Emerging methods to study bacteriophage infection at the single-cell level.

PubMed

Dang, Vinh T; Sullivan, Matthew B

2014-01-01

Bacteria and their viruses (phages) are abundant across diverse ecosystems and their interactions influence global biogeochemical cycles and incidence of disease. Problematically, both classical and metagenomic methods insufficiently assess the host specificity of phages and phage-host infection dynamics in nature. Here we review emerging methods to study phage-host interaction and infection dynamics with a focus on those that offer resolution at the single-cell level. These methods leverage ever-increasing sequence data to identify virus signals from single-cell amplified genome datasets or to produce primers/probes to target particular phage-bacteria pairs (digital PCR and phageFISH), even in complex communities. All three methods enable study of phage infection of uncultured bacteria from environmental samples, while the latter also discriminates between phage-host interaction outcomes (e.g., lytic, chronic, lysogenic) in model systems. Together these techniques enable quantitative, spatiotemporal studies of phage-bacteria interactions from environmental samples of any ecosystem, which will help elucidate and predict the ecological and evolutionary impacts of specific phage-host pairings in nature.

Analyzing Interactions by an IIS-Map-Based Method in Face-to-Face Collaborative Learning: An Empirical Study

ERIC Educational Resources Information Center

Zheng, Lanqin; Yang, Kaicheng; Huang, Ronghuai

2012-01-01

This study proposes a new method named the IIS-map-based method for analyzing interactions in face-to-face collaborative learning settings. This analysis method is conducted in three steps: firstly, drawing an initial IIS-map according to collaborative tasks; secondly, coding and segmenting information flows into information items of IIS; thirdly,…

Explaining the Effectiveness of the Contrast Culture Method for Managing Interpersonal Interactions across Cultures

ERIC Educational Resources Information Center

Hiratsuka, Hiroyoshi; Suzuki, Hanako; Pusina, Alexis

2016-01-01

One of the current challenges in the field of intercultural education comes from the limited availability of training efficacy studies. The present study focused on explaining the effectiveness of the Contrast Culture Method (CCM) as an intercultural education method for managing interpersonal interactions across cultures between graduate…

A Penalized Robust Method for Identifying Gene-Environment Interactions

PubMed Central

Shi, Xingjie; Liu, Jin; Huang, Jian; Zhou, Yong; Xie, Yang; Ma, Shuangge

2015-01-01

In high-throughput studies, an important objective is to identify gene-environment interactions associated with disease outcomes and phenotypes. Many commonly adopted methods assume specific parametric or semiparametric models, which may be subject to model mis-specification. In addition, they usually use significance level as the criterion for selecting important interactions. In this study, we adopt the rank-based estimation, which is much less sensitive to model specification than some of the existing methods and includes several commonly encountered data and models as special cases. Penalization is adopted for the identification of gene-environment interactions. It achieves simultaneous estimation and identification and does not rely on significance level. For computation feasibility, a smoothed rank estimation is further proposed. Simulation shows that under certain scenarios, for example with contaminated or heavy-tailed data, the proposed method can significantly outperform the existing alternatives with more accurate identification. We analyze a lung cancer prognosis study with gene expression measurements under the AFT (accelerated failure time) model. The proposed method identifies interactions different from those using the alternatives. Some of the identified genes have important implications. PMID:24616063

Diversity in Genetic In Vivo Methods for Protein-Protein Interaction Studies: from the Yeast Two-Hybrid System to the Mammalian Split-Luciferase System

PubMed Central

Stynen, Bram; Tournu, Hélène; Tavernier, Jan

2012-01-01

Summary: The yeast two-hybrid system pioneered the field of in vivo protein-protein interaction methods and undisputedly gave rise to a palette of ingenious techniques that are constantly pushing further the limits of the original method. Sensitivity and selectivity have improved because of various technical tricks and experimental designs. Here we present an exhaustive overview of the genetic approaches available to study in vivo binary protein interactions, based on two-hybrid and protein fragment complementation assays. These methods have been engineered and employed successfully in microorganisms such as Saccharomyces cerevisiae and Escherichia coli, but also in higher eukaryotes. From single binary pairwise interactions to whole-genome interactome mapping, the self-reassembly concept has been employed widely. Innovative studies report the use of proteins such as ubiquitin, dihydrofolate reductase, and adenylate cyclase as reconstituted reporters. Protein fragment complementation assays have extended the possibilities in protein-protein interaction studies, with technologies that enable spatial and temporal analyses of protein complexes. In addition, one-hybrid and three-hybrid systems have broadened the types of interactions that can be studied and the findings that can be obtained. Applications of these technologies are discussed, together with the advantages and limitations of the available assays. PMID:22688816

The in Silico Insight into Carbon Nanotube and Nucleic Acid Bases Interaction.

PubMed

Karimi, Ali Asghar; Ghalandari, Behafarid; Tabatabaie, Seyed Saleh; Farhadi, Mohammad

2016-05-01

To explore practical applications of carbon nanotubes (CNTs) in biomedical fields the properties of their interaction with biomolecules must be revealed. Recent years, the interaction of CNTs with biomolecules is a subject of research interest for practical applications so that previous research explored that CNTs have complementary structure properties with single strand DNA (ssDNA). Hence, the quantum mechanics (QM) method based on ab initio was used for this purpose. Therefore values of binding energy, charge distribution, electronic energy and other physical properties of interaction were studied for interaction of nucleic acid bases and SCNT. In this study, the interaction between nucleic acid bases and a (4, 4) single-walled carbon nanotube (SCNT) were investigated through calculations within quantum mechanics (QM) method at theoretical level of Hartree-Fock (HF) method using 6-31G basis set. Hence, the physical properties such as electronic energy, total dipole moment, charge distributions and binding energy of nucleic acid bases interaction with SCNT were investigated based on HF method. It has been found that the guanine base adsorption is bound stronger to the outer surface of nanotube in comparison to the other bases, consistent with the recent theoretical studies. In the other words, the results explored that guanine interaction with SCNT has optimum level of electronic energy so that their interaction is stable. Also, the calculations illustrated that SCNT interact to nucleic acid bases by noncovalent interaction because of charge distribution an electrostatic area is created in place of interaction. Consequently, small diameter SCNT interaction with nucleic acid bases is noncovalent. Also, the results revealed that small diameter SCNT interaction especially SCNT (4, 4) with nucleic acid bases can be useful in practical application area of biomedical fields such detection and drug delivery.

Photonic-plasmonic hybrid single-molecule nanosensor measures the effect of fluorescent labels on DNA-protein dynamics

PubMed Central

Liang, Feng; Guo, Yuzheng; Hou, Shaocong; Quan, Qimin

2017-01-01

Current methods to study molecular interactions require labeling the subject molecules with fluorescent reporters. However, the effect of the fluorescent reporters on molecular dynamics has not been quantified because of a lack of alternative methods. We develop a hybrid photonic-plasmonic antenna-in-a-nanocavity single-molecule biosensor to study DNA-protein dynamics without using fluorescent labels. Our results indicate that the fluorescein and fluorescent protein labels decrease the interaction between a single DNA and a protein due to weakened electrostatic interaction. Although the study is performed on the DNA-XPA system, the conclusion has a general implication that the traditional fluorescent labeling methods might be misestimating the molecular interactions. PMID:28560341

A computational study on the interaction between a vortex and a shock wave

NASA Technical Reports Server (NTRS)

Meadows, Kristine R.; Kumar, Ajay; Hussaini, M. Y.

1989-01-01

A computational study of two-dimensional shock vortex interaction is discussed in this paper. A second order upwind finite volume method is used to solve the Euler equations in conservation form. In this method, the shock wave is captured rather than fitted so that the cases where shock vortex interaction may cause secondary shocks can also be investigated. The effects of vortex strength on the computed flow and acoustic field generated by the interaction are qualitatively evaluated.

Nano Cu interaction with single amino acid tyrosine derived self-assemblies; study through XRD, AFM, confocal Raman microscopy, SERS and DFT methods

NASA Astrophysics Data System (ADS)

Govindhan, Raman; Karthikeyan, Balakrishnan

2017-12-01

3,5-Bis(trifluoromethyl)benzylamine derivatives of single amino acid tyrosine produced self-assembled nanotubes (BTTNTs) as simple Phe-Phe. It has been observed that tyrosine derivative gives exclusively micro and nano tubes irrespective of the concentration of the precursor monomer. However, the introduced xenobiotic trifluoromethyl group (TFM) present in key backbone positionsof the self assembly gives the specific therapeutic function has been highlighted. Herein this work study of such self assembled nanotubes were studied through experimental and theoretical methods. The interaction of nanocopper cluster with the nanotubes (Cu@BTTNTs) were extensively studied by various methods like XRD, AFM, confocal Raman microscopy, SERS and theoretical methods like Mulliken's atomic charge analysis. SERS reveals that the interactions of Cu cluster with NH2, OH, NH and phenyl ring π-electrons system of BTTNTs. DFT studies gave the total dipole moment values of Cu@BTTNTs and explained the nature of interaction.

Comparative Analysis of Western and Domestic Practice of Interactive Method Application in Teaching Social and Political Disciplines at the Universities

ERIC Educational Resources Information Center

Hladka, Halyna

2014-01-01

The comparative analysis of western and domestic practice of introducing active and interactive methods of studies in the process of teaching social science disciplines has been carried out. Features, realities, prospects and limitations in application of interactive methods of teaching in the process of implementing social-political science…

Composite Socio-Technical Systems: A Method for Social Energy Systems

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

Zhang, Yingchen; He, Fulin; Hao, Jun

In order to model and study the interactions between social on technical systems, a systemic method, namely the composite socio-technical systems (CSTS), is proposed to incorporate social systems, technical systems and the interaction mechanism between them. A case study on University of Denver (DU) campus grid is presented in paper to demonstrate the application of the proposed method. In the case study, the social system, technical system, and the interaction mechanism are defined and modelled within the framework of CSTS. Distributed and centralized control and management schemes are investigated, respectively, and numerical results verifies the feasibility and performance of themore » proposed composite system method.« less

A comparative study of multivariable robustness analysis methods as applied to integrated flight and propulsion control

NASA Technical Reports Server (NTRS)

Schierman, John D.; Lovell, T. A.; Schmidt, David K.

1993-01-01

Three multivariable robustness analysis methods are compared and contrasted. The focus of the analysis is on system stability and performance robustness to uncertainty in the coupling dynamics between two interacting subsystems. Of particular interest is interacting airframe and engine subsystems, and an example airframe/engine vehicle configuration is utilized in the demonstration of these approaches. The singular value (SV) and structured singular value (SSV) analysis methods are compared to a method especially well suited for analysis of robustness to uncertainties in subsystem interactions. This approach is referred to here as the interacting subsystem (IS) analysis method. This method has been used previously to analyze airframe/engine systems, emphasizing the study of stability robustness. However, performance robustness is also investigated here, and a new measure of allowable uncertainty for acceptable performance robustness is introduced. The IS methodology does not require plant uncertainty models to measure the robustness of the system, and is shown to yield valuable information regarding the effects of subsystem interactions. In contrast, the SV and SSV methods allow for the evaluation of the robustness of the system to particular models of uncertainty, and do not directly indicate how the airframe (engine) subsystem interacts with the engine (airframe) subsystem.

A strategy to apply quantitative epistasis analysis on developmental traits.

PubMed

Labocha, Marta K; Yuan, Wang; Aleman-Meza, Boanerges; Zhong, Weiwei

2017-05-15

Genetic interactions are keys to understand complex traits and evolution. Epistasis analysis is an effective method to map genetic interactions. Large-scale quantitative epistasis analysis has been well established for single cells. However, there is a substantial lack of such studies in multicellular organisms and their complex phenotypes such as development. Here we present a method to extend quantitative epistasis analysis to developmental traits. In the nematode Caenorhabditis elegans, we applied RNA interference on mutants to inactivate two genes, used an imaging system to quantitatively measure phenotypes, and developed a set of statistical methods to extract genetic interactions from phenotypic measurement. Using two different C. elegans developmental phenotypes, body length and sex ratio, as examples, we showed that this method could accommodate various metazoan phenotypes with performances comparable to those methods in single cell growth studies. Comparing with qualitative observations, this method of quantitative epistasis enabled detection of new interactions involving subtle phenotypes. For example, several sex-ratio genes were found to interact with brc-1 and brd-1, the orthologs of the human breast cancer genes BRCA1 and BARD1, respectively. We confirmed the brc-1 interactions with the following genes in DNA damage response: C34F6.1, him-3 (ortholog of HORMAD1, HORMAD2), sdc-1, and set-2 (ortholog of SETD1A, SETD1B, KMT2C, KMT2D), validating the effectiveness of our method in detecting genetic interactions. We developed a reliable, high-throughput method for quantitative epistasis analysis of developmental phenotypes.

Participant Interaction in Asynchronous Learning Environments: Evaluating Interaction Analysis Methods

ERIC Educational Resources Information Center

Blanchette, Judith

2012-01-01

The purpose of this empirical study was to determine the extent to which three different objective analytical methods--sequence analysis, surface cohesion analysis, and lexical cohesion analysis--can most accurately identify specific characteristics of online interaction. Statistically significant differences were found in all points of…

Research Techniques Made Simple: Emerging Methods to Elucidate Protein Interactions through Spatial Proximity.

PubMed

Che, Yonglu; Khavari, Paul A

2017-12-01

Interactions between proteins are essential for fundamental cellular processes, and the diversity of such interactions enables the vast variety of functions essential for life. A persistent goal in biological research is to develop assays that can faithfully capture different types of protein interactions to allow their study. A major step forward in this direction came with a family of methods that delineates spatial proximity of proteins as an indirect measure of protein-protein interaction. A variety of enzyme- and DNA ligation-based methods measure protein co-localization in space, capturing novel interactions that were previously too transient or low affinity to be identified. Here we review some of the methods that have been successfully used to measure spatially proximal protein-protein interactions. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

A factorial design experiment as a pilot study for noninvasive genetic sampling.

PubMed

Renan, Sharon; Speyer, Edith; Shahar, Naama; Gueta, Tomer; Templeton, Alan R; Bar-David, Shirli

2012-11-01

Noninvasive genetic sampling has increasingly been used in ecological and conservation studies during the last decade. A major part of the noninvasive genetic literature is dedicated to the search for optimal protocols, by comparing different methods of collection, preservation and extraction of DNA from noninvasive materials. However, the lack of quantitative comparisons among these studies and the possibility that different methods are optimal for different systems make it difficult to decide which protocol to use. Moreover, most studies that have compared different methods focused on a single factor - collection, preservation or extraction - while there could be interactions between these factors. We designed a factorial experiment, as a pilot study, aimed at exploring the effect of several collection, preservation and extraction methods, and the interactions between them, on the quality and amplification success of DNA obtained from Asiatic wild ass (Equus hemionus) faeces in Israel. The amplification success rates of one mitochondrial DNA and four microsatellite markers differed substantially as a function of collection, preservation and extraction methods and their interactions. The most efficient combination for our system integrated the use of swabs as a collection method with preservation at -20 °C and with the Qiagen DNA Stool Kit with modifications as the DNA extraction method. The significant interaction found between the collection, preservation methods and the extraction methods reinforces the importance of conducting a factorial design experiment, rather than examining each factor separately, as a pilot study before initiating a full-scale noninvasive research project. © 2012 Blackwell Publishing Ltd.

A deeper look at two concepts of measuring gene-gene interactions: logistic regression and interaction information revisited.

PubMed

Mielniczuk, Jan; Teisseyre, Paweł

2018-03-01

Detection of gene-gene interactions is one of the most important challenges in genome-wide case-control studies. Besides traditional logistic regression analysis, recently the entropy-based methods attracted a significant attention. Among entropy-based methods, interaction information is one of the most promising measures having many desirable properties. Although both logistic regression and interaction information have been used in several genome-wide association studies, the relationship between them has not been thoroughly investigated theoretically. The present paper attempts to fill this gap. We show that although certain connections between the two methods exist, in general they refer two different concepts of dependence and looking for interactions in those two senses leads to different approaches to interaction detection. We introduce ordering between interaction measures and specify conditions for independent and dependent genes under which interaction information is more discriminative measure than logistic regression. Moreover, we show that for so-called perfect distributions those measures are equivalent. The numerical experiments illustrate the theoretical findings indicating that interaction information and its modified version are more universal tools for detecting various types of interaction than logistic regression and linkage disequilibrium measures. © 2017 WILEY PERIODICALS, INC.

Quantification of protein interaction kinetics in a micro droplet

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

Yin, L. L.; College of Chemistry and Chemical Engineering, Chongqing University, Chongqing 400044; Wang, S. P., E-mail: shaopeng.wang@asu.edu, E-mail: njtao@asu.edu

Characterization of protein interactions is essential to the discovery of disease biomarkers, the development of diagnostic assays, and the screening for therapeutic drugs. Conventional flow-through kinetic measurements need relative large amount of sample that is not feasible for precious protein samples. We report a novel method to measure protein interaction kinetics in a single droplet with sub microliter or less volume. A droplet in a humidity-controlled environmental chamber is replacing the microfluidic channels as the reactor for the protein interaction. The binding process is monitored by a surface plasmon resonance imaging (SPRi) system. Association curves are obtained from the averagemore » SPR image intensity in the center area of the droplet. The washing step required by conventional flow-through SPR method is eliminated in the droplet method. The association and dissociation rate constants and binding affinity of an antigen-antibody interaction are obtained by global fitting of association curves at different concentrations. The result obtained by this method is accurate as validated by conventional flow-through SPR system. This droplet-based method not only allows kinetic studies for proteins with limited supply but also opens the door for high-throughput protein interaction study in a droplet-based microarray format that enables measurement of many to many interactions on a single chip.« less

Quantification of protein interaction kinetics in a micro droplet

NASA Astrophysics Data System (ADS)

Yin, L. L.; Wang, S. P.; Shan, X. N.; Zhang, S. T.; Tao, N. J.

2015-11-01

Characterization of protein interactions is essential to the discovery of disease biomarkers, the development of diagnostic assays, and the screening for therapeutic drugs. Conventional flow-through kinetic measurements need relative large amount of sample that is not feasible for precious protein samples. We report a novel method to measure protein interaction kinetics in a single droplet with sub microliter or less volume. A droplet in a humidity-controlled environmental chamber is replacing the microfluidic channels as the reactor for the protein interaction. The binding process is monitored by a surface plasmon resonance imaging (SPRi) system. Association curves are obtained from the average SPR image intensity in the center area of the droplet. The washing step required by conventional flow-through SPR method is eliminated in the droplet method. The association and dissociation rate constants and binding affinity of an antigen-antibody interaction are obtained by global fitting of association curves at different concentrations. The result obtained by this method is accurate as validated by conventional flow-through SPR system. This droplet-based method not only allows kinetic studies for proteins with limited supply but also opens the door for high-throughput protein interaction study in a droplet-based microarray format that enables measurement of many to many interactions on a single chip.

Modeling and Detecting Feature Interactions among Integrated Services of Home Network Systems

NASA Astrophysics Data System (ADS)

Igaki, Hiroshi; Nakamura, Masahide

This paper presents a framework for formalizing and detecting feature interactions (FIs) in the emerging smart home domain. We first establish a model of home network system (HNS), where every networked appliance (or the HNS environment) is characterized as an object consisting of properties and methods. Then, every HNS service is defined as a sequence of method invocations of the appliances. Within the model, we next formalize two kinds of FIs: (a) appliance interactions and (b) environment interactions. An appliance interaction occurs when two method invocations conflict on the same appliance, whereas an environment interaction arises when two method invocations conflict indirectly via the environment. Finally, we propose offline and online methods that detect FIs before service deployment and during execution, respectively. Through a case study with seven practical services, it is shown that the proposed framework is generic enough to capture feature interactions in HNS integrated services. We also discuss several FI resolution schemes within the proposed framework.

Quantum mechanics study of repulsive π-π interaction and flexibility of phenyl moiety in the iron azodioxide complex

NASA Astrophysics Data System (ADS)

Liu, Yuemin; Liu, Yucheng; Murru, Siva; Tzeng, Nianfeng; Srivastava, Radhey S.

