clans that are different from those currently found in the literature or in other databases. We review all types of TEs, including those cleaving CoA, ACP, glutathione, and other protein molecules, and we discuss their structures, functions, and mechanisms. PMID:20506386

Which Specific Skills Developing during Preschool Years Predict the Reading Performance in the First and Second Grade of Primary School?

ERIC Educational Resources Information Center

Papadimitriou, Artemis M.; Vlachos, Filippos M.

2014-01-01

The aim of this study was to examine if specific skills that are developed during preschool years could predict the reading performance in the first and second grade of primary school. Two hundred and eighty-seven children participated in this longitudinal study. At the kindergarten level, phonological awareness (PA), rapid automatised naming,…

Predictive Effects of the Quality of Online Peer-Feedback Provided and Received on Primary School Students' Quality of Question-Generation

ERIC Educational Resources Information Center

Yu, Fu-Yun; Wu, Chun-Ping

2016-01-01

The research objectives of this study were to examine the individual and combined predictive effects of the quality of online peer-feedback provided and received on primary school students' quality of question-generation. A correlational study was adopted, and performance data from 213 fifth-grade students engaged in online question-generation and…

Cross-sectional study examining whether the extent of first-contact access to primary care differentially benefits those with certain personalities to receive preventive services

PubMed Central

Pandhi, Nancy; Schumacher, Jessica R; Thorpe, Carolyn T; Smith, Maureen A

2016-01-01

Objective The extent of first-contact access to primary care (ie, easy availability when needed) is associated with receiving recommended preventive services. Whether this access benefits patients at risk of preventive services underutilisation, such as those with certain personality characteristics, is unclear. Setting Secondary analysis of the 2003–2006 round of the Wisconsin Longitudinal Study. Participants 6975 respondents who reported a usual provider whose specialty was internal medicine or family medicine. Those reporting not visiting a medical provider in the past 12 months, and those who were uninsured were excluded. Primary outcome measures Receiving mammography, cholesterol testing and influenza vaccination. Adjusted predicted probabilities (aPP) of receiving these services were analysed stratified by personality characteristics overall, and if significant, then interacted with first-contact access. Results Lower conscientiousness as compared with higher conscientiousness predicted less of all 3 preventive services; mammography (aPP 80%; 95% CI (77% to 83%) vs aPP 85%; (95% CI 82% to 87%)), cholesterol testing (88%; (85% to 90%) vs 93% (91% to 94%), and influenza vaccination (62%; (59% to 64%) vs 66%; (63% to 68%)). Lower agreeableness as compared with higher agreeableness predicted less mammography (77%; (73% to 81%) vs 84%; (82% to 87%)) and less influenza vaccination (59%; (56% to 62%) vs 65%; (63% to 68%)). Lower extraversion predicted less cholesterol testing (88%; (86% to 91%) vs (92%; (90% to 94%)). Lower openness to experience predicted less influenza vaccination (59%; (56% to 63%) vs (68%; (65% to 70%)). For agreeableness, these differences in receiving preventive services did not persist when first-contact access to primary care was present. Conclusions Certain personality characteristics predicted receiving less preventive care services. For those with less agreeableness, improved first-contact access to primary care mitigated this effect. If these results are replicated in other studies, primary care offices seeking to improve population health through receiving preventive services should prioritise increasing their first-contact accessibility. PMID:26951211

RNAstructure: software for RNA secondary structure prediction and analysis.

PubMed

Reuter, Jessica S; Mathews, David H

2010-03-15

To understand an RNA sequence's mechanism of action, the structure must be known. Furthermore, target RNA structure is an important consideration in the design of small interfering RNAs and antisense DNA oligonucleotides. RNA secondary structure prediction, using thermodynamics, can be used to develop hypotheses about the structure of an RNA sequence. RNAstructure is a software package for RNA secondary structure prediction and analysis. It uses thermodynamics and utilizes the most recent set of nearest neighbor parameters from the Turner group. It includes methods for secondary structure prediction (using several algorithms), prediction of base pair probabilities, bimolecular structure prediction, and prediction of a structure common to two sequences. This contribution describes new extensions to the package, including a library of C++ classes for incorporation into other programs, a user-friendly graphical user interface written in JAVA, and new Unix-style text interfaces. The original graphical user interface for Microsoft Windows is still maintained. The extensions to RNAstructure serve to make RNA secondary structure prediction user-friendly. The package is available for download from the Mathews lab homepage at http://rna.urmc.rochester.edu/RNAstructure.html.