2015-10-01

In this study, repulsive π-π interactions within iron azodioxide complex Fe[Ph(O)NN(O)Ph]3 were quantum mechanically characterized using DFT, MP2 and CCSD(T) methods. Flexibility of six phenyl moieties in this complex structure was also investigated by structural optimization approach using the DFT methods. Our MP2 and CCSD(T) calculations of the closest pair provided interaction energy of 6.62 and 8.29 kcal/mol respectively, which indicate a strongest repulsion among these intra-molecular π-π interactions. Interaction energy of the particular π-π pair calculated from 24 hybrid DFT methods ranges from 4.56 kcal/mol from BHandH method to 15.15 kcal/mol from O3LYP method. Cares should be exercised when interpreting interaction energy and geometry optimization from DFT simulation of systems containing π-π interaction. Comparison between the DFT results and the benchmark CCSD(T) results shows that the DFT calculations of π-π interaction are reasonable but still need to be interpreted with caution. Furthermore, MP2 interaction energy of -44.69 kcal/mol between two substituted π systems/phenyl rings Ph(O)N-moieties suggested that above energetically unfavorable π-π interaction can be compensated by the covalent bond N-N in a single ligand Ph(O)NN(O)Ph, which allows for a reasonable stability across the complex molecules. Optimizations of the entire complex molecule using B3LYP and M06HF methods produced a large variation of π-π distances and orientations, which implied that the complex molecule may perform catalysis at room temperature.

In Vivo Photo-Cross-Linking to Study T3S Interactions Demonstrated Using the Yersinia pestis T3S System.

PubMed

Henderson, Thomas A; Nilles, Matthew L

2017-01-01

Cross-linking of proteins is effective in determining protein-protein interactions. The use of photo-cross-linkers was developed to study protein interactions in several manners. One method involved the incorporation of photo-activatable cross-linking groups into chemically synthesized peptides. A second approach relies on incorporation of photo-activatable cross-linking groups into proteins using tRNAs with chemically bound photo-activatable amino acids with suppressor tRNAs translational systems to incorporate the tags into specific sites. A third system was made possible by the development of photoreactive amino acids that use the normal cellular tRNAs and aminoacyl tRNA synthetases. In this method, the third system is used to demonstrate its utility for the study of T3S system interactions. This method describes how two photo-activatable amino acids, photo-methionine and photo-leucine, that use the normal cellular machinery are incorporated into Yersinia pestis and used to study interactions in the T3S system. To demonstrate the system, the method was used to cross-link the T3S regulatory proteins LcrG and LcrV.

Membrane fouling in a submerged membrane bioreactor: New method and its applications in interfacial interaction quantification.

PubMed

Hong, Huachang; Cai, Xiang; Shen, Liguo; Li, Renjie; Lin, Hongjun

2017-10-01

Quantification of interfacial interactions between two rough surfaces represents one of the most pressing requirements for membrane fouling prediction and control in membrane bioreactors (MBRs). This study firstly constructed regularly rough membrane and particle surfaces by using rigorous mathematical equations. Thereafter, a new method involving surface element integration (SEI) method, differential geometry and composite Simpson's rule was proposed to quantify the interfacial interactions between the two constructed rough surfaces. This new method were then applied to investigate interfacial interactions in a MBR with the data of surface properties of membrane and foulants experimentally measured. The feasibility of the new method was verified. It was found that asperity amplitude and period of the membrane surface exerted profound effects on the total interaction. The new method had broad potential application fields especially including guiding membrane surface design for membrane fouling mitigation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Genetic Risk by Experience Interaction for Childhood Internalizing Problems: Converging Evidence across Multiple Methods

ERIC Educational Resources Information Center

Vendlinski, Matthew K.; Lemery-Chalfant, Kathryn; Essex, Marilyn J.; Goldsmith, H. Hill

2011-01-01

Background: Identifying how genetic risk interacts with experience to predict psychopathology is an important step toward understanding the etiology of mental health problems. Few studies have examined genetic risk by experience interaction (GxE) in the development of childhood psychopathology. Methods: We used both co-twin and parent mental…

GEOPHYSICS, ASTRONOMY AND ASTROPHYSICS: Numerical method of studying nonlinear interactions between long waves and multiple short waves

NASA Astrophysics Data System (ADS)

Xie, Tao; Kuang, Hai-Lan; William, Perrie; Zou, Guang-Hui; Nan, Cheng-Feng; He, Chao; Shen, Tao; Chen, Wei

2009-07-01

Although the nonlinear interactions between a single short gravity wave and a long wave can be solved analytically, the solution is less tractable in more general cases involving multiple short waves. In this work we present a numerical method of studying nonlinear interactions between a long wave and multiple short harmonic waves in infinitely deep water. Specifically, this method is applied to the calculation of the temporal and spatial evolutions of the surface elevations in which a given long wave interacts with several short harmonic waves. Another important application of our method is to quantitatively analyse the nonlinear interactions between an arbitrary short wave train and another short wave train. From simulation results, we obtain that the mechanism for the nonlinear interactions between one short wave train and another short wave train (expressed as wave train 2) leads to the energy focusing of the other short wave train (expressed as wave train 3). This mechanism occurs on wave components with a narrow frequency bandwidth, whose frequencies are near that of wave train 3.

Probing fibronectin–antibody interactions using AFM force spectroscopy and lateral force microscopy

PubMed Central

Kulik, Andrzej J; Lee, Kyumin; Pyka-Fościak, Grazyna; Nowak, Wieslaw

2015-01-01

Summary The first experiment showing the effects of specific interaction forces using lateral force microscopy (LFM) was demonstrated for lectin–carbohydrate interactions some years ago. Such measurements are possible under the assumption that specific forces strongly dominate over the non-specific ones. However, obtaining quantitative results requires the complex and tedious calibration of a torsional force. Here, a new and relatively simple method for the calibration of the torsional force is presented. The proposed calibration method is validated through the measurement of the interaction forces between human fibronectin and its monoclonal antibody. The results obtained using LFM and AFM-based classical force spectroscopies showed similar unbinding forces recorded at similar loading rates. Our studies verify that the proposed lateral force calibration method can be applied to study single molecule interactions. PMID:26114080

Virtual standardized patients: an interactive method to examine variation in depression care among primary care physicians

PubMed Central

Hooper, Lisa M.; Weinfurt, Kevin P.; Cooper, Lisa A.; Mensh, Julie; Harless, William; Kuhajda, Melissa C.; Epstein, Steven A.

2009-01-01

Background Some primary care physicians provide less than optimal care for depression (Kessler et al., Journal of the American Medical Association 291, 2581–90, 2004). However, the literature is not unanimous on the best method to use in order to investigate this variation in care. To capture variations in physician behaviour and decision making in primary care settings, 32 interactive CD-ROM vignettes were constructed and tested. Aim and method The primary aim of this methods-focused paper was to review the extent to which our study method – an interactive CD-ROM patient vignette methodology – was effective in capturing variation in physician behaviour. Specifically, we examined the following questions: (a) Did the interactive CD-ROM technology work? (b) Did we create believable virtual patients? (c) Did the research protocol enable interviews (data collection) to be completed as planned? (d) To what extent was the targeted study sample size achieved? and (e) Did the study interview protocol generate valid and reliable quantitative data and rich, credible qualitative data? Findings Among a sample of 404 randomly selected primary care physicians, our voice-activated interactive methodology appeared to be effective. Specifically, our methodology – combining interactive virtual patient vignette technology, experimental design, and expansive open-ended interview protocol – generated valid explanations for variations in primary care physician practice patterns related to depression care. PMID:20463864

An accurate cost effective DFT approach to study the sensing behaviour of polypyrrole towards nitrate ions in gas and aqueous phases.

PubMed

Wasim, Fatima; Mahmood, Tariq; Ayub, Khurshid

2016-07-28

Density functional theory (DFT) calculations have been performed to study the response of polypyrrole towards nitrate ions in gas and aqueous phases. First, an accurate estimate of interaction energies is obtained by methods calibrated against the gold standard CCSD(T) method. Then, a number of low cost DFT methods are also evaluated for their ability to accurately estimate the binding energies of polymer-nitrate complexes. The low cost methods evaluated here include dispersion corrected potential (DCP), Grimme's D3 correction, counterpoise correction of the B3LYP method, and Minnesota functionals (M05-2X). The interaction energies calculated using the counterpoise (CP) correction and DCP methods at the B3LYP level are in better agreement with the interaction energies calculated using the calibrated methods. The interaction energies of an infinite polymer (polypyrrole) with nitrate ions are calculated by a variety of low cost methods in order to find the associated errors. The electronic and spectroscopic properties of polypyrrole oligomers nPy (where n = 1-9) and nPy-NO3(-) complexes are calculated, and then extrapolated for an infinite polymer through a second degree polynomial fit. Charge analysis, frontier molecular orbital (FMO) analysis and density of state studies also reveal the sensing ability of polypyrrole towards nitrate ions. Interaction energies, charge analysis and density of states analyses illustrate that the response of polypyrrole towards nitrate ions is considerably reduced in the aqueous medium (compared to the gas phase).

A combined database related and de novo MS-identification of yeast mannose-1-phosphate guanyltransferase PSA1 interaction partners at different phases of batch cultivation

NASA Astrophysics Data System (ADS)

Parviainen, Ville; Joenväärä, Sakari; Peltoniemi, Hannu; Mattila, Pirkko; Renkonen, Risto

2009-04-01

Mass spectrometry-based proteomic research has become one of the main methods in protein-protein interaction research. Several high throughput studies have established an interaction landscape of exponentially growing Baker's yeast culture. However, many of the protein-protein interactions are likely to change in different environmental conditions. In order to examine the dynamic nature of the protein interactions we isolated the protein complexes of mannose-1-phosphate guanyltransferase PSA1 from Saccharomyces cerevisiae at four different time points during batch cultivation. We used the tandem affinity purification (TAP)-method to purify the complexes and subjected the tryptic peptides to LC-MS/MS. The resulting peak lists were analyzed with two different methods: the database related protein identification program X!Tandem and the de novo sequencing program Lutefisk. We observed significant changes in the interactome of PSA1 during the batch cultivation and identified altogether 74 proteins interacting with PSA1 of which only six were found to interact during all time points. All the other proteins showed a more dynamic nature of binding activity. In this study we also demonstrate the benefit of using both database related and de novo methods in the protein interaction research to enhance both the quality and the quantity of observations.

Enhanced identification of synergistic and antagonistic emergent interactions among three or more drugs

PubMed Central

White, Cynthia; Mao, Zhiyuan; Savage, Van M.

2016-01-01

Interactions among drugs play a critical role in the killing efficacy of multi-drug treatments. Recent advances in theory and experiment for three-drug interactions enable the search for emergent interactions—ones not predictable from pairwise interactions. Previous work has shown it is easier to detect synergies and antagonisms among pairwise interactions when a rescaling method is applied to the interaction metric. However, no study has carefully examined whether new types of normalization might be needed for emergence. Here, we propose several rescaling methods for enhancing the classification of the higher order drug interactions based on our conceptual framework. To choose the rescaling that best separates synergism, antagonism and additivity, we conducted bacterial growth experiments in the presence of single, pairwise and triple-drug combinations among 14 antibiotics. We found one of our rescaling methods is far better at distinguishing synergistic and antagonistic emergent interactions than any of the other methods. Using our new method, we find around 50% of emergent interactions are additive, much less than previous reports of greater than 90% additivity. We conclude that higher order emergent interactions are much more common than previously believed, and we argue these findings for drugs suggest that appropriate rescaling is crucial to infer higher order interactions. PMID:27278366

Fusing literature and full network data improves disease similarity computation.

PubMed

Li, Ping; Nie, Yaling; Yu, Jingkai

2016-08-30

Identifying relatedness among diseases could help deepen understanding for the underlying pathogenic mechanisms of diseases, and facilitate drug repositioning projects. A number of methods for computing disease similarity had been developed; however, none of them were designed to utilize information of the entire protein interaction network, using instead only those interactions involving disease causing genes. Most of previously published methods required gene-disease association data, unfortunately, many diseases still have very few or no associated genes, which impeded broad adoption of those methods. In this study, we propose a new method (MedNetSim) for computing disease similarity by integrating medical literature and protein interaction network. MedNetSim consists of a network-based method (NetSim), which employs the entire protein interaction network, and a MEDLINE-based method (MedSim), which computes disease similarity by mining the biomedical literature. Among function-based methods, NetSim achieved the best performance. Its average AUC (area under the receiver operating characteristic curve) reached 95.2 %. MedSim, whose performance was even comparable to some function-based methods, acquired the highest average AUC in all semantic-based methods. Integration of MedSim and NetSim (MedNetSim) further improved the average AUC to 96.4 %. We further studied the effectiveness of different data sources. It was found that quality of protein interaction data was more important than its volume. On the contrary, higher volume of gene-disease association data was more beneficial, even with a lower reliability. Utilizing higher volume of disease-related gene data further improved the average AUC of MedNetSim and NetSim to 97.5 % and 96.7 %, respectively. Integrating biomedical literature and protein interaction network can be an effective way to compute disease similarity. Lacking sufficient disease-related gene data, literature-based methods such as MedSim can be a great addition to function-based algorithms. It may be beneficial to steer more resources torward studying gene-disease associations and improving the quality of protein interaction data. Disease similarities can be computed using the proposed methods at http:// www.digintelli.com:8000/ .

Closed-loop bird-computer interactions: a new method to study the role of bird calls.

PubMed

Lerch, Alexandre; Roy, Pierre; Pachet, François; Nagle, Laurent

2011-03-01

In the field of songbird research, many studies have shown the role of male songs in territorial defense and courtship. Calling, another important acoustic communication signal, has received much less attention, however, because calls are assumed to contain less information about the emitter than songs do. Birdcall repertoire is diverse, and the role of calls has been found to be significant in the area of social interaction, for example, in pair, family, and group cohesion. However, standard methods for studying calls do not allow precise and systematic study of their role in communication. We propose herein a new method to study bird vocal interaction. A closed-loop computer system interacts with canaries, Serinus canaria, by (1) automatically classifying two basic types of canary vocalization, single versus repeated calls, as they are produced by the subject, and (2) responding with a preprogrammed call type recorded from another bird. This computerized animal-machine interaction requires no human interference. We show first that the birds do engage in sustained interactions with the system, by studying the rate of single and repeated calls for various programmed protocols. We then show that female canaries differentially use single and repeated calls. First, they produce significantly more single than repeated calls, and second, the rate of single calls is associated with the context in which they interact, whereas repeated calls are context independent. This experiment is the first illustration of how closed-loop bird-computer interaction can be used productively to study social relationships. © Springer-Verlag 2010

Computational methods for identifying miRNA sponge interactions.

PubMed

Le, Thuc Duy; Zhang, Junpeng; Liu, Lin; Li, Jiuyong

2017-07-01

Recent findings show that coding genes are not the only targets that miRNAs interact with. In fact, there is a pool of different RNAs competing with each other to attract miRNAs for interactions, thus acting as competing endogenous RNAs (ceRNAs). The ceRNAs indirectly regulate each other via the titration mechanism, i.e. the increasing concentration of a ceRNA will decrease the number of miRNAs that are available for interacting with other targets. The cross-talks between ceRNAs, i.e. their interactions mediated by miRNAs, have been identified as the drivers in many disease conditions, including cancers. In recent years, some computational methods have emerged for identifying ceRNA-ceRNA interactions. However, there remain great challenges and opportunities for developing computational methods to provide new insights into ceRNA regulatory mechanisms.In this paper, we review the publically available databases of ceRNA-ceRNA interactions and the computational methods for identifying ceRNA-ceRNA interactions (also known as miRNA sponge interactions). We also conduct a comparison study of the methods with a breast cancer dataset. Our aim is to provide a current snapshot of the advances of the computational methods in identifying miRNA sponge interactions and to discuss the remaining challenges. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A comparative study of traditional lecture methods and interactive lecture methods in introductory geology courses for non-science majors at the college level

NASA Astrophysics Data System (ADS)

Hundley, Stacey A.

In recent years there has been a national call for reform in undergraduate science education. The goal of this reform movement in science education is to develop ways to improve undergraduate student learning with an emphasis on developing more effective teaching practices. Introductory science courses at the college level are generally taught using a traditional lecture format. Recent studies have shown incorporating active learning strategies within the traditional lecture classroom has positive effects on student outcomes. This study focuses on incorporating interactive teaching methods into the traditional lecture classroom to enhance student learning for non-science majors enrolled in introductory geology courses at a private university. Students' experience and instructional preferences regarding introductory geology courses were identified from survey data analysis. The information gained from responses to the questionnaire was utilized to develop an interactive lecture introductory geology course for non-science majors. Student outcomes were examined in introductory geology courses based on two teaching methods: interactive lecture and traditional lecture. There were no significant statistical differences between the groups based on the student outcomes and teaching methods. Incorporating interactive lecture methods did not statistically improve student outcomes when compared to traditional lecture teaching methods. However, the responses to the survey revealed students have a preference for introductory geology courses taught with lecture and instructor-led discussions and students prefer to work independently or in small groups. The results of this study are useful to individuals who teach introductory geology courses and individuals who teach introductory science courses for non-science majors at the college level.

[Detection of protein-protein interactions by FRET and BRET methods].

PubMed

Matoulková, E; Vojtěšek, B

2014-01-01

Nowadays, in vivo protein-protein interaction studies have become preferable detecting meth-ods that enable to show or specify (already known) protein interactions and discover their inhibitors. They also facilitate detection of protein conformational changes and discovery or specification of signaling pathways in living cells. One group of in vivo methods enabling these findings is based on fluorescent resonance energy transfer (FRET) and its bio-luminescent modification (BRET). They are based on visualization of protein-protein interactions via light or enzymatic excitation of fluorescent or bio-luminescent proteins. These methods allow not only protein localization within the cell or its organelles (or small animals) but they also allow us to quantify fluorescent signals and to discover weak or strong interaction partners. In this review, we explain the principles of FRET and BRET, their applications in the characterization of protein-protein interactions and we describe several findings using these two methods that clarify molecular and cellular mechanisms and signals related to cancer biology.

Search for neutrino oscillations in the MINOS experiment by using quasi-elastic interactions

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

Piteira, Rodolphe

2005-09-29

The enthusiasm of the scientific community for studying oscillations of neutrinos is equaled only by the mass of their detectors. The MINOS experiment determines and compares the near spectrum of muonic neutrinos from the NUMI beam to the far one, in order to measure two oscillation parameters: Δmmore » $$2\\atop{23}$$ and sin 2 (2θ 23). The spectra are obtained by analyzing the charged current interactions which difficulty lies in identifying the interactions products (e.g. muons). An alternative method identifying the traces of muons, bent by the magnetic field of the detectors, and determining their energies is presented in this manuscript. The sensitivity of the detectors is optimal for the quasi-elastic interactions, for which a selection method is proposed, to study their oscillation. Even though it reduces the statistics, such a study introduces fewer systematic errors, constituting the ideal method on the long range.« less

Theoretical study on the polar hydrogen-π (Hp-π) interactions between protein side chains

PubMed Central

2013-01-01

Background In the study of biomolecular structures and interactions the polar hydrogen-π bonds (Hp-π) are an extensive molecular interaction type. In proteins 11 of 20 natural amino acids and in DNA (or RNA) all four nucleic acids are involved in this type interaction. Results The Hp-π in proteins are studied using high level QM method CCSD/6-311 + G(d,p) + H-Bq (ghost hydrogen basis functions) in vacuum and in solutions (water, acetonitrile, and cyclohexane). Three quantum chemical methods (B3LYP, CCSD, and CCSD(T)) and three basis sets (6-311 + G(d,p), TZVP, and cc-pVTZ) are compared. The Hp-π donors include R2NH, RNH2, ROH, and C6H5OH; and the acceptors are aromatic amino acids, peptide bond unit, and small conjugate π-groups. The Hp-π interaction energies of four amino acid pairs (Ser-Phe, Lys-Phe, His-Phe, and Tyr-Phe) are quantitatively calculated. Conclusions Five conclusion points are abstracted from the calculation results. (1) The common DFT method B3LYP fails in describing the Hp-π interactions. On the other hand, CCSD/6-311 + G(d,p) plus ghost atom H-Bq can yield better results, very close to the state-of-the-art method CCSD(T)/cc-pVTZ. (2) The Hp-π interactions are point to π-plane interactions, possessing much more interaction conformations and broader energy range than other interaction types, such as common hydrogen bond and electrostatic interactions. (3) In proteins the Hp-π interaction energies are in the range 10 to 30 kJ/mol, comparable or even larger than common hydrogen bond interactions. (4) The bond length of Hp-π interactions are in the region from 2.30 to 3.00 Å at the perpendicular direction to the π-plane, much longer than the common hydrogen bonds (~1.9 Å). (5) Like common hydrogen bond interactions, the Hp-π interactions are less affected by solvation effects. PMID:23705926

Teaching Undergraduate Marketing Students Using "Hot Seating through Puppetry": An Exploratory Study

ERIC Educational Resources Information Center

Pearce, Glenn; Hardiman, Nigel

2012-01-01

Changes in preferred methods of learning among many students in recent years have challenged educators to introduce more interactive and experiential teaching methods. "Hot seating"--where a person, such as an invited subject expert is interviewed by an audience--is a well-established interactive method of learning, but is often limited…

Interactive Methods of Teaching Physics at Technical Universities

ERIC Educational Resources Information Center

Krišták, L'uboš; Nemec, Miroslav; Danihelová, Zuzana

2014-01-01

The paper presents results of "non-traditional" teaching of the basic course of Physics in the first year of study at the Technical University in Zvolen, specifically teaching via interactive method enriched with problem tasks and experiments. This paper presents also research results of the use of the given method in conditions of…

The Keyword Method and Children's Vocabulary Learning: An Interaction with Vocabulary Knowledge.

ERIC Educational Resources Information Center

McGivern, Julie E.; Levin, Joel R.

A study explored a potential aptitude-by-treatment interaction associated with the keyword method of vocabulary acquisition. This method is a two-stage mnemonic process whereby an unfamiliar term is first transformed into a familiar concrete stimulus and then a thematic relationship is created between the transformed stimulus and the information…

Analysis of the Interaction of Student Characteristics with Method in Micro-Teaching.

ERIC Educational Resources Information Center

Chavers, Katherine; And Others

A study examined the comparative effects on microteaching performance of (1) eight different methods of teacher training and (2) the interaction of method with student characteristics. Subjects, 71 enrollees in an educational psychology course, were randomly assigned to eight treatment groups (including one control group). Treatments consisted of…

Users' Interaction with World Wide Web Resources: An Exploratory Study Using a Holistic Approach.

ERIC Educational Resources Information Center

Wang, Peiling; Hawk, William B.; Tenopir, Carol

2000-01-01

Presents results of a study that explores factors of user-Web interaction in finding factual information, develops a conceptual framework for studying user-Web interaction, and applies a process-tracing method for conducting holistic user-Web studies. Describes measurement techniques and proposes a model consisting of the user, interface, and the…

Cation-π Interactions: Computational Analyses of the Aromatic Box Motif and the Fluorination Strategy for Experimental Evaluation

PubMed Central

Davis, Matthew R.; Dougherty, Dennis A.

2015-01-01

Cation-π interactions are common in biological systems, and many structural studies have revealed the aromatic box as a common motif. With the aim of understanding the nature of the aromatic box, several computational methods were evaluated for their ability to reproduce experimental cation-π binding energies. We find the DFT method M06 with the 6-31G(d,p) basis set performs best of several methods tested. The binding of benzene to a number of different cations (sodium, potassium, ammonium, tetramethylammonium, and guanidinium) was studied. In addition, the binding of the organic cations NH4+ and NMe4+ to ab initio generated aromatic boxes as well as examples of aromatic boxes from protein crystal structures were investigated. These data, along with a study of the distance dependence of the cation-π interaction, indicate that multiple aromatic residues can meaningfully contribute to cation binding, even with displacements of more than an angstrom from the optimal cation-π interaction. Progressive fluorination of benzene and indole was studied as well, and binding energies obtained were used to reaffirm the validity of the “fluorination strategy” to study cation-π interactions in vivo. PMID:26467787

Cation-π interactions: computational analyses of the aromatic box motif and the fluorination strategy for experimental evaluation.

PubMed

Davis, Matthew R; Dougherty, Dennis A

2015-11-21

Cation-π interactions are common in biological systems, and many structural studies have revealed the aromatic box as a common motif. With the aim of understanding the nature of the aromatic box, several computational methods were evaluated for their ability to reproduce experimental cation-π binding energies. We find the DFT method M06 with the 6-31G(d,p) basis set performs best of several methods tested. The binding of benzene to a number of different cations (sodium, potassium, ammonium, tetramethylammonium, and guanidinium) was studied. In addition, the binding of the organic cations NH4(+) and NMe4(+) to ab initio generated aromatic boxes as well as examples of aromatic boxes from protein crystal structures were investigated. These data, along with a study of the distance dependence of the cation-π interaction, indicate that multiple aromatic residues can meaningfully contribute to cation binding, even with displacements of more than an angstrom from the optimal cation-π interaction. Progressive fluorination of benzene and indole was studied as well, and binding energies obtained were used to reaffirm the validity of the "fluorination strategy" to study cation-π interactions in vivo.

Interactive Visualization of Dependencies

ERIC Educational Resources Information Center

Moreno, Camilo Arango; Bischof, Walter F.; Hoover, H. James

2012-01-01

We present an interactive tool for browsing course requisites as a case study of dependency visualization. This tool uses multiple interactive visualizations to allow the user to explore the dependencies between courses. A usability study revealed that the proposed browser provides significant advantages over traditional methods, in terms of…

Study and selection of in vivo protein interactions by coupling bimolecular fluorescence complementation and flow cytometry.

PubMed

Morell, Montse; Espargaro, Alba; Aviles, Francesc Xavier; Ventura, Salvador

2008-01-01

We present a high-throughput approach to study weak protein-protein interactions by coupling bimolecular fluorescent complementation (BiFC) to flow cytometry (FC). In BiFC, the interaction partners (bait and prey) are fused to two rationally designed fragments of a fluorescent protein, which recovers its function upon the binding of the interacting proteins. For weak protein-protein interactions, the detected fluorescence is proportional to the interaction strength, thereby allowing in vivo discrimination between closely related binders with different affinity for the bait protein. FC provides a method for high-speed multiparametric data acquisition and analysis; the assay is simple, thousands of cells can be analyzed in seconds and, if required, selected using fluorescence-activated cell sorting (FACS). The combination of both methods (BiFC-FC) provides a technically straightforward, fast and highly sensitive method to validate weak protein interactions and to screen and identify optimal ligands in biologically synthesized libraries. Once plasmids encoding the protein fusions have been obtained, the evaluation of a specific interaction, the generation of a library and selection of active partners using BiFC-FC can be accomplished in 5 weeks.

The Effects of Web-Based Interactive Virtual Tours on the Development of Prospective Mathematics Teachers' Spatial Skills

ERIC Educational Resources Information Center

Kurtulus, Aytac

2013-01-01

The aim of this study was to investigate the effects of web-based interactive virtual tours on the development of prospective mathematics teachers' spatial skills. The study was designed based on experimental method. The "one-group pre-test post-test design" of this method was taken as the research model. The study was conducted with 3rd year…

Evaluation of DFT methods for computing the interaction energies of homomolecular and heteromolecular dimers of monosubstituted benzene

NASA Astrophysics Data System (ADS)

Godfrey-Kittle, Andrew; Cafiero, Mauricio

We present density functional theory (DFT) interaction energies for the sandwich and T-shaped conformers of substituted benzene dimers. The DFT functionals studied include TPSS, HCTH407, B3LYP, and X3LYP. We also include Hartree-Fock (HF) and second-order Møller-Plesset perturbation theory calculations (MP2), as well as calculations using a new functional, P3LYP, which includes PBE and HF exchange and LYP correlation. Although DFT methods do not explicitly account for the dispersion interactions important in the benzene-dimer interactions, we find that our new method, P3LYP, as well as HCTH407 and TPSS, match MP2 and CCSD(T) calculations much better than the hybrid methods B3LYP and X3LYP methods do.

A Mixed Methods Study of the Relationship between Student Perceptions of Teacher-Student Interactions and Motivation in Middle Level Science

ERIC Educational Resources Information Center

Smart, Julie B.

2014-01-01

This mixed-methods study examined the relationship between middle level science students' perceptions of teacher-student interactions and students' science motivation, particulary their efficacy, value, and goal orientation for learning science. In this sequential explanatory design, quantitative and qualitative data were collected in two phases,…

Platform construction and extraction mechanism study of magnetic mixed hemimicelles solid-phase extraction

NASA Astrophysics Data System (ADS)

Xiao, Deli; Zhang, Chan; He, Jia; Zeng, Rong; Chen, Rong; He, Hua

2016-12-01

Simple, accurate and high-throughput pretreatment method would facilitate large-scale studies of trace analysis in complex samples. Magnetic mixed hemimicelles solid-phase extraction has the power to become a key pretreatment method in biological, environmental and clinical research. However, lacking of experimental predictability and unsharpness of extraction mechanism limit the development of this promising method. Herein, this work tries to establish theoretical-based experimental designs for extraction of trace analytes from complex samples using magnetic mixed hemimicelles solid-phase extraction. We selected three categories and six sub-types of compounds for systematic comparative study of extraction mechanism, and comprehensively illustrated the roles of different force (hydrophobic interaction, π-π stacking interactions, hydrogen-bonding interaction, electrostatic interaction) for the first time. What’s more, the application guidelines for supporting materials, surfactants and sample matrix were also summarized. The extraction mechanism and platform established in the study render its future promising for foreseeable and efficient pretreatment under theoretical based experimental design for trace analytes from environmental, biological and clinical samples.

A coupled sharp-interface immersed boundary-finite-element method for flow-structure interaction with application to human phonation.

PubMed

Zheng, X; Xue, Q; Mittal, R; Beilamowicz, S

2010-11-01

A new flow-structure interaction method is presented, which couples a sharp-interface immersed boundary method flow solver with a finite-element method based solid dynamics solver. The coupled method provides robust and high-fidelity solution for complex flow-structure interaction (FSI) problems such as those involving three-dimensional flow and viscoelastic solids. The FSI solver is used to simulate flow-induced vibrations of the vocal folds during phonation. Both two- and three-dimensional models have been examined and qualitative, as well as quantitative comparisons, have been made with established results in order to validate the solver. The solver is used to study the onset of phonation in a two-dimensional laryngeal model and the dynamics of the glottal jet in a three-dimensional model and results from these studies are also presented.

Setting up the Interactive Educational Process in Higher Education

ERIC Educational Resources Information Center

Ponomariova, Olga Nikolaevna; Vasin?, Olga Nikolaevna

2016-01-01

This article aims to discuss the opportunities in the interactive teaching in higher education. The study presents the methodological approach of understanding the notions of "teaching technology" and "interactive teaching methods". The originality of the study consists in the authors' definition of the situation in "the…

Estimating and testing interactions when explanatory variables are subject to non-classical measurement error.

PubMed

Murad, Havi; Kipnis, Victor; Freedman, Laurence S

2016-10-01

Assessing interactions in linear regression models when covariates have measurement error (ME) is complex.We previously described regression calibration (RC) methods that yield consistent estimators and standard errors for interaction coefficients of normally distributed covariates having classical ME. Here we extend normal based RC (NBRC) and linear RC (LRC) methods to a non-classical ME model, and describe more efficient versions that combine estimates from the main study and internal sub-study. We apply these methods to data from the Observing Protein and Energy Nutrition (OPEN) study. Using simulations we show that (i) for normally distributed covariates efficient NBRC and LRC were nearly unbiased and performed well with sub-study size ≥200; (ii) efficient NBRC had lower MSE than efficient LRC; (iii) the naïve test for a single interaction had type I error probability close to the nominal significance level, whereas efficient NBRC and LRC were slightly anti-conservative but more powerful; (iv) for markedly non-normal covariates, efficient LRC yielded less biased estimators with smaller variance than efficient NBRC. Our simulations suggest that it is preferable to use: (i) efficient NBRC for estimating and testing interaction effects of normally distributed covariates and (ii) efficient LRC for estimating and testing interactions for markedly non-normal covariates. © The Author(s) 2013.

Allelic-based gene-gene interaction associated with quantitative traits.

PubMed

Jung, Jeesun; Sun, Bin; Kwon, Deukwoo; Koller, Daniel L; Foroud, Tatiana M

2009-05-01

Recent studies have shown that quantitative phenotypes may be influenced not only by multiple single nucleotide polymorphisms (SNPs) within a gene but also by the interaction between SNPs at unlinked genes. We propose a new statistical approach that can detect gene-gene interactions at the allelic level which contribute to the phenotypic variation in a quantitative trait. By testing for the association of allelic combinations at multiple unlinked loci with a quantitative trait, we can detect the SNP allelic interaction whether or not it can be detected as a main effect. Our proposed method assigns a score to unrelated subjects according to their allelic combination inferred from observed genotypes at two or more unlinked SNPs, and then tests for the association of the allelic score with a quantitative trait. To investigate the statistical properties of the proposed method, we performed a simulation study to estimate type I error rates and power and demonstrated that this allelic approach achieves greater power than the more commonly used genotypic approach to test for gene-gene interaction. As an example, the proposed method was applied to data obtained as part of a candidate gene study of sodium retention by the kidney. We found that this method detects an interaction between the calcium-sensing receptor gene (CaSR), the chloride channel gene (CLCNKB) and the Na, K, 2Cl cotransporter gene (CLC12A1) that contributes to variation in diastolic blood pressure.

A Kernel Machine Method for Detecting Effects of Interaction Between Multidimensional Variable Sets: An Imaging Genetics Application

PubMed Central

Ge, Tian; Nichols, Thomas E.; Ghosh, Debashis; Mormino, Elizabeth C.

2015-01-01

Measurements derived from neuroimaging data can serve as markers of disease and/or healthy development, are largely heritable, and have been increasingly utilized as (intermediate) phenotypes in genetic association studies. To date, imaging genetic studies have mostly focused on discovering isolated genetic effects, typically ignoring potential interactions with non-genetic variables such as disease risk factors, environmental exposures, and epigenetic markers. However, identifying significant interaction effects is critical for revealing the true relationship between genetic and phenotypic variables, and shedding light on disease mechanisms. In this paper, we present a general kernel machine based method for detecting effects of interaction between multidimensional variable sets. This method can model the joint and epistatic effect of a collection of single nucleotide polymorphisms (SNPs), accommodate multiple factors that potentially moderate genetic influences, and test for nonlinear interactions between sets of variables in a flexible framework. As a demonstration of application, we applied the method to data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to detect the effects of the interactions between candidate Alzheimer's disease (AD) risk genes and a collection of cardiovascular disease (CVD) risk factors, on hippocampal volume measurements derived from structural brain magnetic resonance imaging (MRI) scans. Our method identified that two genes, CR1 and EPHA1, demonstrate significant interactions with CVD risk factors on hippocampal volume, suggesting that CR1 and EPHA1 may play a role in influencing AD-related neurodegeneration in the presence of CVD risks. PMID:25600633

Numerical solution for the interaction of shock wave with laminar boundary layer in two-dimensional flow on a flat plate. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Landau, U.

1984-01-01

The finite difference computation method was investigated for solving problems of interaction between a shock wave and a laminar boundary layer, through solution of the complete Navier-Stokes equations. This method provided excellent solutions, was simple to perform and needed a relatively short solution time. A large number of runs for various flow conditions could be carried out from which the interaction characteristics and principal factors that influence interaction could be studied.

Quantitative Investigation of Protein-Nucleic Acid Interactions by Biosensor Surface Plasmon Resonance.

PubMed

Wang, Shuo; Poon, Gregory M K; Wilson, W David

2015-01-01

Biosensor-surface plasmon resonance (SPR) technology has emerged as a powerful label-free approach for the study of nucleic acid interactions in real time. The method provides simultaneous equilibrium and kinetic characterization for biomolecular interactions with low sample requirements and without the need for external probes. A detailed and practical guide for protein-DNA interaction analyses using biosensor-SPR methods is presented. Details of SPR technology and basic fundamentals are described with recommendations on the preparation of the SPR instrument, sensor chips and samples, experimental design, quantitative and qualitative data analyses and presentation. A specific example of the interaction of a transcription factor with DNA is provided with results evaluated by both kinetic and steady-state SPR methods.

Interaction among Undergraduate Students: Does Age Matter?

ERIC Educational Resources Information Center

Gregoryk, Kerry; Eighmy, Myron

2009-01-01

This mixed method study described the interaction preferences among generational groups of undergraduate students and how these preferences factor into classroom interaction. The study utilized a two-phase process, starting with qualitative data gathered from focus groups. A published instrument was used to qualify participants for one of four…

Functional Logistic Regression Approach to Detecting Gene by Longitudinal Environmental Exposure Interaction in a Case-Control Study

PubMed Central

Wei, Peng; Tang, Hongwei; Li, Donghui

2014-01-01

Most complex human diseases are likely the consequence of the joint actions of genetic and environmental factors. Identification of gene-environment (GxE) interactions not only contributes to a better understanding of the disease mechanisms, but also improves disease risk prediction and targeted intervention. In contrast to the large number of genetic susceptibility loci discovered by genome-wide association studies, there have been very few successes in identifying GxE interactions which may be partly due to limited statistical power and inaccurately measured exposures. While existing statistical methods only consider interactions between genes and static environmental exposures, many environmental/lifestyle factors, such as air pollution and diet, change over time, and cannot be accurately captured at one measurement time point or by simply categorizing into static exposure categories. There is a dearth of statistical methods for detecting gene by time-varying environmental exposure interactions. Here we propose a powerful functional logistic regression (FLR) approach to model the time-varying effect of longitudinal environmental exposure and its interaction with genetic factors on disease risk. Capitalizing on the powerful functional data analysis framework, our proposed FLR model is capable of accommodating longitudinal exposures measured at irregular time points and contaminated by measurement errors, commonly encountered in observational studies. We use extensive simulations to show that the proposed method can control the Type I error and is more powerful than alternative ad hoc methods. We demonstrate the utility of this new method using data from a case-control study of pancreatic cancer to identify the windows of vulnerability of lifetime body mass index on the risk of pancreatic cancer as well as genes which may modify this association. PMID:25219575

Functional logistic regression approach to detecting gene by longitudinal environmental exposure interaction in a case-control study.

PubMed

Wei, Peng; Tang, Hongwei; Li, Donghui

2014-11-01

Most complex human diseases are likely the consequence of the joint actions of genetic and environmental factors. Identification of gene-environment (G × E) interactions not only contributes to a better understanding of the disease mechanisms, but also improves disease risk prediction and targeted intervention. In contrast to the large number of genetic susceptibility loci discovered by genome-wide association studies, there have been very few successes in identifying G × E interactions, which may be partly due to limited statistical power and inaccurately measured exposures. Although existing statistical methods only consider interactions between genes and static environmental exposures, many environmental/lifestyle factors, such as air pollution and diet, change over time, and cannot be accurately captured at one measurement time point or by simply categorizing into static exposure categories. There is a dearth of statistical methods for detecting gene by time-varying environmental exposure interactions. Here, we propose a powerful functional logistic regression (FLR) approach to model the time-varying effect of longitudinal environmental exposure and its interaction with genetic factors on disease risk. Capitalizing on the powerful functional data analysis framework, our proposed FLR model is capable of accommodating longitudinal exposures measured at irregular time points and contaminated by measurement errors, commonly encountered in observational studies. We use extensive simulations to show that the proposed method can control the Type I error and is more powerful than alternative ad hoc methods. We demonstrate the utility of this new method using data from a case-control study of pancreatic cancer to identify the windows of vulnerability of lifetime body mass index on the risk of pancreatic cancer as well as genes that may modify this association. © 2014 Wiley Periodicals, Inc.

The pragmatics of therapeutic interaction: an empirical study.

PubMed

Lepper, Georgia

2009-10-01

The research reported in this article aims to demonstrate a method for the systematic study of the therapist/patient interaction in psychoanalytic psychotherapy, drawing upon the tradition and methods of 'pragmatics'--the study of language in interaction. A brief introduction to the discipline of pragmatics demonstrates its relevance to the contemporary focus of clinical theory on the here-and-now dynamics of the relationship between analyst and patient. This is followed by a detailed study of five segments from the transcript of a therapeutic dialogue, drawn from a brief psychoanalytic psychotherapy, in which therapist and patient negotiate the meaning of the patient's symptom: Is it psychosomatic? The research seeks to show how the therapeutic process can be observed and studied as an interactional achievement, grounded in general and well-studied procedures through which meaning is intersubjectively developed and shared. Implications of the analysis for clinical theory and practice, and further research, are discussed.