RNA-Puzzles: A CASP-like evaluation of RNA three-dimensional structure prediction

PubMed Central

Cruz, José Almeida; Blanchet, Marc-Frédérick; Boniecki, Michal; Bujnicki, Janusz M.; Chen, Shi-Jie; Cao, Song; Das, Rhiju; Ding, Feng; Dokholyan, Nikolay V.; Flores, Samuel Coulbourn; Huang, Lili; Lavender, Christopher A.; Lisi, Véronique; Major, François; Mikolajczak, Katarzyna; Patel, Dinshaw J.; Philips, Anna; Puton, Tomasz; Santalucia, John; Sijenyi, Fredrick; Hermann, Thomas; Rother, Kristian; Rother, Magdalena; Serganov, Alexander; Skorupski, Marcin; Soltysinski, Tomasz; Sripakdeevong, Parin; Tuszynska, Irina; Weeks, Kevin M.; Waldsich, Christina; Wildauer, Michael; Leontis, Neocles B.; Westhof, Eric

2012-01-01

We report the results of a first, collective, blind experiment in RNA three-dimensional (3D) structure prediction, encompassing three prediction puzzles. The goals are to assess the leading edge of RNA structure prediction techniques; compare existing methods and tools; and evaluate their relative strengths, weaknesses, and limitations in terms of sequence length and structural complexity. The results should give potential users insight into the suitability of available methods for different applications and facilitate efforts in the RNA structure prediction community in ongoing efforts to improve prediction tools. We also report the creation of an automated evaluation pipeline to facilitate the analysis of future RNA structure prediction exercises. PMID:22361291

A model for the Pockels effect in distorted liquid crystal blue phases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Castles, F., E-mail: flynn.castles@materials.ox.ac.uk

2015-09-07

Recent experiments have found that a mechanically distorted blue phase can exhibit a primary linear electro-optic (Pockels) effect [F. Castles et al., Nat. Mater. 13, 817 (2014)]. Here, it is shown that flexoelectricity can account for the experimental results and a model, which is based on continuum theory but takes into account the sub-unit-cell structure, is proposed. The model provides a quantitative description of the effect accurate to the nearest order of magnitude and predicts that the Pockels coefficient(s) in an optimally distorted blue phase may be two orders of magnitude larger than in lithium niobate.

Compression strength of composite primary structural components

NASA Technical Reports Server (NTRS)

Johnson, Eric R.

1992-01-01

A status report of work performed during the period May 1, 1992 to October 31, 1992 is presented. Research was conducted in three areas: delamination initiation in postbuckled dropped-ply laminates; stiffener crippling initiated by delamination; and pressure pillowing of an orthogonally stiffened cylindrical shell. The geometrically nonlinear response and delamination initiation of compression-loaded dropped-ply laminates is analyzed. A computational model of the stiffener specimens that includes the capability to predict the interlaminar response at the flange free edge in postbuckling is developed. The distribution of the interacting loads between the stiffeners and the shell wall, particularly at the load transfer at the stiffener crossing point, is determined.

Self-Efficacy, School Resources, Job Stressors and Burnout among Spanish Primary and Secondary School Teachers: A Structural Equation Approach

ERIC Educational Resources Information Center

Betoret, Fernando Domenech

2009-01-01

This study examines the relationship between school resources, teacher self-efficacy, potential multi-level stressors and teacher burnout using structural equation modelling. The causal structure for primary and secondary school teachers was also examined. The sample was composed of 724 primary and secondary Spanish school teachers. The changes…

Structural Dynamics of Education Reforms and Quality of Primary Education in Uganda

ERIC Educational Resources Information Center

Nyenje, Aida

2016-01-01

This paper examines Uganda's recent undertaking to reform her Primary School education System with a focus on the effect of structural dynamics of education reforms and the quality of primary education. Structural dynamics in the context of this study is in reference to the organizational composition of the education system at the government,…

Predicting Consumer Biomass, Size-Structure, Production, Catch Potential, Responses to Fishing and Associated Uncertainties in the World's Marine Ecosystems.