A Combinatorial Approach to Detecting Gene-Gene and Gene-Environment Interactions in Family Studies

PubMed Central

Lou, Xiang-Yang; Chen, Guo-Bo; Yan, Lei; Ma, Jennie Z.; Mangold, Jamie E.; Zhu, Jun; Elston, Robert C.; Li, Ming D.

2008-01-01

Widespread multifactor interactions present a significant challenge in determining risk factors of complex diseases. Several combinatorial approaches, such as the multifactor dimensionality reduction (MDR) method, have emerged as a promising tool for better detecting gene-gene (G × G) and gene-environment (G × E) interactions. We recently developed a general combinatorial approach, namely the generalized multifactor dimensionality reduction (GMDR) method, which can entertain both qualitative and quantitative phenotypes and allows for both discrete and continuous covariates to detect G × G and G × E interactions in a sample of unrelated individuals. In this article, we report the development of an algorithm that can be used to study G × G and G × E interactions for family-based designs, called pedigree-based GMDR (PGMDR). Compared to the available method, our proposed method has several major improvements, including allowing for covariate adjustments and being applicable to arbitrary phenotypes, arbitrary pedigree structures, and arbitrary patterns of missing marker genotypes. Our Monte Carlo simulations provide evidence that the PGMDR method is superior in performance to identify epistatic loci compared to the MDR-pedigree disequilibrium test (PDT). Finally, we applied our proposed approach to a genetic data set on tobacco dependence and found a significant interaction between two taste receptor genes (i.e., TAS2R16 and TAS2R38) in affecting nicotine dependence. PMID:18834969

Evaluation of the interaction between hydroxyapatite and bisphosphonate by nonlinear capillary electrochromatography.

PubMed

Kong, Deying; Chen, Zilin

2017-05-01

Bisphosphonates are a class of chemical compounds used to treat diseases caused by increased bone resorption. Zoledronate is a third-generation bisphosphonate drug. Hydroxyapatite is main mineral constituent of bones, which can be bound by bisphosphonates in vivo. In this work, we report a method of nonlinear capillary electrochromatography for study on the interaction between hydroxyapatite and bisphosphonate. Hydroxyapatite was modified on the inner wall of capillary by a biomimetic-mineralization method. Then nonlinear chromatography was used to fit and analyze the interaction between zoledronate and hydroxyapatite. The association rate constants of zoledronate in hydroxyapatite-modified capillary and bare capillary are 642.3 and 195/M/min, respectively. This indicates that there is strong binding interactions and affinity between zoledronate and hydroxyapatite. Besides, the interaction between zoledronate and hydroxyapatite was confirmed further by ultraviolet spectroscopy. The method of nonlinear capillary electrochromatography provides a fast and effect approach for studying of bone metabolism disease by evaluation of interaction between hydroxyapatite and bisphosphonates. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Interaction entropy for protein-protein binding

NASA Astrophysics Data System (ADS)

Sun, Zhaoxi; Yan, Yu N.; Yang, Maoyou; Zhang, John Z. H.

2017-03-01

Protein-protein interactions are at the heart of signal transduction and are central to the function of protein machine in biology. The highly specific protein-protein binding is quantitatively characterized by the binding free energy whose accurate calculation from the first principle is a grand challenge in computational biology. In this paper, we show how the interaction entropy approach, which was recently proposed for protein-ligand binding free energy calculation, can be applied to computing the entropic contribution to the protein-protein binding free energy. Explicit theoretical derivation of the interaction entropy approach for protein-protein interaction system is given in detail from the basic definition. Extensive computational studies for a dozen realistic protein-protein interaction systems are carried out using the present approach and comparisons of the results for these protein-protein systems with those from the standard normal mode method are presented. Analysis of the present method for application in protein-protein binding as well as the limitation of the method in numerical computation is discussed. Our study and analysis of the results provided useful information for extracting correct entropic contribution in protein-protein binding from molecular dynamics simulations.

Identification of genes related to proliferative diabetic retinopathy through RWR algorithm based on protein-protein interaction network.

PubMed

Zhang, Jian; Suo, Yan; Liu, Min; Xu, Xun

2018-06-01

Proliferative diabetic retinopathy (PDR) is one of the most common complications of diabetes and can lead to blindness. Proteomic studies have provided insight into the pathogenesis of PDR and a series of PDR-related genes has been identified but are far from fully characterized because the experimental methods are expensive and time consuming. In our previous study, we successfully identified 35 candidate PDR-related genes through the shortest-path algorithm. In the current study, we developed a computational method using the random walk with restart (RWR) algorithm and the protein-protein interaction (PPI) network to identify potential PDR-related genes. After some possible genes were obtained by the RWR algorithm, a three-stage filtration strategy, which includes the permutation test, interaction test and enrichment test, was applied to exclude potential false positives caused by the structure of PPI network, the poor interaction strength, and the limited similarity on gene ontology (GO) terms and biological pathways. As a result, 36 candidate genes were discovered by the method which was different from the 35 genes reported in our previous study. A literature review showed that 21 of these 36 genes are supported by previous experiments. These findings suggest the robustness and complementary effects of both our efforts using different computational methods, thus providing an alternative method to study PDR pathogenesis. Copyright © 2017 Elsevier B.V. All rights reserved.

Interaction Entropy: A New Paradigm for Highly Efficient and Reliable Computation of Protein-Ligand Binding Free Energy.

PubMed

Duan, Lili; Liu, Xiao; Zhang, John Z H

2016-05-04

Efficient and reliable calculation of protein-ligand binding free energy is a grand challenge in computational biology and is of critical importance in drug design and many other molecular recognition problems. The main challenge lies in the calculation of entropic contribution to protein-ligand binding or interaction systems. In this report, we present a new interaction entropy method which is theoretically rigorous, computationally efficient, and numerically reliable for calculating entropic contribution to free energy in protein-ligand binding and other interaction processes. Drastically different from the widely employed but extremely expensive normal mode method for calculating entropy change in protein-ligand binding, the new method calculates the entropic component (interaction entropy or -TΔS) of the binding free energy directly from molecular dynamics simulation without any extra computational cost. Extensive study of over a dozen randomly selected protein-ligand binding systems demonstrated that this interaction entropy method is both computationally efficient and numerically reliable and is vastly superior to the standard normal mode approach. This interaction entropy paradigm introduces a novel and intuitive conceptual understanding of the entropic effect in protein-ligand binding and other general interaction systems as well as a practical method for highly efficient calculation of this effect.

Numerical simulation of stress amplification induced by crack interaction in human femur bone

NASA Astrophysics Data System (ADS)

Alia, Noor; Daud, Ruslizam; Ramli, Mohammad Fadzli; Azman, Wan Zuki; Faizal, Ahmad; Aisyah, Siti

2015-05-01

This research is about numerical simulation using a computational method which study on stress amplification induced by crack interaction in human femur bone. Cracks in human femur bone usually occur because of large load or stress applied on it. Usually, the fracture takes longer time to heal itself. At present, the crack interaction is still not well understood due to bone complexity. Thus, brittle fracture behavior of bone may be underestimated and inaccurate. This study aims to investigate the geometrical effect of double co-planar edge cracks on stress intensity factor (K) in femur bone. This research focuses to analyze the amplification effect on the fracture behavior of double co-planar edge cracks, where numerical model is developed using computational method. The concept of fracture mechanics and finite element method (FEM) are used to solve the interacting cracks problems using linear elastic fracture mechanics (LEFM) theory. As a result, this study has shown the identification of the crack interaction limit (CIL) and crack unification limit (CUL) exist in the human femur bone model developed. In future research, several improvements will be made such as varying the load, applying thickness on the model and also use different theory or method in calculating the stress intensity factor (K).

Predicting Human Protein Subcellular Locations by the Ensemble of Multiple Predictors via Protein-Protein Interaction Network with Edge Clustering Coefficients

PubMed Central

Du, Pufeng; Wang, Lusheng

2014-01-01

One of the fundamental tasks in biology is to identify the functions of all proteins to reveal the primary machinery of a cell. Knowledge of the subcellular locations of proteins will provide key hints to reveal their functions and to understand the intricate pathways that regulate biological processes at the cellular level. Protein subcellular location prediction has been extensively studied in the past two decades. A lot of methods have been developed based on protein primary sequences as well as protein-protein interaction network. In this paper, we propose to use the protein-protein interaction network as an infrastructure to integrate existing sequence based predictors. When predicting the subcellular locations of a given protein, not only the protein itself, but also all its interacting partners were considered. Unlike existing methods, our method requires neither the comprehensive knowledge of the protein-protein interaction network nor the experimentally annotated subcellular locations of most proteins in the protein-protein interaction network. Besides, our method can be used as a framework to integrate multiple predictors. Our method achieved 56% on human proteome in absolute-true rate, which is higher than the state-of-the-art methods. PMID:24466278

Drug-Target Interaction Prediction through Label Propagation with Linear Neighborhood Information.

PubMed

Zhang, Wen; Chen, Yanlin; Li, Dingfang

2017-11-25

Interactions between drugs and target proteins provide important information for the drug discovery. Currently, experiments identified only a small number of drug-target interactions. Therefore, the development of computational methods for drug-target interaction prediction is an urgent task of theoretical interest and practical significance. In this paper, we propose a label propagation method with linear neighborhood information (LPLNI) for predicting unobserved drug-target interactions. Firstly, we calculate drug-drug linear neighborhood similarity in the feature spaces, by considering how to reconstruct data points from neighbors. Then, we take similarities as the manifold of drugs, and assume the manifold unchanged in the interaction space. At last, we predict unobserved interactions between known drugs and targets by using drug-drug linear neighborhood similarity and known drug-target interactions. The experiments show that LPLNI can utilize only known drug-target interactions to make high-accuracy predictions on four benchmark datasets. Furthermore, we consider incorporating chemical structures into LPLNI models. Experimental results demonstrate that the model with integrated information (LPLNI-II) can produce improved performances, better than other state-of-the-art methods. The known drug-target interactions are an important information source for computational predictions. The usefulness of the proposed method is demonstrated by cross validation and the case study.

Using mixed methods research in medical education: basic guidelines for researchers.

PubMed

Schifferdecker, Karen E; Reed, Virginia A

2009-07-01

Mixed methods research involves the collection, analysis and integration of both qualitative and quantitative data in a single study. The benefits of a mixed methods approach are particularly evident when studying new questions or complex initiatives and interactions, which is often the case in medical education research. Basic guidelines for when to use mixed methods research and how to design a mixed methods study in medical education research are not readily available. The purpose of this paper is to remedy that situation by providing an overview of mixed methods research, research design models relevant for medical education research, examples of each research design model in medical education research, and basic guidelines for medical education researchers interested in mixed methods research. Mixed methods may prove superior in increasing the integrity and applicability of findings when studying new or complex initiatives and interactions in medical education research. They deserve an increased presence and recognition in medical education research.

Detection of time delays and directional interactions based on time series from complex dynamical systems

NASA Astrophysics Data System (ADS)

Ma, Huanfei; Leng, Siyang; Tao, Chenyang; Ying, Xiong; Kurths, Jürgen; Lai, Ying-Cheng; Lin, Wei

2017-07-01

Data-based and model-free accurate identification of intrinsic time delays and directional interactions is an extremely challenging problem in complex dynamical systems and their networks reconstruction. A model-free method with new scores is proposed to be generally capable of detecting single, multiple, and distributed time delays. The method is applicable not only to mutually interacting dynamical variables but also to self-interacting variables in a time-delayed feedback loop. Validation of the method is carried out using physical, biological, and ecological models and real data sets. Especially, applying the method to air pollution data and hospital admission records of cardiovascular diseases in Hong Kong reveals the major air pollutants as a cause of the diseases and, more importantly, it uncovers a hidden time delay (about 30-40 days) in the causal influence that previous studies failed to detect. The proposed method is expected to be universally applicable to ascertaining and quantifying subtle interactions (e.g., causation) in complex systems arising from a broad range of disciplines.

[The effectiveness of psychoanalytic-interactional therapy in borderline personality disorder: a study of clinical data].

PubMed

Leichsenring, Falk; Masuhr, Oliver; Jaeger, Ulrich; Dally, Andreas; Streeck, Ulrich

2007-01-01

Different methods are available for the psychotherapeutic treatment of patients with severe structural mental disorders. Psychoanalytic-interactional therapy is among those methods which have been clinically proven to be effective for many years. Psychoanalytic-interactional therapy was derived from analytic psychotherapy specifically to allow for the treatment of severely disturbed patients, e.g. patients with borderline personality disorders, prepsychotic disorders, addictions and perversions. In a naturalistic study, the effectiveness of psychoanalytic-interactional therapy was tested in a sample of patients with borderline personality disorders (N = 132). The patients were treated at the Clinic Tiefenbrunn near Goettingen, Germany. Standardized, reliable and valid diagnostic instruments were used to study the treatment effects. Psychoanalytic-interactional therapy was found to significantly improve target symptoms, general symptoms, interpersonal problems and life satisfaction. The results are discussed with regard to the treatment of severely disturbed patients.

Development of the brain's functional network architecture.

PubMed

Vogel, Alecia C; Power, Jonathan D; Petersen, Steven E; Schlaggar, Bradley L

2010-12-01

A full understanding of the development of the brain's functional network architecture requires not only an understanding of developmental changes in neural processing in individual brain regions but also an understanding of changes in inter-regional interactions. Resting state functional connectivity MRI (rs-fcMRI) is increasingly being used to study functional interactions between brain regions in both adults and children. We briefly review methods used to study functional interactions and networks with rs-fcMRI and how these methods have been used to define developmental changes in network functional connectivity. The developmental rs-fcMRI studies to date have found two general properties. First, regional interactions change from being predominately anatomically local in children to interactions spanning longer cortical distances in young adults. Second, this developmental change in functional connectivity occurs, in general, via mechanisms of segregation of local regions and integration of distant regions into disparate subnetworks.

Development of the Brain's Functional Network Architecture

PubMed Central

Power, Jonathan D.; Petersen, Steven E.; Schlaggar, Bradley L.

2013-01-01

A full understanding of the development of the brain's functional network architecture requires not only an understanding of developmental changes in neural processing in individual brain regions but also an understanding of changes in inter-regional interactions. Resting state functional connectivity MRI (rs-fcMRI) is increasingly being used to study functional interactions between brain regions in both adults and children. We briefly review methods used to study functional interactions and networks with rs-fcMRI and how these methods have been used to define developmental changes in network functional connectivity. The developmental rs-fcMRI studies to date have found two general properties. First, regional interactions change from being predominately anatomically local in children to interactions spanning longer cortical distances in young adults. Second, this developmental change in functional connectivity occurs, in general, via mechanisms of segregation of local regions and integration of distant regions into disparate subnetworks. PMID:20976563

Active subnetwork recovery with a mechanism-dependent scoring function; with application to angiogenesis and organogenesis studies

PubMed Central

2013-01-01

Background The learning active subnetworks problem involves finding subnetworks of a bio-molecular network that are active in a particular condition. Many approaches integrate observation data (e.g., gene expression) with the network topology to find candidate subnetworks. Increasingly, pathway databases contain additional annotation information that can be mined to improve prediction accuracy, e.g., interaction mechanism (e.g., transcription, microRNA, cleavage) annotations. We introduce a mechanism-based approach to active subnetwork recovery which exploits such annotations. We suggest that neighboring interactions in a network tend to be co-activated in a way that depends on the “correlation” of their mechanism annotations. e.g., neighboring phosphorylation and de-phosphorylation interactions may be more likely to be co-activated than neighboring phosphorylation and covalent bonding interactions. Results Our method iteratively learns the mechanism correlations and finds the most likely active subnetwork. We use a probabilistic graphical model with a Markov Random Field component which creates dependencies between the states (active or non-active) of neighboring interactions, that incorporates a mechanism-based component to the function. We apply a heuristic-based EM-based algorithm suitable for the problem. We validated our method’s performance using simulated data in networks downloaded from GeneGO against the same approach without the mechanism-based component, and two other existing methods. We validated our methods performance in correctly recovering (1) the true interaction states, and (2) global network properties of the original network against these other methods. We applied our method to networks generated from time-course gene expression studies in angiogenesis and lung organogenesis and validated the findings from a biological perspective against current literature. Conclusions The advantage of our mechanism-based approach is best seen in networks composed of connected regions with a large number of interactions annotated with a subset of mechanisms, e.g., a regulatory region of transcription interactions, or a cleavage cascade region. When applied to real datasets, our method recovered novel and biologically meaningful putative interactions, e.g., interactions from an integrin signaling pathway using the angiogenesis dataset, and a group of regulatory microRNA interactions in an organogenesis network. PMID:23432934

Quantitative analysis of small molecule-nucleic acid interactions with a biosensor surface and surface plasmon resonance detection.

PubMed

Liu, Yang; Wilson, W David

2010-01-01

Surface plasmon resonance (SPR) technology with biosensor surfaces has become a widely-used tool for the study of nucleic acid interactions without any labeling requirements. The method provides simultaneous kinetic and equilibrium characterization of the interactions of biomolecules as well as small molecule-biopolymer binding. SPR monitors molecular interactions in real time and provides significant advantages over optical or calorimetic methods for systems with strong binding coupled to small spectroscopic signals and/or reaction heats. A detailed and practical guide for nucleic acid interaction analysis using SPR-biosensor methods is presented. Details of the SPR technology and basic fundamentals are described with recommendations on the preparation of the SPR instrument, sensor chips, and samples, as well as extensive information on experimental design, quantitative and qualitative data analysis and presentation. A specific example of the interaction of a minor-groove-binding agent with DNA is evaluated by both kinetic and steady-state SPR methods to illustrate the technique. Since the molecules that bind cooperatively to specific DNA sequences are attractive for many applications, a cooperative small molecule-DNA interaction is also presented.

Noncovalent π⋅⋅⋅π interaction between graphene and aromatic molecule: Structure, energy, and nature

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

Wang, Weizhou, E-mail: wzw@lynu.edu.cn, E-mail: ybw@gzu.edu.cn; Zhang, Yu; Wang, Yi-Bo, E-mail: wzw@lynu.edu.cn, E-mail: ybw@gzu.edu.cn

2014-03-07

Noncovalent π⋅⋅⋅π interactions between graphene and aromatic molecules have been studied by using density functional theory with empirical dispersion correction (ωB97X-D) combined with zeroth-order symmetry adapted perturbation theory (SAPT0). Excellent agreement of the interaction energies computed by means of ωB97X-D and spin component scaled (SCS) SAPT0 methods, respectively, shows great promise for the two methods in the study of the adsorption of aromatic molecules on graphene. The other important finding in this study is that, according to SCS-SAPT0 analyses, π⋅⋅⋅π interactions between graphene and aromatic molecules are largely dependent on both dispersion and electrostatic type interactions. It is also noticedmore » that π⋅⋅⋅π interactions become stronger and more dispersive (less electrostatic) upon substitution of the very electronegative fluorine atoms onto the aromatic molecules.« less

An Immersed Boundary Method for Solving the Compressible Navier-Stokes Equations with Fluid Structure Interaction

NASA Technical Reports Server (NTRS)

Brehm, Christoph; Barad, Michael F.; Kiris, Cetin C.

2016-01-01

An immersed boundary method for the compressible Navier-Stokes equation and the additional infrastructure that is needed to solve moving boundary problems and fully coupled fluid-structure interaction is described. All the methods described in this paper were implemented in NASA's LAVA solver framework. The underlying immersed boundary method is based on the locally stabilized immersed boundary method that was previously introduced by the authors. In the present paper this method is extended to account for all aspects that are involved for fluid structure interaction simulations, such as fast geometry queries and stencil computations, the treatment of freshly cleared cells, and the coupling of the computational fluid dynamics solver with a linear structural finite element method. The current approach is validated for moving boundary problems with prescribed body motion and fully coupled fluid structure interaction problems in 2D and 3D. As part of the validation procedure, results from the second AIAA aeroelastic prediction workshop are also presented. The current paper is regarded as a proof of concept study, while more advanced methods for fluid structure interaction are currently being investigated, such as geometric and material nonlinearities, and advanced coupling approaches.

Genome-wide Mapping of Cellular Protein–RNA Interactions Enabled by Chemical Crosslinking

PubMed Central

Li, Xiaoyu; Song, Jinghui; Yi, Chengqi

2014-01-01

RNA–protein interactions influence many biological processes. Identifying the binding sites of RNA-binding proteins (RBPs) remains one of the most fundamental and important challenges to the studies of such interactions. Capturing RNA and RBPs via chemical crosslinking allows stringent purification procedures that significantly remove the non-specific RNA and protein interactions. Two major types of chemical crosslinking strategies have been developed to date, i.e., UV-enabled crosslinking and enzymatic mechanism-based covalent capture. In this review, we compare such strategies and their current applications, with an emphasis on the technologies themselves rather than the biology that has been revealed. We hope such methods could benefit broader audience and also urge for the development of new methods to study RNA−RBP interactions. PMID:24747191

Summarizing techniques that combine three non-parametric scores to detect disease-associated 2-way SNP-SNP interactions.

PubMed

Sengupta Chattopadhyay, Amrita; Hsiao, Ching-Lin; Chang, Chien Ching; Lian, Ie-Bin; Fann, Cathy S J

2014-01-01

Identifying susceptibility genes that influence complex diseases is extremely difficult because loci often influence the disease state through genetic interactions. Numerous approaches to detect disease-associated SNP-SNP interactions have been developed, but none consistently generates high-quality results under different disease scenarios. Using summarizing techniques to combine a number of existing methods may provide a solution to this problem. Here we used three popular non-parametric methods-Gini, absolute probability difference (APD), and entropy-to develop two novel summary scores, namely principle component score (PCS) and Z-sum score (ZSS), with which to predict disease-associated genetic interactions. We used a simulation study to compare performance of the non-parametric scores, the summary scores, the scaled-sum score (SSS; used in polymorphism interaction analysis (PIA)), and the multifactor dimensionality reduction (MDR). The non-parametric methods achieved high power, but no non-parametric method outperformed all others under a variety of epistatic scenarios. PCS and ZSS, however, outperformed MDR. PCS, ZSS and SSS displayed controlled type-I-errors (<0.05) compared to GS, APDS, ES (>0.05). A real data study using the genetic-analysis-workshop 16 (GAW 16) rheumatoid arthritis dataset identified a number of interesting SNP-SNP interactions. © 2013 Elsevier B.V. All rights reserved.

Approach-Method Interaction: The Role of Teaching Method on the Effect of Context-Based Approach in Physics Instruction

ERIC Educational Resources Information Center

Pesman, Haki; Ozdemir, Omer Faruk

2012-01-01

The purpose of this study is to explore not only the effect of context-based physics instruction on students' achievement and motivation in physics, but also how the use of different teaching methods influences it (interaction effect). Therefore, two two-level-independent variables were defined, teaching approach (contextual and non-contextual…

Lattice quantum chromodynamical approach to nuclear physics

NASA Astrophysics Data System (ADS)

Aoki, Sinya; Doi, Takumi; Hatsuda, Tetsuo; Ikeda, Yoichi; Inoue, Takashi; Ishii, Noriyoshi; Murano, Keiko; Nemura, Hidekatsu; Sasaki, Kenji; HAL QCD Collaboration

2012-09-01

We review recent progress in the HAL QCD method, which was recently proposed to investigate hadron interactions in lattice quantum chromodynamics (QCD). The strategy to extract the energy-independent non-local potential in lattice QCD is explained in detail. The method is applied to study nucleon-nucleon, nucleon-hyperon, hyperon-hyperon, and meson-baryon interactions. Several extensions of the method are also discussed.

Suppression of stochastic pulsation in laser-plasma interaction by smoothing methods

NASA Astrophysics Data System (ADS)

Hora, Heinrich; Aydin, Meral

1992-04-01

The control of the very complex behavior of a plasma with laser interaction by smoothing with induced spatial incoherence or other methods was related to improving the lateral uniformity of the irradiation. While this is important, it is shown from numerical hydrodynamic studies that the very strong temporal pulsation (stuttering) will mostly be suppressed by these smoothing methods too.

Detection of Protein Complexes Based on Penalized Matrix Decomposition in a Sparse Protein⁻Protein Interaction Network.

PubMed

Cao, Buwen; Deng, Shuguang; Qin, Hua; Ding, Pingjian; Chen, Shaopeng; Li, Guanghui

2018-06-15

High-throughput technology has generated large-scale protein interaction data, which is crucial in our understanding of biological organisms. Many complex identification algorithms have been developed to determine protein complexes. However, these methods are only suitable for dense protein interaction networks, because their capabilities decrease rapidly when applied to sparse protein⁻protein interaction (PPI) networks. In this study, based on penalized matrix decomposition ( PMD ), a novel method of penalized matrix decomposition for the identification of protein complexes (i.e., PMD pc ) was developed to detect protein complexes in the human protein interaction network. This method mainly consists of three steps. First, the adjacent matrix of the protein interaction network is normalized. Second, the normalized matrix is decomposed into three factor matrices. The PMD pc method can detect protein complexes in sparse PPI networks by imposing appropriate constraints on factor matrices. Finally, the results of our method are compared with those of other methods in human PPI network. Experimental results show that our method can not only outperform classical algorithms, such as CFinder, ClusterONE, RRW, HC-PIN, and PCE-FR, but can also achieve an ideal overall performance in terms of a composite score consisting of F-measure, accuracy (ACC), and the maximum matching ratio (MMR).

Genome-wide gene–gene interaction analysis for next-generation sequencing

PubMed Central

Zhao, Jinying; Zhu, Yun; Xiong, Momiao

2016-01-01

The critical barrier in interaction analysis for next-generation sequencing (NGS) data is that the traditional pairwise interaction analysis that is suitable for common variants is difficult to apply to rare variants because of their prohibitive computational time, large number of tests and low power. The great challenges for successful detection of interactions with NGS data are (1) the demands in the paradigm of changes in interaction analysis; (2) severe multiple testing; and (3) heavy computations. To meet these challenges, we shift the paradigm of interaction analysis between two SNPs to interaction analysis between two genomic regions. In other words, we take a gene as a unit of analysis and use functional data analysis techniques as dimensional reduction tools to develop a novel statistic to collectively test interaction between all possible pairs of SNPs within two genome regions. By intensive simulations, we demonstrate that the functional logistic regression for interaction analysis has the correct type 1 error rates and higher power to detect interaction than the currently used methods. The proposed method was applied to a coronary artery disease dataset from the Wellcome Trust Case Control Consortium (WTCCC) study and the Framingham Heart Study (FHS) dataset, and the early-onset myocardial infarction (EOMI) exome sequence datasets with European origin from the NHLBI's Exome Sequencing Project. We discovered that 6 of 27 pairs of significantly interacted genes in the FHS were replicated in the independent WTCCC study and 24 pairs of significantly interacted genes after applying Bonferroni correction in the EOMI study. PMID:26173972

Evaluation Criteria for Interactive E-Books for Open and Distance Learning

ERIC Educational Resources Information Center

Bozkurt, Aras; Bozkaya, Mujgan

2015-01-01

The aim of this mixed method study is to identify evaluation criteria for interactive e-books. To find answers for the research questions of the study, both quantitative and qualitative data were collected through a four-round Delphi study with a panel consisting of 30 experts. After that, a total of 20 interactive e-books were examined with…

Contact interaction between a layered foundation and a system of annular punches with complex base shapes

NASA Astrophysics Data System (ADS)

Kazakov, K. E.; Kurdina, S. P.

2018-04-01

We study the contact interaction between a system of rigid annular punches and a viscoelastic two-layer foundation. The upper layer is thin compared with the punch width. We study the case where the punch shapes are described by a rapidly varying functions. We use special methods for constructing the solutions, because the standard methods are inefficient.

Pharmacokinetic and pharmacodynamic drug interactions of carbamazepine and glibenclamide in healthy albino Wistar rats

PubMed Central

Prashanth, S.; Kumar, A. Anil; Madhu, B.; Rama, N.; Sagar, J. Vidya

2011-01-01

Aims: To find out the pharmacokinetic and pharmacodynamic drug interaction of carbamazepine, a protype drug used to treat painful diabetic neuropathy with glibenclamide in healthy albino Wistar rats following single and multiple dosage treatment. Materials and Methods: Therapeutic doses (TD) of glibenclamide and TD of carbamazepine were administered to the animals. The blood glucose levels were estimated by GOD/POD method and the plasma glibenclamide concentrations were estimated by a sensitive RP HPLC method to calculate pharmacokinetic parameters. Results: In single dose study the percentage reduction of blood glucose levels and glibenclamide concentrations of rats treated with both carbamazepine and glibenclamide were significantly increased when compared with glibenclamide alone treated rats and the mechanism behind this interaction may be due to inhibition of P-glycoprotein mediated transport of glibenclamide by carbamazepine, but in multiple dose study the percentage reduction of blood glucose levels and glibenclamide concentrations were reduced and it may be due to inhibition of P-glycoprotein mediated transport and induction of CYP2C9, the enzyme through which glibenclamide is metabolised. Conclusions: In the present study there is a pharmacokinetic and pharmacodynamic interaction between carbamazepine and glibenclamide was observed. The possible interaction involves both P-gp and CYP enzymes. To investigate this type of interactions pre-clinically are helpful to avoid drug-drug interactions in clinical situation. PMID:21701639

FIND: difFerential chromatin INteractions Detection using a spatial Poisson process

PubMed Central

Chen, Yang; Zhang, Michael Q.

2018-01-01

Polymer-based simulations and experimental studies indicate the existence of a spatial dependency between the adjacent DNA fibers involved in the formation of chromatin loops. However, the existing strategies for detecting differential chromatin interactions assume that the interacting segments are spatially independent from the other segments nearby. To resolve this issue, we developed a new computational method, FIND, which considers the local spatial dependency between interacting loci. FIND uses a spatial Poisson process to detect differential chromatin interactions that show a significant difference in their interaction frequency and the interaction frequency of their neighbors. Simulation and biological data analysis show that FIND outperforms the widely used count-based methods and has a better signal-to-noise ratio. PMID:29440282

CO oxidation reaction on Pt(111) studied by the dynamic Monte Carlo method including lateral interactions of adsorbates.

PubMed

Nagasaka, Masanari; Kondoh, Hiroshi; Nakai, Ikuyo; Ohta, Toshiaki

2007-01-28

The dynamics of adsorbate structures during CO oxidation on Pt(111) surfaces and its effects on the reaction were studied by the dynamic Monte Carlo method including lateral interactions of adsorbates. The lateral interaction energies between adsorbed species were calculated by the density functional theory method. Dynamic Monte Carlo simulations were performed for the oxidation reaction over a mesoscopic scale, where the experimentally determined activation energies of elementary paths were altered by the calculated lateral interaction energies. The simulated results reproduced the characteristics of the microscopic and mesoscopic scale adsorbate structures formed during the reaction, and revealed that the complicated reaction kinetics is comprehensively explained by a single reaction path affected by the surrounding adsorbates. We also propose from the simulations that weakly adsorbed CO molecules at domain boundaries promote the island-periphery specific reaction.

Using a dual safeguard web-based interactive teaching approach in an introductory physics class

NASA Astrophysics Data System (ADS)

Li, Lie-Ming; Li, Bin; Luo, Ying

2015-06-01

We modified the Just-in-Time Teaching approach and developed a dual safeguard web-based interactive (DGWI) teaching system for an introductory physics course. The system consists of four instructional components that improve student learning by including warm-up assignments and online homework. Student and instructor activities involve activities both in the classroom and on a designated web site. An experimental study with control groups evaluated the effectiveness of the DGWI teaching method. The results indicate that the DGWI method is an effective way to improve students' understanding of physics concepts, develop students' problem-solving abilities through instructor-student interactions, and identify students' misconceptions through a safeguard framework based on questions that satisfy teaching requirements and cover all of the course material. The empirical study and a follow-up survey found that the DGWI method increased student-teacher interaction and improved student learning outcomes.

Estimating interaction on an additive scale between continuous determinants in a logistic regression model.

PubMed

Knol, Mirjam J; van der Tweel, Ingeborg; Grobbee, Diederick E; Numans, Mattijs E; Geerlings, Mirjam I

2007-10-01

To determine the presence of interaction in epidemiologic research, typically a product term is added to the regression model. In linear regression, the regression coefficient of the product term reflects interaction as departure from additivity. However, in logistic regression it refers to interaction as departure from multiplicativity. Rothman has argued that interaction estimated as departure from additivity better reflects biologic interaction. So far, literature on estimating interaction on an additive scale using logistic regression only focused on dichotomous determinants. The objective of the present study was to provide the methods to estimate interaction between continuous determinants and to illustrate these methods with a clinical example. and results From the existing literature we derived the formulas to quantify interaction as departure from additivity between one continuous and one dichotomous determinant and between two continuous determinants using logistic regression. Bootstrapping was used to calculate the corresponding confidence intervals. To illustrate the theory with an empirical example, data from the Utrecht Health Project were used, with age and body mass index as risk factors for elevated diastolic blood pressure. The methods and formulas presented in this article are intended to assist epidemiologists to calculate interaction on an additive scale between two variables on a certain outcome. The proposed methods are included in a spreadsheet which is freely available at: http://www.juliuscenter.nl/additive-interaction.xls.

Automated identification of social interaction criteria in Drosophila melanogaster.

PubMed

Schneider, J; Levine, J D

2014-10-01

The study of social behaviour within groups has relied on fixed definitions of an 'interaction'. Criteria used in these definitions often involve a subjectively defined cut-off value for proximity, orientation and time (e.g. courtship, aggression and social interaction networks) and the same numerical values for these criteria are applied to all of the treatment groups within an experiment. One universal definition of an interaction could misidentify interactions within groups that differ in life histories, study treatments and/or genetic mutations. Here, we present an automated method for determining the values of interaction criteria using a pre-defined rule set rather than pre-defined values. We use this approach and show changing social behaviours in different manipulations of Drosophila melanogaster. We also show that chemosensory cues are an important modality of social spacing and interaction. This method will allow a more robust analysis of the properties of interacting groups, while helping us understand how specific groups regulate their social interaction space. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Construction of Interaction Layer on Socio-Environmental Simulation

NASA Astrophysics Data System (ADS)

Torii, Daisuke; Ishida, Toru

In this study, we propose a method to construct a system based on a legacy socio-environmental simulator which enables to design more realistic interaction models in socio-environmetal simulations. First, to provide a computational model suitable for agent interactions, an interaction layer is constructed and connected from outside of a legacy socio-environmental simulator. Next, to configure the agents interacting ability, connection description for controlling the flow of information in the connection area is provided. As a concrete example, we realized an interaction layer by Q which is a scenario description language and connected it to CORMAS, a socio-envirionmental simulator. Finally, we discuss the capability of our method, using the system, in the Fire-Fighter domain.

A kernel machine method for detecting effects of interaction between multidimensional variable sets: an imaging genetics application.

PubMed

Ge, Tian; Nichols, Thomas E; Ghosh, Debashis; Mormino, Elizabeth C; Smoller, Jordan W; Sabuncu, Mert R

2015-04-01

Measurements derived from neuroimaging data can serve as markers of disease and/or healthy development, are largely heritable, and have been increasingly utilized as (intermediate) phenotypes in genetic association studies. To date, imaging genetic studies have mostly focused on discovering isolated genetic effects, typically ignoring potential interactions with non-genetic variables such as disease risk factors, environmental exposures, and epigenetic markers. However, identifying significant interaction effects is critical for revealing the true relationship between genetic and phenotypic variables, and shedding light on disease mechanisms. In this paper, we present a general kernel machine based method for detecting effects of the interaction between multidimensional variable sets. This method can model the joint and epistatic effect of a collection of single nucleotide polymorphisms (SNPs), accommodate multiple factors that potentially moderate genetic influences, and test for nonlinear interactions between sets of variables in a flexible framework. As a demonstration of application, we applied the method to the data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to detect the effects of the interactions between candidate Alzheimer's disease (AD) risk genes and a collection of cardiovascular disease (CVD) risk factors, on hippocampal volume measurements derived from structural brain magnetic resonance imaging (MRI) scans. Our method identified that two genes, CR1 and EPHA1, demonstrate significant interactions with CVD risk factors on hippocampal volume, suggesting that CR1 and EPHA1 may play a role in influencing AD-related neurodegeneration in the presence of CVD risks. Copyright © 2015 Elsevier Inc. All rights reserved.

Detecting epistasis with the marginal epistasis test in genetic mapping studies of quantitative traits

PubMed Central

Zeng, Ping; Mukherjee, Sayan; Zhou, Xiang

2017-01-01

Epistasis, commonly defined as the interaction between multiple genes, is an important genetic component underlying phenotypic variation. Many statistical methods have been developed to model and identify epistatic interactions between genetic variants. However, because of the large combinatorial search space of interactions, most epistasis mapping methods face enormous computational challenges and often suffer from low statistical power due to multiple test correction. Here, we present a novel, alternative strategy for mapping epistasis: instead of directly identifying individual pairwise or higher-order interactions, we focus on mapping variants that have non-zero marginal epistatic effects—the combined pairwise interaction effects between a given variant and all other variants. By testing marginal epistatic effects, we can identify candidate variants that are involved in epistasis without the need to identify the exact partners with which the variants interact, thus potentially alleviating much of the statistical and computational burden associated with standard epistatic mapping procedures. Our method is based on a variance component model, and relies on a recently developed variance component estimation method for efficient parameter inference and p-value computation. We refer to our method as the “MArginal ePIstasis Test”, or MAPIT. With simulations, we show how MAPIT can be used to estimate and test marginal epistatic effects, produce calibrated test statistics under the null, and facilitate the detection of pairwise epistatic interactions. We further illustrate the benefits of MAPIT in a QTL mapping study by analyzing the gene expression data of over 400 individuals from the GEUVADIS consortium. PMID:28746338

A study on the application of voice interaction in automotive human machine interface experience design

NASA Astrophysics Data System (ADS)

Huang, Zhaohui; Huang, Xiemin

2018-04-01

This paper, firstly, introduces the application trend of the integration of multi-channel interactions in automotive HMI ((Human Machine Interface) from complex information models faced by existing automotive HMI and describes various interaction modes. By comparing voice interaction and touch screen, gestures and other interaction modes, the potential and feasibility of voice interaction in automotive HMI experience design are concluded. Then, the related theories of voice interaction, identification technologies, human beings' cognitive models of voices and voice design methods are further explored. And the research priority of this paper is proposed, i.e. how to design voice interaction to create more humane task-oriented dialogue scenarios to enhance interactive experiences of automotive HMI. The specific scenarios in driving behaviors suitable for the use of voice interaction are studied and classified, and the usability principles and key elements for automotive HMI voice design are proposed according to the scenario features. Then, through the user participatory usability testing experiment, the dialogue processes of voice interaction in automotive HMI are defined. The logics and grammars in voice interaction are classified according to the experimental results, and the mental models in the interaction processes are analyzed. At last, the voice interaction design method to create the humane task-oriented dialogue scenarios in the driving environment is proposed.

Computer simulation and experimental study of the polysaccharide-polysaccharide interaction in the bacteria Azospirillum brasilense Sp245

NASA Astrophysics Data System (ADS)

Arefeva, Oksana A.; Kuznetsov, Pavel E.; Tolmachev, Sergey A.; Kupadze, Machammad S.; Khlebtsov, Boris N.; Rogacheva, Svetlana M.

2003-09-01

We have studied the conformational properties and molecular dynamics of polysaccharides by using molecular modeling methods. Theoretical and experimental results of polysaccharide-polysaccharide interactions are described.

Assessment selection in human-automation interaction studies: The Failure-GAM2E and review of assessment methods for highly automated driving.