PubMed

Jennings, Simon; Collingridge, Kate

2015-01-01

Existing estimates of fish and consumer biomass in the world's oceans are disparate. This creates uncertainty about the roles of fish and other consumers in biogeochemical cycles and ecosystem processes, the extent of human and environmental impacts and fishery potential. We develop and use a size-based macroecological model to assess the effects of parameter uncertainty on predicted consumer biomass, production and distribution. Resulting uncertainty is large (e.g. median global biomass 4.9 billion tonnes for consumers weighing 1 g to 1000 kg; 50% uncertainty intervals of 2 to 10.4 billion tonnes; 90% uncertainty intervals of 0.3 to 26.1 billion tonnes) and driven primarily by uncertainty in trophic transfer efficiency and its relationship with predator-prey body mass ratios. Even the upper uncertainty intervals for global predictions of consumer biomass demonstrate the remarkable scarcity of marine consumers, with less than one part in 30 million by volume of the global oceans comprising tissue of macroscopic animals. Thus the apparently high densities of marine life seen in surface and coastal waters and frequently visited abundance hotspots will likely give many in society a false impression of the abundance of marine animals. Unexploited baseline biomass predictions from the simple macroecological model were used to calibrate a more complex size- and trait-based model to estimate fisheries yield and impacts. Yields are highly dependent on baseline biomass and fisheries selectivity. Predicted global sustainable fisheries yield increases ≈4 fold when smaller individuals (< 20 cm from species of maximum mass < 1 kg) are targeted in all oceans, but the predicted yields would rarely be accessible in practice and this fishing strategy leads to the collapse of larger species if fishing mortality rates on different size classes cannot be decoupled. Our analyses show that models with minimal parameter demands that are based on a few established ecological principles can support equitable analysis and comparison of diverse ecosystems. The analyses provide insights into the effects of parameter uncertainty on global biomass and production estimates, which have yet to be achieved with complex models, and will therefore help to highlight priorities for future research and data collection. However, the focus on simple model structures and global processes means that non-phytoplankton primary production and several groups, structures and processes of ecological and conservation interest are not represented. Consequently, our simple models become increasingly less useful than more complex alternatives when addressing questions about food web structure and function, biodiversity, resilience and human impacts at smaller scales and for areas closer to coasts.

Contrast-enhanced [18F] fluorodeoxyglucose-positron emission tomography-computed tomography as an initial imaging modality in patients presenting with metastatic malignancy of undefined primary origin

PubMed Central

Jain, Avani; Srivastava, Madhur Kumar; Pawaskar, Alok Suresh; Shelley, Simon; Elangovan, Indirani; Jain, Hasmukh; Pandey, Somnath; Kalal, Shilpa; Amalachandran, Jaykanth

2015-01-01

Background: To evaluate the advantages of contrast enhanced F-18-fluorodeoxyglucose (FDG) positron emission tomography-computed tomography (PET-contrast enhanced CT [CECT]) when used as an initial imaging modality in patients presenting with metastatic malignancy of undefined primary origin (MUO). Materials and Methods: A total of 243 patients with fine needle aspiration cytology/biopsy proven MUO were included in this prospective study. Patients who were thoroughly evaluated for primary or primary tumor was detected by any other investigation were excluded from the analysis. Totally, 163 patients with pathological diagnosis of malignancy but no apparent sites of the primary tumor were finally selected for analysis. The site of probable primary malignancy suggested by PET-CECT was confirmed by biopsy/follow-up. Results: PET-CECT suggested probable site of primary in 128/163 (78.52%) patients. In 30/35 remaining patients, primary tumor was not detected even after extensive work-up. In 5 patients, where PET-CECT was negative, primary was found on further extensive investigations or follow-up. The sensitivity, specificity, positive predictive value and negative predictive value of the study were 95.76%, 66.67%, 88.28% and 85.71% respectively. Conclusions: F-18 FDG PET-CECT aptly serves the purpose of initial imaging modality owing to high sensitivity, negative and positive predictive value. PET-CECT not only surveys the whole body for the primary malignancy but also stages the disease accurately. Use of contrast improves the diagnostic utility of modality as well as help in staging of the primary tumor. Although benefits of using PET-CECT as initial diagnostic modality are obvious from this study, there is a need for a larger study comparing conventional methods for diagnosing primary in patients with MUO versus PET-CECT. PMID:26170563