PubMed

Grane, Camilla

2018-01-01

Highly automated driving will change driver's behavioural patterns. Traditional methods used for assessing manual driving will only be applicable for the parts of human-automation interaction where the driver intervenes such as in hand-over and take-over situations. Therefore, driver behaviour assessment will need to adapt to the new driving scenarios. This paper aims at simplifying the process of selecting appropriate assessment methods. Thirty-five papers were reviewed to examine potential and relevant methods. The review showed that many studies still relies on traditional driving assessment methods. A new method, the Failure-GAM 2 E model, with purpose to aid assessment selection when planning a study, is proposed and exemplified in the paper. Failure-GAM 2 E includes a systematic step-by-step procedure defining the situation, failures (Failure), goals (G), actions (A), subjective methods (M), objective methods (M) and equipment (E). The use of Failure-GAM 2 E in a study example resulted in a well-reasoned assessment plan, a new way of measuring trust through feet movements and a proposed Optimal Risk Management Model. Failure-GAM 2 E and the Optimal Risk Management Model are believed to support the planning process for research studies in the field of human-automation interaction. Copyright © 2017 Elsevier Ltd. All rights reserved.

Platform construction and extraction mechanism study of magnetic mixed hemimicelles solid-phase extraction

PubMed Central

Xiao, Deli; Zhang, Chan; He, Jia; Zeng, Rong; Chen, Rong; He, Hua

2016-01-01

Simple, accurate and high-throughput pretreatment method would facilitate large-scale studies of trace analysis in complex samples. Magnetic mixed hemimicelles solid-phase extraction has the power to become a key pretreatment method in biological, environmental and clinical research. However, lacking of experimental predictability and unsharpness of extraction mechanism limit the development of this promising method. Herein, this work tries to establish theoretical-based experimental designs for extraction of trace analytes from complex samples using magnetic mixed hemimicelles solid-phase extraction. We selected three categories and six sub-types of compounds for systematic comparative study of extraction mechanism, and comprehensively illustrated the roles of different force (hydrophobic interaction, π-π stacking interactions, hydrogen-bonding interaction, electrostatic interaction) for the first time. What’s more, the application guidelines for supporting materials, surfactants and sample matrix were also summarized. The extraction mechanism and platform established in the study render its future promising for foreseeable and efficient pretreatment under theoretical based experimental design for trace analytes from environmental, biological and clinical samples. PMID:27924944

Applied Graph-Mining Algorithms to Study Biomolecular Interaction Networks

PubMed Central

2014-01-01

Protein-protein interaction (PPI) networks carry vital information on the organization of molecular interactions in cellular systems. The identification of functionally relevant modules in PPI networks is one of the most important applications of biological network analysis. Computational analysis is becoming an indispensable tool to understand large-scale biomolecular interaction networks. Several types of computational methods have been developed and employed for the analysis of PPI networks. Of these computational methods, graph comparison and module detection are the two most commonly used strategies. This review summarizes current literature on graph kernel and graph alignment methods for graph comparison strategies, as well as module detection approaches including seed-and-extend, hierarchical clustering, optimization-based, probabilistic, and frequent subgraph methods. Herein, we provide a comprehensive review of the major algorithms employed under each theme, including our recently published frequent subgraph method, for detecting functional modules commonly shared across multiple cancer PPI networks. PMID:24800226

Numerical simulation of the solitary wave interacting with an elastic structure using MPS-FEM coupled method

NASA Astrophysics Data System (ADS)

Rao, Chengping; Zhang, Youlin; Wan, Decheng

2017-12-01

Fluid-Structure Interaction (FSI) caused by fluid impacting onto a flexible structure commonly occurs in naval architecture and ocean engineering. Research on the problem of wave-structure interaction is important to ensure the safety of offshore structures. This paper presents the Moving Particle Semi-implicit and Finite Element Coupled Method (MPS-FEM) to simulate FSI problems. The Moving Particle Semi-implicit (MPS) method is used to calculate the fluid domain, while the Finite Element Method (FEM) is used to address the structure domain. The scheme for the coupling of MPS and FEM is introduced first. Then, numerical validation and convergent study are performed to verify the accuracy of the solver for solitary wave generation and FSI problems. The interaction between the solitary wave and an elastic structure is investigated by using the MPS-FEM coupled method.

Interactive Land-Use Optimization Using Laguerre Voronoi Diagram with Dynamic Generating Point Allocation

NASA Astrophysics Data System (ADS)

Chaidee, S.; Pakawanwong, P.; Suppakitpaisarn, V.; Teerasawat, P.

2017-09-01

In this work, we devise an efficient method for the land-use optimization problem based on Laguerre Voronoi diagram. Previous Voronoi diagram-based methods are more efficient and more suitable for interactive design than discrete optimization-based method, but, in many cases, their outputs do not satisfy area constraints. To cope with the problem, we propose a force-directed graph drawing algorithm, which automatically allocates generating points of Voronoi diagram to appropriate positions. Then, we construct a Laguerre Voronoi diagram based on these generating points, use linear programs to adjust each cell, and reconstruct the diagram based on the adjustment. We adopt the proposed method to the practical case study of Chiang Mai University's allocated land for a mixed-use complex. For this case study, compared to other Voronoi diagram-based method, we decrease the land allocation error by 62.557 %. Although our computation time is larger than the previous Voronoi-diagram-based method, it is still suitable for interactive design.

Effects of Mastery Learning Strategies on Community College Mathematics Students' Achievement and Success Rate.

ERIC Educational Resources Information Center

Abadir, Laila; And Others

The effects of mastery learning strategies, interactive video mathematics (IVM), individualized instruction (IND), and the lecture method on mathematics achievement of community college students was studied. Interactions among instructional methods, gender, and age were examined; and the grade success rate was determined for each instructional…

Ab initio O(N) elongation-counterpoise method for BSSE-corrected interaction energy analyses in biosystems

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

Orimoto, Yuuichi; Xie, Peng; Liu, Kai

2015-03-14

An Elongation-counterpoise (ELG-CP) method was developed for performing accurate and efficient interaction energy analysis and correcting the basis set superposition error (BSSE) in biosystems. The method was achieved by combining our developed ab initio O(N) elongation method with the conventional counterpoise method proposed for solving the BSSE problem. As a test, the ELG-CP method was applied to the analysis of the DNAs’ inter-strands interaction energies with respect to the alkylation-induced base pair mismatch phenomenon that causes a transition from G⋯C to A⋯T. It was found that the ELG-CP method showed high efficiency (nearly linear-scaling) and high accuracy with a negligiblymore » small energy error in the total energy calculations (in the order of 10{sup −7}–10{sup −8} hartree/atom) as compared with the conventional method during the counterpoise treatment. Furthermore, the magnitude of the BSSE was found to be ca. −290 kcal/mol for the calculation of a DNA model with 21 base pairs. This emphasizes the importance of BSSE correction when a limited size basis set is used to study the DNA models and compare small energy differences between them. In this work, we quantitatively estimated the inter-strands interaction energy for each possible step in the transition process from G⋯C to A⋯T by the ELG-CP method. It was found that the base pair replacement in the process only affects the interaction energy for a limited area around the mismatch position with a few adjacent base pairs. From the interaction energy point of view, our results showed that a base pair sliding mechanism possibly occurs after the alkylation of guanine to gain the maximum possible number of hydrogen bonds between the bases. In addition, the steps leading to the A⋯T replacement accompanied with replications were found to be unfavorable processes corresponding to ca. 10 kcal/mol loss in stabilization energy. The present study indicated that the ELG-CP method is promising for performing effective interaction energy analyses in biosystems.« less

Tetraquark candidate Zc(3900) from coupled-channel scattering - how to extract hadronic interactions? -

NASA Astrophysics Data System (ADS)

Ikeda, Yoichi

2018-03-01

We present recent progress of lattice QCD studies on hadronic interactions which play a crucial role to understand the properties of atomic nuclei and hadron resonances. There are two methods, the plateau method (or the direct method) and the HAL QCD method, to study the hadronic interactions. In the plateau method, the determination of a ground state energy from the temporal correlation functions of multi-hadron systems is a key to reliably extract the physical observables. It turns out that, due to the contamination of excited elastic scattering states nearby, one can easily be misled by a fake plateau into extracting the ground state energy. We introduce a consistency check (sanity check) which can rule out obviously false results obtained from a fake plateau, and find that none of the results obtained at the moment for two-baryon systems in the plateau method pass the test. On the other hand, the HAL QCD method is free from the fake-plateau problem. We investigate the systematic uncertainties of the HAL QCD method, which are found to be well controlled. On the basis of the HAL QCD method, the structure of the tetraquark candidate Zc(3900), which was experimentally reported in e+e- collisions, is studied by the s-wave two-meson coupled-channel scattering. The results show that the Zc(3900) is not a conventional resonance but a threshold cusp. A semi-phenomenological analysis with the coupled-channel interaction to the experimentally observed decay mode is also presented to confirm the conclusion.

Activating articulation skills through theraplay.

PubMed

Kupperman, P; Bligh, S; Goodban, M

1980-11-01

Speech Theraplay, a method of remediation for children with articulation disorders, is described. The approach is based on parent-child interactions that are postulated to activate articulation acquisition. These interactions between parent and child were duplicated and intensified in the clinical setting. Target phonemes were embedded into spontaneous interactive play, both in isolation and in meaningful exchange. The results of a six-week study indicate improvement in the articulation abilities of six children with this method.

Evaluation of interactive teaching for undergraduate medical students using a classroom interactive response system in India.

PubMed

Datta, Rakesh; Datta, Karuna; Venkatesh, M D

2015-07-01

The classical didactic lecture has been the cornerstone of the theoretical undergraduate medical education. Their efficacy however reduces due to reduced interaction and short attention span of the students. It is hypothesized that the interactive response pad obviates some of these drawbacks. The aim of this study was to evaluate the effectiveness of an interactive response system by comparing it with conventional classroom teaching. A prospective comparative longitudinal study was conducted on 192 students who were exposed to either conventional or interactive teaching over 20 classes. Pre-test, Post-test and retentions test (post 8-12 weeks) scores were collated and statistically analysed. An independent observer measured number of student interactions in each class. Pre-test scores from both groups were similar (p = 0.71). There was significant improvement in both post test scores when compared to pre-test scores in either method (p < 0.001). The interactive post-test score was better than conventional post test score (p < 0.001) by 8-10% (95% CI-difference of means - 8.2%-9.24%-10.3%). The interactive retention test score was better than conventional retention test score (p < 0.001) by 15-18% (95% CI-difference of means - 15.0%-16.64%-18.2%). There were 51 participative events in the interactive group vs 25 in the conventional group. The Interactive Response Pad method was efficacious in teaching. Students taught with the interactive method were likely to score 8-10% higher (statistically significant) in the immediate post class time and 15-18% higher (statistically significant) after 8-12 weeks. The number of student-teacher interactions increases when using the interactive response pads.

Epistasis analysis for quantitative traits by functional regression model.

PubMed

Zhang, Futao; Boerwinkle, Eric; Xiong, Momiao

2014-06-01

The critical barrier in interaction analysis for rare variants is that most traditional statistical methods for testing interactions were originally designed for testing the interaction between common variants and are difficult to apply to rare variants because of their prohibitive computational time and poor ability. The great challenges for successful detection of interactions with next-generation sequencing (NGS) data are (1) lack of methods for interaction analysis with rare variants, (2) severe multiple testing, and (3) time-consuming computations. To meet these challenges, we shift the paradigm of interaction analysis between two loci to interaction analysis between two sets of loci or genomic regions and collectively test interactions between all possible pairs of SNPs within two genomic regions. In other words, we take a genome region as a basic unit of interaction analysis and use high-dimensional data reduction and functional data analysis techniques to develop a novel functional regression model to collectively test interactions between all possible pairs of single nucleotide polymorphisms (SNPs) within two genome regions. By intensive simulations, we demonstrate that the functional regression models for interaction analysis of the quantitative trait have the correct type 1 error rates and a much better ability to detect interactions than the current pairwise interaction analysis. The proposed method was applied to exome sequence data from the NHLBI's Exome Sequencing Project (ESP) and CHARGE-S study. We discovered 27 pairs of genes showing significant interactions after applying the Bonferroni correction (P-values < 4.58 × 10(-10)) in the ESP, and 11 were replicated in the CHARGE-S study. © 2014 Zhang et al.; Published by Cold Spring Harbor Laboratory Press.

Interaction of methotrexate with trypsin analyzed by spectroscopic and molecular modeling methods

NASA Astrophysics Data System (ADS)

Wang, Yanqing; Zhang, Hongmei; Cao, Jian; Zhou, Qiuhua

2013-11-01

Trypsin is one of important digestive enzymes that have intimate correlation with human health and illness. In this work, the interaction of trypsin with methotrexate was investigated by spectroscopic and molecular modeling methods. The results revealed that methotrexate could interact with trypsin with about one binding site. Methotrexate molecule could enter into the primary substrate-binding pocket, resulting in inhibition of trypsin activity. Furthermore, the thermodynamic analysis implied that electrostatic force, hydrogen bonding, van der Waals and hydrophobic interactions were the main interactions for stabilizing the trypsin-methotrexate system, which agreed well with the results from the molecular modeling study.

Density functional study of molecular interactions in secondary structures of proteins.

PubMed

Takano, Yu; Kusaka, Ayumi; Nakamura, Haruki

2016-01-01

Proteins play diverse and vital roles in biology, which are dominated by their three-dimensional structures. The three-dimensional structure of a protein determines its functions and chemical properties. Protein secondary structures, including α-helices and β-sheets, are key components of the protein architecture. Molecular interactions, in particular hydrogen bonds, play significant roles in the formation of protein secondary structures. Precise and quantitative estimations of these interactions are required to understand the principles underlying the formation of three-dimensional protein structures. In the present study, we have investigated the molecular interactions in α-helices and β-sheets, using ab initio wave function-based methods, the Hartree-Fock method (HF) and the second-order Møller-Plesset perturbation theory (MP2), density functional theory, and molecular mechanics. The characteristic interactions essential for forming the secondary structures are discussed quantitatively.

ROCS: a Reproducibility Index and Confidence Score for Interaction Proteomics Studies

PubMed Central

2012-01-01

Background Affinity-Purification Mass-Spectrometry (AP-MS) provides a powerful means of identifying protein complexes and interactions. Several important challenges exist in interpreting the results of AP-MS experiments. First, the reproducibility of AP-MS experimental replicates can be low, due both to technical variability and the dynamic nature of protein interactions in the cell. Second, the identification of true protein-protein interactions in AP-MS experiments is subject to inaccuracy due to high false negative and false positive rates. Several experimental approaches can be used to mitigate these drawbacks, including the use of replicated and control experiments and relative quantification to sensitively distinguish true interacting proteins from false ones. Methods To address the issues of reproducibility and accuracy of protein-protein interactions, we introduce a two-step method, called ROCS, which makes use of Indicator Prey Proteins to select reproducible AP-MS experiments, and of Confidence Scores to select specific protein-protein interactions. The Indicator Prey Proteins account for measures of protein identifiability as well as protein reproducibility, effectively allowing removal of outlier experiments that contribute noise and affect downstream inferences. The filtered set of experiments is then used in the Protein-Protein Interaction (PPI) scoring step. Prey protein scoring is done by computing a Confidence Score, which accounts for the probability of occurrence of prey proteins in the bait experiments relative to the control experiment, where the significance cutoff parameter is estimated by simultaneously controlling false positives and false negatives against metrics of false discovery rate and biological coherence respectively. In summary, the ROCS method relies on automatic objective criterions for parameter estimation and error-controlled procedures. Results We illustrate the performance of our method by applying it to five previously published AP-MS experiments, each containing well characterized protein interactions, allowing for systematic benchmarking of ROCS. We show that our method may be used on its own to make accurate identification of specific, biologically relevant protein-protein interactions, or in combination with other AP-MS scoring methods to significantly improve inferences. Conclusions Our method addresses important issues encountered in AP-MS datasets, making ROCS a very promising tool for this purpose, either on its own or in conjunction with other methods. We anticipate that our methodology may be used more generally in proteomics studies and databases, where experimental reproducibility issues arise. The method is implemented in the R language, and is available as an R package called “ROCS”, freely available from the CRAN repository http://cran.r-project.org/. PMID:22682516

Evaluating the utility of two gestural discomfort evaluation methods

PubMed Central

Son, Minseok; Jung, Jaemoon; Park, Woojin

2017-01-01

Evaluating physical discomfort of designed gestures is important for creating safe and usable gesture-based interaction systems; yet, gestural discomfort evaluation has not been extensively studied in HCI, and few evaluation methods seem currently available whose utility has been experimentally confirmed. To address this, this study empirically demonstrated the utility of the subjective rating method after a small number of gesture repetitions (a maximum of four repetitions) in evaluating designed gestures in terms of physical discomfort resulting from prolonged, repetitive gesture use. The subjective rating method has been widely used in previous gesture studies but without empirical evidence on its utility. This study also proposed a gesture discomfort evaluation method based on an existing ergonomics posture evaluation tool (Rapid Upper Limb Assessment) and demonstrated its utility in evaluating designed gestures in terms of physical discomfort resulting from prolonged, repetitive gesture use. Rapid Upper Limb Assessment is an ergonomics postural analysis tool that quantifies the work-related musculoskeletal disorders risks for manual tasks, and has been hypothesized to be capable of correctly determining discomfort resulting from prolonged, repetitive gesture use. The two methods were evaluated through comparisons against a baseline method involving discomfort rating after actual prolonged, repetitive gesture use. Correlation analyses indicated that both methods were in good agreement with the baseline. The methods proposed in this study seem useful for predicting discomfort resulting from prolonged, repetitive gesture use, and are expected to help interaction designers create safe and usable gesture-based interaction systems. PMID:28423016

Thermal transport through a spin-phonon interacting junction: A nonequilibrium Green's function method study

NASA Astrophysics Data System (ADS)

Zhang, Zu-Quan; Lü, Jing-Tao

2017-09-01

Using the nonequilibrium Green's function method, we consider heat transport in an insulating ferromagnetic spin chain model with spin-phonon interaction under an external magnetic field. Employing the Holstein-Primakoff transformation to the spin system, we treat the resulted magnon-phonon interaction within the self-consistent Born approximation. We find the magnon-phonon coupling can change qualitatively the magnon thermal conductance in the high-temperature regime. At a spectral mismatched ferromagnetic-normal insulator interface, we also find thermal rectification and negative differential thermal conductance due to the magnon-phonon interaction. We show that these effects can be effectively tuned by the external applied magnetic field, a convenient advantage absent in anharmonic phonon and electron-phonon systems studied before.

A quasi-static continuum model describing interactions between plasmons and non-absorbing biomolecules

NASA Astrophysics Data System (ADS)

Salary, Mohammad Mahdi; Mosallaei, Hossein

2015-06-01

Interactions between the plasmons of noble metal nanoparticles and non-absorbing biomolecules forms the basis of the plasmonic sensors, which have received much attention. Studying these interactions can help to exploit the full potentials of plasmonic sensors in quantification and analysis of biomolecules. Here, a quasi-static continuum model is adopted for this purpose. We present a boundary-element method for computing the optical response of plasmonic particles to the molecular binding events by solving the Poisson equation. The model represents biomolecules with their molecular surfaces, thus accurately accounting for the influence of exact binding conformations as well as structural differences between different proteins on the response of plasmonic nanoparticles. The linear systems arising in the method are solved iteratively with Krylov generalized minimum residual algorithm, and the acceleration is achieved by applying precorrected-Fast Fourier Transformation technique. We apply the developed method to investigate interactions of biotinylated gold nanoparticles (nanosphere and nanorod) with four different types of biotin-binding proteins. The interactions are studied at both ensemble and single-molecule level. Computational results demonstrate the ability of presented model for analyzing realistic nanoparticle-biomolecule configurations. The method can provide comprehensive study for wide variety of applications, including protein structures, monitoring structural and conformational transitions, and quantification of protein concentrations. In addition, it is suitable for design and optimization of the nano-plasmonic sensors.

The Association between Parental Interaction Style and Children's Joint Engagement in Families with Toddlers with Autism

ERIC Educational Resources Information Center

Patterson, Stephanie Y.; Elder, Lauren; Gulsrud, Amanda; Kasari, Connie

2014-01-01

Purpose: This study examines the relationship between parental interaction style (responsive vs directive) and child-initiated joint engagement within caregiver-child interactions with toddlers diagnosed with autism spectrum disorders. Method: Videotaped interactions of 85 toddler-caregiver dyads were coded for child engagement and both parental…

Interactivity, Information Processing, and Learning on the World Wide Web.