Evaluation of a Novel Renewable Hepatic Cell Model for Prediction of Clinical CYP3A4 Induction Using a Correlation-Based Relative Induction Score Approach.

PubMed

Zuo, Rongjun; Li, Feng; Parikh, Sweta; Cao, Li; Cooper, Kirsten L; Hong, Yulong; Liu, Jin; Faris, Ronald A; Li, Daochuan; Wang, Hongbing

2017-02-01

Metabolism enzyme induction-mediated drug-drug interactions need to be carefully characterized in vitro for drug candidates to predict in vivo safety risk and therapeutic efficiency. Currently, both the Food and Drug Administration and European Medicines Agency recommend using primary human hepatocytes as the gold standard in vitro test system for studying the induction potential of candidate drugs on cytochrome P450 (CYP), CYP3A4, CYP1A2, and CYP2B6. However, primary human hepatocytes are known to bear inherent limitations such as limited supply and large lot-to-lot variations, which result in an experimental burden to qualify new lots. To overcome these shortcomings, a renewable source of human hepatocytes (i.e., Corning HepatoCells) was developed from primary human hepatocytes and was evaluated for in vitro CYP3A4 induction using methods well established by the pharmaceutical industry. HepatoCells have shown mature hepatocyte-like morphology and demonstrated primary hepatocyte-like response to prototypical inducers of all three CYP enzymes with excellent consistency. Importantly, HepatoCells retain a phenobarbital-responsive nuclear translocation of human constitutive androstane receptor from the cytoplasm, characteristic to primary hepatocytes. To validate HepatoCells as a useful tool to predict potential clinical relevant CYP3A4 induction, we tested three different lots of HepatoCells with a group of clinical strong, moderate/weak CYP3A4 inducers, and noninducers. A relative induction score calibration curve-based approach was used for prediction. HepatoCells showed accurate prediction comparable to primary human hepatocytes. Together, these results demonstrate that Corning HepatoCells is a reliable in vitro model for drug-drug interaction studies during the early phase of drug testing. Copyright © 2017 by The Author(s).

RNA-Puzzles Round III: 3D RNA structure prediction of five riboswitches and one ribozyme

PubMed Central

Biesiada, Marcin; Boniecki, Michał J.; Chou, Fang-Chieh; Ferré-D'Amaré, Adrian R.; Das, Rhiju; Dunin-Horkawicz, Stanisław; Geniesse, Caleb; Kappel, Kalli; Kladwang, Wipapat; Krokhotin, Andrey; Łach, Grzegorz E.; Major, François; Mann, Thomas H.; Pachulska-Wieczorek, Katarzyna; Patel, Dinshaw J.; Piccirilli, Joseph A.; Popenda, Mariusz; Purzycka, Katarzyna J.; Ren, Aiming; Rice, Greggory M.; Santalucia, John; Tandon, Arpit; Trausch, Jeremiah J.; Wang, Jian; Weeks, Kevin M.; Williams, Benfeard; Xiao, Yi; Zhang, Dong; Zok, Tomasz