ERIC Educational Resources Information Center

Tremayne, Mark; Dunwoody, Sharon

2001-01-01

Examines the role of interactivity in the presentation of science news on the World Wide Web. Proposes and tests a model of interactive information processing that suggests that characteristics of users and Web sites influence interactivity, which influences knowledge acquisition. Describes use of a think-aloud method to study participants' mental…

FIND: difFerential chromatin INteractions Detection using a spatial Poisson process.

PubMed

Djekidel, Mohamed Nadhir; Chen, Yang; Zhang, Michael Q

2018-02-12

Polymer-based simulations and experimental studies indicate the existence of a spatial dependency between the adjacent DNA fibers involved in the formation of chromatin loops. However, the existing strategies for detecting differential chromatin interactions assume that the interacting segments are spatially independent from the other segments nearby. To resolve this issue, we developed a new computational method, FIND, which considers the local spatial dependency between interacting loci. FIND uses a spatial Poisson process to detect differential chromatin interactions that show a significant difference in their interaction frequency and the interaction frequency of their neighbors. Simulation and biological data analysis show that FIND outperforms the widely used count-based methods and has a better signal-to-noise ratio. © 2018 Djekidel et al.; Published by Cold Spring Harbor Laboratory Press.

Filtering Gene Ontology semantic similarity for identifying protein complexes in large protein interaction networks.

PubMed

Wang, Jian; Xie, Dong; Lin, Hongfei; Yang, Zhihao; Zhang, Yijia

2012-06-21

Many biological processes recognize in particular the importance of protein complexes, and various computational approaches have been developed to identify complexes from protein-protein interaction (PPI) networks. However, high false-positive rate of PPIs leads to challenging identification. A protein semantic similarity measure is proposed in this study, based on the ontology structure of Gene Ontology (GO) terms and GO annotations to estimate the reliability of interactions in PPI networks. Interaction pairs with low GO semantic similarity are removed from the network as unreliable interactions. Then, a cluster-expanding algorithm is used to detect complexes with core-attachment structure on filtered network. Our method is applied to three different yeast PPI networks. The effectiveness of our method is examined on two benchmark complex datasets. Experimental results show that our method performed better than other state-of-the-art approaches in most evaluation metrics. The method detects protein complexes from large scale PPI networks by filtering GO semantic similarity. Removing interactions with low GO similarity significantly improves the performance of complex identification. The expanding strategy is also effective to identify attachment proteins of complexes.

A proteomics method using immunoaffinity fluorogenic derivatization-liquid chromatography/tandem mass spectrometry (FD-LC-MS/MS) to identify a set of interacting proteins.

PubMed

Nakata, Katsunori; Saitoh, Ryoichi; Ishigai, Masaki; Imai, Kazuhiro

2018-02-01

Biological functions in organisms are usually controlled by a set of interacting proteins, and identifying the proteins that interact is useful for understanding the mechanism of the functions. Immunoprecipitation is a method that utilizes the affinity of an antibody to isolate and identify the proteins that have interacted in a biological sample. In this study, the FD-LC-MS/MS method, which involves fluorogenic derivatization followed by separation and quantification by HPLC and finally identification of proteins by HPLC-tandem mass spectrometry, was used to identify proteins in immunoprecipitated samples, using heat shock protein 90 (HSP90) as a model of an interacting protein in HepaRG cells. As a result, HSC70 protein, which was known to form a complex with HSP90, was isolated, together with three different types of HSP90-beta. The results demonstrated that the proposed immunoaffinity-FD-LC-MS/MS method could be useful for simultaneously detecting and identifying the proteins that interact with a certain protein. Copyright © 2017 John Wiley & Sons, Ltd.

An examination of the earthquake behaviour of a retaining wall considering soil-structure interaction

NASA Astrophysics Data System (ADS)

Köktan, Utku; Demir, Gökhan; Kerem Ertek, M.

2017-04-01

The earthquake behavior of retaining walls is commonly calculated with pseudo static approaches based on Mononobe-Okabe method. The seismic ground pressure acting on the retaining wall by the Mononobe-Okabe method does not give a definite idea of the distribution of the seismic ground pressure because it is obtained by balancing the forces acting on the active wedge behind the wall. With this method, wave propagation effects and soil-structure interaction are neglected. The purpose of this study is to examine the earthquake behavior of a retaining wall taking into account the soil-structure interaction. For this purpose, time history seismic analysis of the soil-structure interaction system using finite element method has been carried out considering 3 different soil conditions. Seismic analysis of the soil-structure model was performed according to the earthquake record of "1971, San Fernando Pacoima Dam, 196 degree" existing in the library of MIDAS GTS NX software. The results obtained from the analyses show that the soil-structure interaction is very important for the seismic design of a retaining wall. Keywords: Soil-structure interaction, Finite element model, Retaining wall

A method to improve visual similarity of breast masses for an interactive computer-aided diagnosis environment.

PubMed

Zheng, Bin; Lu, Amy; Hardesty, Lara A; Sumkin, Jules H; Hakim, Christiane M; Ganott, Marie A; Gur, David

2006-01-01

The purpose of this study was to develop and test a method for selecting "visually similar" regions of interest depicting breast masses from a reference library to be used in an interactive computer-aided diagnosis (CAD) environment. A reference library including 1000 malignant mass regions and 2000 benign and CAD-generated false-positive regions was established. When a suspicious mass region is identified, the scheme segments the region and searches for similar regions from the reference library using a multifeature based k-nearest neighbor (KNN) algorithm. To improve selection of reference images, we added an interactive step. All actual masses in the reference library were subjectively rated on a scale from 1 to 9 as to their "visual margins speculations". When an observer identifies a suspected mass region during a case interpretation he/she first rates the margins and the computerized search is then limited only to regions rated as having similar levels of spiculation (within +/-1 scale difference). In an observer preference study including 85 test regions, two sets of the six "similar" reference regions selected by the KNN with and without the interactive step were displayed side by side with each test region. Four radiologists and five nonclinician observers selected the more appropriate ("similar") reference set in a two alternative forced choice preference experiment. All four radiologists and five nonclinician observers preferred the sets of regions selected by the interactive method with an average frequency of 76.8% and 74.6%, respectively. The overall preference for the interactive method was highly significant (p < 0.001). The study demonstrated that a simple interactive approach that includes subjectively perceived ratings of one feature alone namely, a rating of margin "spiculation," could substantially improve the selection of "visually similar" reference images.

In vitro interaction study of retinoic acid isomers with telmisartan and amlodipine by equilibrium dialysis method using UV spectroscopy

NASA Astrophysics Data System (ADS)

Varghese, Susheel John; Johny, Sojimol K.; Paul, David; Ravi, Thengungal Kochupappy

2011-07-01

The in vitro protein binding of retinoic acid isomers (isotretinoin and tretinoin) and the antihypertensive drugs (amlodipine and telmisartan) was studied by equilibrium dialysis method. In this study, free fraction of drugs and the % of binding of drugs in the mixture to bovine serum albumin (BSA) were calculated. The influence of retinoic acid isomers on the % of protein binding of telmisartan and amlodipine at physiological pH (7.4) and temperature (37 ± 0.5 °C) was also evaluated. The in vitro displacement interaction study of drugs telmisartan and amlodipine on retinoic acid isomers and also interaction of retinoic acid isomers on telmisartan and amlodipine were carried out.

Transition-density-fragment interaction combined with transfer integral approach for excitation-energy transfer via charge-transfer states

NASA Astrophysics Data System (ADS)

Fujimoto, Kazuhiro J.

2012-07-01

A transition-density-fragment interaction (TDFI) combined with a transfer integral (TI) method is proposed. The TDFI method was previously developed for describing electronic Coulomb interaction, which was applied to excitation-energy transfer (EET) [K. J. Fujimoto and S. Hayashi, J. Am. Chem. Soc. 131, 14152 (2009)] and exciton-coupled circular dichroism spectra [K. J. Fujimoto, J. Chem. Phys. 133, 124101 (2010)]. In the present study, the TDFI method is extended to the exchange interaction, and hence it is combined with the TI method for applying to the EET via charge-transfer (CT) states. In this scheme, the overlap correction is also taken into account. To check the TDFI-TI accuracy, several test calculations are performed to an ethylene dimer. As a result, the TDFI-TI method gives a much improved description of the electronic coupling, compared with the previous TDFI method. Based on the successful description of the electronic coupling, the decomposition analysis is also performed with the TDFI-TI method. The present analysis clearly shows a large contribution from the Coulomb interaction in most of the cases, and a significant influence of the CT states at the small separation. In addition, the exchange interaction is found to be small in this system. The present approach is useful for analyzing and understanding the mechanism of EET.

Phase transition in the spin- 3 / 2 Blume-Emery-Griffiths model with antiferromagnetic second neighbor interactions

NASA Astrophysics Data System (ADS)

Yezli, M.; Bekhechi, S.; Hontinfinde, F.; EZ-Zahraouy, H.

2016-04-01

Two nonperturbative methods such as Monte-Carlo simulation (MC) and Transfer-Matrix Finite-Size-Scaling calculations (TMFSS) have been used to study the phase transition of the spin- 3 / 2 ​Blume-Emery-Griffiths model (BEG) with quadrupolar and antiferromagnetic next-nearest-neighbor exchange interactions. Ground state and finite temperature phase diagrams are obtained by means of these two methods. New degenerate phases are found and only second order phase transitions occur for all values of the parameter interactions. No sign of the intermediate phase is found from both methods. Critical exponents are also obtained from TMFSS calculations. Ising criticality and nonuniversal behaviors are observed depending on the strength of the second neighbor interaction.

Validity Argument for Assessing L2 Pragmatics in Interaction Using Mixed Methods

ERIC Educational Resources Information Center

Youn, Soo Jung

2015-01-01

This study investigates the validity of assessing L2 pragmatics in interaction using mixed methods, focusing on the evaluation inference. Open role-plays that are meaningful and relevant to the stakeholders in an English for Academic Purposes context were developed for classroom assessment. For meaningful score interpretations and accurate…

Quantum Monte Carlo methods for nuclear physics

DOE PAGES

Carlson, J.; Gandolfi, S.; Pederiva, F.; ...

2015-09-09

Quantum Monte Carlo methods have proved valuable to study the structure and reactions of light nuclei and nucleonic matter starting from realistic nuclear interactions and currents. These ab-initio calculations reproduce many low-lying states, moments, and transitions in light nuclei, and simultaneously predict many properties of light nuclei and neutron matter over a rather wide range of energy and momenta. The nuclear interactions and currents are reviewed along with a description of the continuum quantum Monte Carlo methods used in nuclear physics. These methods are similar to those used in condensed matter and electronic structure but naturally include spin-isospin, tensor, spin-orbit,more » and three-body interactions. A variety of results are presented, including the low-lying spectra of light nuclei, nuclear form factors, and transition matrix elements. Low-energy scattering techniques, studies of the electroweak response of nuclei relevant in electron and neutrino scattering, and the properties of dense nucleonic matter as found in neutron stars are also described. Furthermore, a coherent picture of nuclear structure and dynamics emerges based upon rather simple but realistic interactions and currents.« less

Quantum Monte Carlo methods for nuclear physics

DOE PAGES

Carlson, Joseph A.; Gandolfi, Stefano; Pederiva, Francesco; ...

2014-10-19

Quantum Monte Carlo methods have proved very valuable to study the structure and reactions of light nuclei and nucleonic matter starting from realistic nuclear interactions and currents. These ab-initio calculations reproduce many low-lying states, moments and transitions in light nuclei, and simultaneously predict many properties of light nuclei and neutron matter over a rather wide range of energy and momenta. We review the nuclear interactions and currents, and describe the continuum Quantum Monte Carlo methods used in nuclear physics. These methods are similar to those used in condensed matter and electronic structure but naturally include spin-isospin, tensor, spin-orbit, and three-bodymore » interactions. We present a variety of results including the low-lying spectra of light nuclei, nuclear form factors, and transition matrix elements. We also describe low-energy scattering techniques, studies of the electroweak response of nuclei relevant in electron and neutrino scattering, and the properties of dense nucleonic matter as found in neutron stars. A coherent picture of nuclear structure and dynamics emerges based upon rather simple but realistic interactions and currents.« less

A method for communication analysis in prosthodontics.

PubMed

Sondell, K; Söderfeldt, B; Palmqvist, S

1998-02-01

Particularly in prosthodontics, in which the issues of esthetic preferences and possibilities are abundant, improved knowledge about dentist patient communication during clinical encounters is important. Because previous studies on communication used different methods and patient materials, the results are difficult to evaluate. There is, therefore, a need for methodologic development. One method that makes it possible to quantitatively describe different interaction behaviors during clinical encounters is the Roter Method of Interaction Process Analysis (RIAS). Since the method was developed in the USA for use in the medical context, a translation of the method into Swedish and a modification of the categories for use in prosthodontics were necessary. The revised manual was used to code 10 audio recordings of dentist patient encounters at a specialist clinic for prosthodontics. No major alterations of the RIAS manual were made during the translation and modification. The study shows that it is possible to distinguish patterns of communication in audio-recorded dentist patient encounters. The method also made the identification of different interaction profiles possible. These profiles distinguished well among the audio-recorded encounters. The coding procedures were tested for intra-rater reliability and found to be 97% for utterance classification and lambda = 0.76 for categorization definition. It was concluded that the revised RIAS method is applicable in communication studies in prosthodontics.

[Simple method for precognition of drug interaction between oral iron and phenolic hydroxyl group-containing drugs].

PubMed

Sunagane, Nobuyoshi; Yoshinobu, Etsuko; Murayama, Nobuko; Terawaki, Yasufumi; Kamimura, Naoki; Uruno, Tsutomu

2005-02-01

In the present study, we devised a simple method for detecting the drug interaction between oral iron preparations and phenolic hydroxyl group-containing drugs, using the coloring reaction as indicator, due to the formation of complexes or chelates. In the method, oral iron preparations and test drugs in amounts as much as single dose for adults were added to 10 ml of purified water to make sample suspensions for testing. Thirty minutes after mixing an oral iron suspension and a test drug suspension, the change of color in the mixture was observed macroscopically and graded as 0 to 3, with a marked color change judged as grade 3 and no color change as grade 0. Screening of 14 test drugs commonly used orally was carried out. When using sodium ferrous citrate preparations as oral iron, 5 were classified as grade 3, 2 as grade 2, 4 as grade 1, and 3 as grade 0, respectively. To verify usefulness of the method, the interactions suggested by screening were pharmacokinetically assessed by measuring serum concentrations of the drug in mice. When a levodopa or droxidopa preparation, judged as grade 3 in screening, was concomitantly administered with an iron preparation, a significant reduction in bioavailability of the test drug was observed, indicating possible drug interaction between the test drug and oral iron. Combined administration of an acetaminophen preparation, judged as grade 1, and oral iron preparation showed no influence on the bioavailability of the test drug, implying no detectable interactions between them. In conclusion, the simple method devised in the present study is useful for precognition of drug interactions between oral iron preparations and phenolic hydroxyl group-containing drugs, and the drugs with a higher grade in screening may induce drug interactions with oral iron.

A novel method to identify hub pathways of rheumatoid arthritis based on differential pathway networks.

PubMed

Wei, Shi-Tong; Sun, Yong-Hua; Zong, Shi-Hua

2017-09-01

The aim of the current study was to identify hub pathways of rheumatoid arthritis (RA) using a novel method based on differential pathway network (DPN) analysis. The present study proposed a DPN where protein‑protein interaction (PPI) network was integrated with pathway‑pathway interactions. Pathway data was obtained from background PPI network and the Reactome pathway database. Subsequently, pathway interactions were extracted from the pathway data by building randomized gene‑gene interactions and a weight value was assigned to each pathway interaction using Spearman correlation coefficient (SCC) to identify differential pathway interactions. Differential pathway interactions were visualized using Cytoscape to construct a DPN. Topological analysis was conducted to identify hub pathways that possessed the top 5% degree distribution of DPN. Modules of DPN were mined according to ClusterONE. A total of 855 pathways were selected to build pathway interactions. By filtrating pathway interactions of weight values >0.7, a DPN with 312 nodes and 791 edges was obtained. Topological degree analysis revealed 15 hub pathways, such as heparan sulfate/heparin‑glycosaminoglycan (HS‑GAG) degradation, HS‑GAG metabolism and keratan sulfate degradation for RA based on DPN. Furthermore, hub pathways were also important in modules, which validated the significance of hub pathways. In conclusion, the proposed method is a computationally efficient way to identify hub pathways of RA, which identified 15 hub pathways that may be potential biomarkers and provide insight to future investigation and treatment of RA.

Artifact interactions retard technological improvement: An empirical study

PubMed Central

Magee, Christopher L.

2017-01-01

Empirical research has shown performance improvement of many different technological domains occurs exponentially but with widely varying improvement rates. What causes some technologies to improve faster than others do? Previous quantitative modeling research has identified artifact interactions, where a design change in one component influences others, as an important determinant of improvement rates. The models predict that improvement rate for a domain is proportional to the inverse of the domain’s interaction parameter. However, no empirical research has previously studied and tested the dependence of improvement rates on artifact interactions. A challenge to testing the dependence is that any method for measuring interactions has to be applicable to a wide variety of technologies. Here we propose a novel patent-based method that is both technology domain-agnostic and less costly than alternative methods. We use textual content from patent sets in 27 domains to find the influence of interactions on improvement rates. Qualitative analysis identified six specific keywords that signal artifact interactions. Patent sets from each domain were then examined to determine the total count of these 6 keywords in each domain, giving an estimate of artifact interactions in each domain. It is found that improvement rates are positively correlated with the inverse of the total count of keywords with Pearson correlation coefficient of +0.56 with a p-value of 0.002. The results agree with model predictions, and provide, for the first time, empirical evidence that artifact interactions have a retarding effect on improvement rates of technological domains. PMID:28777798

The Multiple Correspondence Analysis Method and Brain Functional Connectivity: Its Application to the Study of the Non-linear Relationships of Motor Cortex and Basal Ganglia.

PubMed

Rodriguez-Sabate, Clara; Morales, Ingrid; Sanchez, Alberto; Rodriguez, Manuel

2017-01-01

The complexity of basal ganglia (BG) interactions is often condensed into simple models mainly based on animal data and that present BG in closed-loop cortico-subcortical circuits of excitatory/inhibitory pathways which analyze the incoming cortical data and return the processed information to the cortex. This study was aimed at identifying functional relationships in the BG motor-loop of 24 healthy-subjects who provided written, informed consent and whose BOLD-activity was recorded by MRI methods. The analysis of the functional interaction between these centers by correlation techniques and multiple linear regression showed non-linear relationships which cannot be suitably addressed with these methods. The multiple correspondence analysis (MCA), an unsupervised multivariable procedure which can identify non-linear interactions, was used to study the functional connectivity of BG when subjects were at rest. Linear methods showed different functional interactions expected according to current BG models. MCA showed additional functional interactions which were not evident when using lineal methods. Seven functional configurations of BG were identified with MCA, two involving the primary motor and somatosensory cortex, one involving the deepest BG (external-internal globus pallidum, subthalamic nucleus and substantia nigral), one with the input-output BG centers (putamen and motor thalamus), two linking the input-output centers with other BG (external pallidum and subthalamic nucleus), and one linking the external pallidum and the substantia nigral. The results provide evidence that the non-linear MCA and linear methods are complementary and should be best used in conjunction to more fully understand the nature of functional connectivity of brain centers.

The visible touch: in planta visualization of protein-protein interactions by fluorophore-based methods

PubMed Central

Bhat, Riyaz A; Lahaye, Thomas; Panstruga, Ralph

2006-01-01

Non-invasive fluorophore-based protein interaction assays like fluorescence resonance energy transfer (FRET) and bimolecular fluorescence complementation (BiFC, also referred to as "split YFP") have been proven invaluable tools to study protein-protein interactions in living cells. Both methods are now frequently used in the plant sciences and are likely to develop into standard techniques for the identification, verification and in-depth analysis of polypeptide interactions. In this review, we address the individual strengths and weaknesses of both approaches and provide an outlook about new directions and possible future developments for both techniques. PMID:16800872

Conversation analysis as a method for investigating interaction in care home environments.