2017-01-01

RNA-Puzzles is a collective experiment in blind 3D RNA structure prediction. We report here a third round of RNA-Puzzles. Five puzzles, 4, 8, 12, 13, 14, all structures of riboswitch aptamers and puzzle 7, a ribozyme structure, are included in this round of the experiment. The riboswitch structures include biological binding sites for small molecules (S-adenosyl methionine, cyclic diadenosine monophosphate, 5-amino 4-imidazole carboxamide riboside 5′-triphosphate, glutamine) and proteins (YbxF), and one set describes large conformational changes between ligand-free and ligand-bound states. The Varkud satellite ribozyme is the most recently solved structure of a known large ribozyme. All puzzles have established biological functions and require structural understanding to appreciate their molecular mechanisms. Through the use of fast-track experimental data, including multidimensional chemical mapping, and accurate prediction of RNA secondary structure, a large portion of the contacts in 3D have been predicted correctly leading to similar topologies for the top ranking predictions. Template-based and homology-derived predictions could predict structures to particularly high accuracies. However, achieving biological insights from de novo prediction of RNA 3D structures still depends on the size and complexity of the RNA. Blind computational predictions of RNA structures already appear to provide useful structural information in many cases. Similar to the previous RNA-Puzzles Round II experiment, the prediction of non-Watson–Crick interactions and the observed high atomic clash scores reveal a notable need for an algorithm of improvement. All prediction models and assessment results are available at http://ahsoka.u-strasbg.fr/rnapuzzles/. PMID:28138060

Genetic Markers Predict Primary Non-Response and Durable Response To Anti-TNF Biologic Therapies in Crohn's Disease.

PubMed

Barber, Grant E; Yajnik, Vijay; Khalili, Hamed; Giallourakis, Cosmas; Garber, John; Xavier, Ramnik; Ananthakrishnan, Ashwin N

2016-12-01

One-fifth of patients with Crohn's disease (CD) are primary non-responders to anti-tumor necrosis factor (anti-TNF) therapy, and an estimated 10-15% will fail therapy annually. Little is known about the genetics of response to anti-TNF therapy. The aim of our study was to identify genetic factors associated with primary non-response (PNR) and loss of response to anti-TNFs in CD. From a prospective registry, we characterized the response of 427 CD patients to their first anti-TNF therapy. Patients were designated as achieving primary response, durable response, and non-durable response based on clinical, endoscopic, and radiologic criteria. Genotyping was performed on the Illumina Immunochip. Separate genetic scores based on presence of predictive genetic alleles were calculated for PNR and durable response and performance of clinical and genetics models were compared. From 359 patients, 36 were adjudged to have PNR (10%), 200 had durable response, and 74 had non-durable response. PNRs had longer disease duration and were more likely to be smokers. Fifteen risk alleles were associated with PNR. Patients with PNR had a significantly higher genetic risk score (GRS) (P =8 × 10 -12 ). A combined clinical-genetic model more accurately predicted PNR when compared with a clinical only model (0.93 vs. 0.70, P <0.001). Sixteen distinct single nucleotide polymorphisms predicted durable response with a higher GRS (P =7 × 10 -13 ). The GRSs for PNR and durable response were not mutually correlated, suggesting distinct mechanisms. Genetic risk alleles can predict primary non-response and durable response to anti-TNF therapy in CD.

Do patients׳ illness beliefs predict depression measures at six months in primary care; a longitudinal study.

PubMed

Lynch, Jeannette; Moore, Michael; Moss-Morris, Rona; Kendrick, Tony

2015-03-15

Depressive disorders are prevalent and costly but there is a lack of evidence on how best to select treatments for mild to moderate depression in primary care. Illness beliefs have been shown to affect the outcome from physical illness, but there is limited information on the beliefs of patients who are depressed. To measure patients׳ beliefs about depression at baseline and determine whether these relate to depression severity at six months. Primary care patients with a recently diagnosed episode of depression completed the Beliefs about Depression Questionnaire and depression severity scores at baseline. The primary outcome was the change in depression severity score on the Hospital Anxiety and Depression Scale after six months. 227/292 (78%) participants completed follow-up questionnaires. Initial severity of depression at baseline, and particular beliefs about the causes, consequences and timeline of depression predicted poorer outcomes, whereas a belief in using exercise or keeping busy to treat depression predicted improved outcomes. Prescription of antidepressants did not appear to mediate these relationships. This was an initial study using a new validated questionnaire and it cannot be predicted whether these results are representative or would be reproduced in other populations. Although participants were primary care patients whose GP (General Practitioner) had coded as having a new incident episode of depression in the preceding six months, 43% of participants stated they had been depressed for more than a year. Sufficient participants were recruited to ensure the study was adequately powered but participation rate was 30%, raising the possibility of response bias. Illness beliefs may help to predict outcomes in depression and therefore assessing and addressing patients׳ beliefs about their depression may enhance treatment. Crown Copyright © 2015. Published by Elsevier B.V. All rights reserved.

Enhanced risk prediction model for emergency department use and hospitalizations in patients in a primary care medical home.

PubMed

Takahashi, Paul Y; Heien, Herbert C; Sangaralingham, Lindsey R; Shah, Nilay D; Naessens, James M

2016-07-01

With the advent of healthcare payment reform, identifying high-risk populations has become more important to providers. Existing risk-prediction models often focus on chronic conditions. This study sought to better understand other factors to improve identification of the highest risk population. A retrospective cohort study of a paneled primary care population utilizing 2010 data to calibrate a risk prediction model of hospital and emergency department (ED) use in 2011. Data were randomly split into development and validation data sets. We compared the enhanced model containing the additional risk predictors with the Minnesota medical tiering model. The study was conducted in the primary care practice of an integrated delivery system at an academic medical center in Rochester, Minnesota. The study focus was primary care medical home patients in 2010 and 2011 (n = 84,752), with the primary outcome of subsequent hospitalization or ED visit. A total of 42,384 individuals derived the enhanced risk-prediction model and 42,368 individuals validated the model. Predictors included Adjusted Clinical Groups-based Minnesota medical tiering, patient demographics, insurance status, and prior year healthcare utilization. Additional variables included specific mental and medical conditions, use of high-risk medications, and body mass index. The area under the curve in the enhanced model was 0.705 (95% CI, 0.698-0.712) compared with 0.662 (95% CI, 0.656-0.669) in the Minnesota medical tiering-only model. New high-risk patients in the enhanced model were more likely to have lack of health insurance, presence of Medicaid, diagnosed depression, and prior ED utilization. An enhanced model including additional healthcare-related factors improved the prediction of risk of hospitalization or ED visit.

Transferrin saturation phenotype and HFE genotype screening for hemochromatosis and primary iron overload: predictions from a model based on national, racial, and ethnic group composition in central Alabama.

PubMed

Barton, J C; Acton, R T

2000-01-01

There is interest in general population screening for hemochromatosis and other primary iron overload disorders, although not all persons are at equal risk. We developed a model to estimate the numbers of persons in national, racial, or ethnic population subgroups in Jefferson County, Alabama, who would be detected using transferrin saturation (phenotype) or HFE mutation analysis (genotype) screening. Approximately 62% are Caucasians, 37% are African Americans, and the remainder are Hispanics, Asians, or Native Americans. The predicted phenotype frequencies are greatest in a Caucasian subgroup, ethnicity unspecified, which consists predominantly of persons of Scotch and Irish descent (0.0065 men, 0.0046 women), and in African Americans (0.0089 men, 0.0085 women). Frequencies of the HFE genotype C282Y/C282Y > or = 0.0001 are predicted to occur only among Caucasians; the greatest frequency (0.0080) was predicted to occur in the ethnicity-unspecified Caucasian population. C282Y/C282Y frequency estimates were lower in Italian, Greek, and Jewish subgroups. There is excellent agreement in the numbers of the ethnicity-unspecified Caucasians who would be detected using phenotype and genotype criteria. Our model also indicates that phenotyping would identify more persons with primary iron overload than would genotyping in our Italian Caucasian, Hispanic, and African American subgroups. This is consistent with previous observations that indicate that primary iron overload disorders in persons of southern Italian descent and African Americans are largely attributable to non-HFE alleles. Because the proportions of population subgroups and their genetic constitution may differ significantly in other geographic regions, we suggest that models similar to the present one be constructed to predict optimal screening strategies for primary iron overload disorders.