PubMed

Chatwin, John

2014-11-01

This article gives an outline of how the socio-linguistic approach of conversation analysis can be applied to the analysis of carer-patient interaction in care homes. A single case study from a routine encounter in a residential care home is presented. This is used to show how the conversation analysis method works, the kinds of interactional and communication features it can expose, and what specific contribution this kind of micro-interactional approach may make to improving quality of care in these environments. © The Author(s) 2013 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Comarison of Four Methods for Teaching Phases of the Moon

NASA Astrophysics Data System (ADS)

Upton, Brianna; Cid, Ximena; Lopez, Ramon

2008-03-01

Previous studies have shown that many students have misconceptions about basic concepts in astronomy. As a consequence, various interactive engagement methods have been developed for introductory astronomy. We will present the results of a study that compares four different teaching methods for the subject of the phases of the Moon, which is well known to produce student difficulties. We compare a fairly traditional didactic approach, the use of manipulatives (moonballs) in lecture, the University of Arizona Lecture Tutorials, and an interactive computer program used in a didactic fashion. We use pre- and post-testing with the Lunar Phase Concept Inventory to determine the relative effectiveness of these methods.

AA9int: SNP Interaction Pattern Search Using Non-Hierarchical Additive Model Set.

PubMed

Lin, Hui-Yi; Huang, Po-Yu; Chen, Dung-Tsa; Tung, Heng-Yuan; Sellers, Thomas A; Pow-Sang, Julio; Eeles, Rosalind; Easton, Doug; Kote-Jarai, Zsofia; Amin Al Olama, Ali; Benlloch, Sara; Muir, Kenneth; Giles, Graham G; Wiklund, Fredrik; Gronberg, Henrik; Haiman, Christopher A; Schleutker, Johanna; Nordestgaard, Børge G; Travis, Ruth C; Hamdy, Freddie; Neal, David E; Pashayan, Nora; Khaw, Kay-Tee; Stanford, Janet L; Blot, William J; Thibodeau, Stephen N; Maier, Christiane; Kibel, Adam S; Cybulski, Cezary; Cannon-Albright, Lisa; Brenner, Hermann; Kaneva, Radka; Batra, Jyotsna; Teixeira, Manuel R; Pandha, Hardev; Lu, Yong-Jie; Park, Jong Y

2018-06-07

The use of single nucleotide polymorphism (SNP) interactions to predict complex diseases is getting more attention during the past decade, but related statistical methods are still immature. We previously proposed the SNP Interaction Pattern Identifier (SIPI) approach to evaluate 45 SNP interaction patterns/patterns. SIPI is statistically powerful but suffers from a large computation burden. For large-scale studies, it is necessary to use a powerful and computation-efficient method. The objective of this study is to develop an evidence-based mini-version of SIPI as the screening tool or solitary use and to evaluate the impact of inheritance mode and model structure on detecting SNP-SNP interactions. We tested two candidate approaches: the 'Five-Full' and 'AA9int' method. The Five-Full approach is composed of the five full interaction models considering three inheritance modes (additive, dominant and recessive). The AA9int approach is composed of nine interaction models by considering non-hierarchical model structure and the additive mode. Our simulation results show that AA9int has similar statistical power compared to SIPI and is superior to the Five-Full approach, and the impact of the non-hierarchical model structure is greater than that of the inheritance mode in detecting SNP-SNP interactions. In summary, it is recommended that AA9int is a powerful tool to be used either alone or as the screening stage of a two-stage approach (AA9int+SIPI) for detecting SNP-SNP interactions in large-scale studies. The 'AA9int' and 'parAA9int' functions (standard and parallel computing version) are added in the SIPI R package, which is freely available at https://linhuiyi.github.io/LinHY_Software/. hlin1@lsuhsc.edu. Supplementary data are available at Bioinformatics online.

Water interactions with hydrophobic groups: Assessment and recalibration of semiempirical molecular orbital methods

NASA Astrophysics Data System (ADS)

Marion, Antoine; Monard, Gérald; Ruiz-López, Manuel F.; Ingrosso, Francesca

2014-07-01

In this work, we present a study of the ability of different semiempirical methods to describe intermolecular interactions in water solution. In particular, we focus on methods based on the Neglect of Diatomic Differential Overlap approximation. Significant improvements of these methods have been reported in the literature in the past years regarding the description of non-covalent interactions. In particular, a broad range of methodologies has been developed to deal with the properties of hydrogen-bonded systems, with varying degrees of success. In contrast, the interactions between water and a molecule containing hydrophobic groups have been little analyzed. Indeed, by considering the potential energy surfaces obtained using different semiempirical Hamiltonians for the intermolecular interactions of model systems, we found that none of the available methods provides an entirely satisfactory description of both hydrophobic and hydrophilic interactions in water. In addition, a vibrational analysis carried out in a model system for these interactions, a methane clathrate cluster, showed that some recent methods cannot be used to carry out studies of vibrational properties. Following a procedure established in our group [M. I. Bernal-Uruchurtu, M. T. C. Martins-Costa, C. Millot, and M. F. Ruiz-López, J. Comput. Chem. 21, 572 (2000); W. Harb, M. I. Bernal-Uruchurtu, and M. F. Ruiz-López, Theor. Chem. Acc. 112, 204 (2004)], we developed new parameters for the core-core interaction terms based on fitting potential energy curves obtained at the MP2 level for our model system. We investigated the transferability of the new parameters to describe a system, having both hydrophilic and hydrophobic groups, interacting with water. We found that only by introducing two different sets of parameters for hydrophilic and hydrophobic hydrogen atom types we are able to match the features of the ab initio calculated properties. Once this assumption is made, a good agreement with the MP2 reference is achieved. The results reported in this work provide therefore a direction for future developments of semiempirical approaches that are still required to investigate chemical processes in biomolecules and in large disordered systems.

Life-table methods for detecting age-risk factor interactions in long-term follow-up studies.

PubMed

Logue, E E; Wing, S

1986-01-01

Methodological investigation has suggested that age-risk factor interactions should be more evident in age of experience life tables than in follow-up time tables due to the mixing of ages of experience over follow-up time in groups defined by age at initial examination. To illustrate the two approaches, age modification of the effect of total cholesterol on ischemic heart disease mortality in two long-term follow-up studies was investigated. Follow-up time life table analysis of 116 deaths over 20 years in one study was more consistent with a uniform relative risk due to cholesterol, while age of experience life table analysis was more consistent with a monotonic negative age interaction. In a second follow-up study (160 deaths over 24 years), there was no evidence of a monotonic negative age-cholesterol interaction by either method. It was concluded that age-specific life table analysis should be used when age-risk factor interactions are considered, but that both approaches yield almost identical results in absence of age interaction. The identification of the more appropriate life-table analysis should be ultimately guided by the nature of the age or time phenomena of scientific interest.

Numerical approach for finite volume three-body interaction

NASA Astrophysics Data System (ADS)

Guo, Peng; Gasparian, Vladimir

2018-01-01

In the present work, we study a numerical approach to one dimensional finite volume three-body interaction, the method is demonstrated by considering a toy model of three spinless particles interacting with pair-wise δ -function potentials. The numerical results are compared with the exact solutions of three spinless bosons interaction when the strength of short-range interactions are set equal for all pairs.

Interactions of cephalexin with bovine serum albumin: displacement reaction and molecular docking.

PubMed

Hamishehkar, Hamed; Hosseini, Soheila; Naseri, Abdolhossein; Safarnejad, Azam; Rasoulzadeh, Farzaneh

2016-01-01

Introduction: The drug-plasma protein interaction is a fundamental issue in guessing and checking the serious drug side effects related with other drugs. The purpose of this research was to study the interaction of cephalexin with bovine serum albumin (BSA) and displacement reaction using site probes. Methods: The interaction mechanism concerning cephalexin (CPL) with BSA was investigated using various spectroscopic methods and molecular modeling method. The binding sites number, n, apparent binding constant, K, and thermodynamic parameters, ΔG 0 , ΔH 0 , and ΔS 0 were considered at different temperatures. To evaluate the experimental results, molecular docking modeling was calculated. Results: The distance, r=1.156 nm between BSA and CPL were found in accordance with the Forster theory of non-radiation energy transfer (FRET) indicating energy transfer occurs between BSA and CPL. According to the binding parameters and ΔG 0 = negative values and ΔS 0 = 28.275 j mol -1 K -1 , a static quenching process is effective in the CPL-BSA interaction spontaneously. ΔG 0 for the CPL-BSA complex obtained from the docking simulation is -28.99 kj mol -1 , which is close to experimental ΔG of binding, -21.349 kj mol -1 that indicates a good agreement between the results of docking methods and experimental data. Conclusion: The outcomes of spectroscopic methods revealed that the conformation of BSA changed during drug-BSA interaction. The results of FRET propose that CPL quenches the fluorescence of BSA by static quenching and FRET. The displacement study showed that phenylbutazon and ketoprofen displaced CPL, indicating that its binding site on albumin is site I and Gentamicin cannot be displaced from the binding site of CPL. All results of molecular docking method agreed with the results of experimental data.

The effectiveness of hydrotherapy in the treatment of social and behavioral aspects of children with autism spectrum disorders: a systematic review

PubMed Central

Mortimer, Rachel; Privopoulos, Melinda; Kumar, Saravana

2014-01-01

Background Autism spectrum disorders (ASDs) are increasing in prevalence. Children with ASDs present with impairments in social interactions; communication; restricted, repetitive, and stereotyped patterns of behavior, interests, or activities; as well as motor delays. Hydrotherapy is used as a treatment for children with disabilities and motor delays. There have been no systematic reviews conducted on the effectiveness of hydrotherapy in children with ASDs. Aim We aimed to examine the effectiveness of hydrotherapy on social interactions and behaviors in the treatment of children with ASDs. Methods A systematic search of Cochrane, CINAHL, PsycINFO, Embase, MEDLINE®, and Academic Search Premier was conducted. Studies of participants, aged 3–18 years, with ASDs at a high-functioning level were included if they utilized outcome measures assessing social interactions and behaviors through questionnaire or observation. A critical appraisal, using the McMaster Critical Review Form for Quantitative Studies, was performed to assess methodological quality. Results Four studies of varying research design and quality met the inclusion criteria. The participants in these studies were aged between 3–12 years of age. The duration of the intervention ranged from 10–14 weeks, and each study used varied measures of outcome. Overall, all the studies showed some improvements in social interactions or behaviors following a Halliwick-based hydrotherapy intervention. Interpretation Few studies have investigated the effect of hydrotherapy on the social interactions and behaviors of children with ASDs. While there is an increasing body of evidence for hydrotherapy for children with ASDs, this is constrained by small sample size, lack of comparator, crude sampling methods, and the lack of standardized outcome measures. Hydrotherapy shows potential as a treatment method for social interactions and behaviors in children with ASDs. PMID:24520196

A Grammatical Approach to RNA-RNA Interaction Prediction

NASA Astrophysics Data System (ADS)

Kato, Yuki; Akutsu, Tatsuya; Seki, Hiroyuki

2007-11-01

Much attention has been paid to two interacting RNA molecules involved in post-transcriptional control of gene expression. Although there have been a few studies on RNA-RNA interaction prediction based on dynamic programming algorithm, no grammar-based approach has been proposed. The purpose of this paper is to provide a new modeling for RNA-RNA interaction based on multiple context-free grammar (MCFG). We present a polynomial time parsing algorithm for finding the most likely derivation tree for the stochastic version of MCFG, which is applicable to RNA joint secondary structure prediction including kissing hairpin loops. Also, elementary tests on RNA-RNA interaction prediction have shown that the proposed method is comparable to Alkan et al.'s method.

Recent advances in understanding the interaction of groundwater and surface water

USGS Publications Warehouse

Winter, Thomas C.

1995-01-01

The most common image of the interaction of groundwater and surface water is that of the interaction of streams with a contiguous alluvial aquifer. This type of system has been the focus of study for more than 100 years, from the work of Boussinesq (1877) to the present, and stream-aquifer interaction continues to be the most common topic of papers discussing the interaction of groundwater and surface water. However, groundwater and surface water interact in a wide variety of landscapes from alpine to coastal. Within these landscapes, ground-water systems range in scale from local to regional, and the types of surface water include streams, lakes, wetlands, and oceans. Given the broad spectrum of the topic of groundwater and surface water interaction, an overview of studies of this topic could be organized according to surface water type, landscape type, scale of hydrologic systems, or field and analytical methods. All these factors are discussed, but this paper is organized according to landscape type because of the great increase in studies of the interaction of groundwater and surface water in landscapes other than riverine systems in the last 15 years. Furthermore, discussing studies by landscape type facilitates comparison of methods and results from different geologic and climatic settings. The general landscapes discussed are mountain terrane, riverine systems, coastal terrane, hummocky terrane, and karst terrane.

A kernel regression approach to gene-gene interaction detection for case-control studies.

PubMed

Larson, Nicholas B; Schaid, Daniel J

2013-11-01

Gene-gene interactions are increasingly being addressed as a potentially important contributor to the variability of complex traits. Consequently, attentions have moved beyond single locus analysis of association to more complex genetic models. Although several single-marker approaches toward interaction analysis have been developed, such methods suffer from very high testing dimensionality and do not take advantage of existing information, notably the definition of genes as functional units. Here, we propose a comprehensive family of gene-level score tests for identifying genetic elements of disease risk, in particular pairwise gene-gene interactions. Using kernel machine methods, we devise score-based variance component tests under a generalized linear mixed model framework. We conducted simulations based upon coalescent genetic models to evaluate the performance of our approach under a variety of disease models. These simulations indicate that our methods are generally higher powered than alternative gene-level approaches and at worst competitive with exhaustive SNP-level (where SNP is single-nucleotide polymorphism) analyses. Furthermore, we observe that simulated epistatic effects resulted in significant marginal testing results for the involved genes regardless of whether or not true main effects were present. We detail the benefits of our methods and discuss potential genome-wide analysis strategies for gene-gene interaction analysis in a case-control study design. © 2013 WILEY PERIODICALS, INC.

With whom do you feel most intimate?: Exploring the quality of Facebook friendships in relation to similarities and interaction behaviors.

PubMed

Wee, Jieun; Lee, Joonhwan

2017-01-01

It is widely accepted that people tend to associate more and feel closer to those who share similar attributes with themselves. Most of the research on the phenomenon has been carried out in face-to-face contexts. However, it is necessary to study the phenomenon in computer-mediated contexts as well. Exploring Facebook is important in that friendships within the network indicate a broader spectrum of friends, ranging from complete strangers to confiding relations. Also, since diverse communication methods are available on Facebook, which method a user adopts to interact with a "friend" could influence the quality of the relationship, i.e. intimacy. Thus, current research aims to test whether people in computer-mediated contexts do perceive more intimacy toward friends who share similar traits, and further, aims to examine which interaction methods influence the closeness of relationship by collecting activity data of users on Facebook. Results from current study show traits related to intimacy in the online context of Facebook. Moreover, in addition to the interaction type itself, direction of the interaction influenced how intimate users feel towards their friends. Overall findings suggest that further investigation on the dynamics of online communication methods used in developing and maintaining relationships is necessary.

With whom do you feel most intimate?: Exploring the quality of Facebook friendships in relation to similarities and interaction behaviors

PubMed Central

Wee, Jieun; Lee, Joonhwan

2017-01-01

It is widely accepted that people tend to associate more and feel closer to those who share similar attributes with themselves. Most of the research on the phenomenon has been carried out in face-to-face contexts. However, it is necessary to study the phenomenon in computer-mediated contexts as well. Exploring Facebook is important in that friendships within the network indicate a broader spectrum of friends, ranging from complete strangers to confiding relations. Also, since diverse communication methods are available on Facebook, which method a user adopts to interact with a “friend” could influence the quality of the relationship, i.e. intimacy. Thus, current research aims to test whether people in computer-mediated contexts do perceive more intimacy toward friends who share similar traits, and further, aims to examine which interaction methods influence the closeness of relationship by collecting activity data of users on Facebook. Results from current study show traits related to intimacy in the online context of Facebook. Moreover, in addition to the interaction type itself, direction of the interaction influenced how intimate users feel towards their friends. Overall findings suggest that further investigation on the dynamics of online communication methods used in developing and maintaining relationships is necessary. PMID:28453526

Interactive Multimedia Package in Ameliorating Communicative Skill in English

ERIC Educational Resources Information Center

Singaravelu, G.

2011-01-01

The study enlightens the effectiveness of Interactive-Multimedia Package in developing communicative skill in English at standard VI. Present methods of developing communicative skill are ineffective to the students in improving their communicative competencies in English. Challenging interactive Multimedia Package helps to enhance the…

Learning contextual gene set interaction networks of cancer with condition specificity

PubMed Central

2013-01-01

Background Identifying similarities and differences in the molecular constitutions of various types of cancer is one of the key challenges in cancer research. The appearances of a cancer depend on complex molecular interactions, including gene regulatory networks and gene-environment interactions. This complexity makes it challenging to decipher the molecular origin of the cancer. In recent years, many studies reported methods to uncover heterogeneous depictions of complex cancers, which are often categorized into different subtypes. The challenge is to identify diverse molecular contexts within a cancer, to relate them to different subtypes, and to learn underlying molecular interactions specific to molecular contexts so that we can recommend context-specific treatment to patients. Results In this study, we describe a novel method to discern molecular interactions specific to certain molecular contexts. Unlike conventional approaches to build modular networks of individual genes, our focus is to identify cancer-generic and subtype-specific interactions between contextual gene sets, of which each gene set share coherent transcriptional patterns across a subset of samples, termed contextual gene set. We then apply a novel formulation for quantitating the effect of the samples from each subtype on the calculated strength of interactions observed. Two cancer data sets were analyzed to support the validity of condition-specificity of identified interactions. When compared to an existing approach, the proposed method was much more sensitive in identifying condition-specific interactions even in heterogeneous data set. The results also revealed that network components specific to different types of cancer are related to different biological functions than cancer-generic network components. We found not only the results that are consistent with previous studies, but also new hypotheses on the biological mechanisms specific to certain cancer types that warrant further investigations. Conclusions The analysis on the contextual gene sets and characterization of networks of interaction composed of these sets discovered distinct functional differences underlying various types of cancer. The results show that our method successfully reveals many subtype-specific regions in the identified maps of biological contexts, which well represent biological functions that can be connected to specific subtypes. PMID:23418942

Study of plasma formation in CW CO2 laser beam-metal surface interaction

NASA Astrophysics Data System (ADS)

Azharonok, V. V.; Vasilchenko, Zh V.; Golubev, Vladimir S.; Gresev, A. N.; Zabelin, Alexandre M.; Chubrik, N. I.; Shimanovich, V. D.

1994-04-01

An interaction of the cw CO2 laser beam and a moving metal surface has been studied. The pulsed and thermodynamical parameters of the surface plasma were investigated by optical and spectroscopical methods. The subsonic radiation wave propagation in the erosion plasma torch has been studied.

MEG dual scanning: a procedure to study real-time auditory interaction between two persons

PubMed Central

Baess, Pamela; Zhdanov, Andrey; Mandel, Anne; Parkkonen, Lauri; Hirvenkari, Lotta; Mäkelä, Jyrki P.; Jousmäki, Veikko; Hari, Riitta

2012-01-01

Social interactions fill our everyday life and put strong demands on our brain function. However, the possibilities for studying the brain basis of social interaction are still technically limited, and even modern brain imaging studies of social cognition typically monitor just one participant at a time. We present here a method to connect and synchronize two faraway neuromagnetometers. With this method, two participants at two separate sites can interact with each other through a stable real-time audio connection with minimal delay and jitter. The magnetoencephalographic (MEG) and audio recordings of both laboratories are accurately synchronized for joint offline analysis. The concept can be extended to connecting multiple MEG devices around the world. As a proof of concept of the MEG-to-MEG link, we report the results of time-sensitive recordings of cortical evoked responses to sounds delivered at laboratories separated by 5 km. PMID:22514530

Study on fluid-structure interaction in liquid oxygen feeding pipe systems using finite volume method

NASA Astrophysics Data System (ADS)

Wei, Xin; Sun, Bing

2011-10-01

The fluid-structure interaction may occur in space launch vehicles, which would lead to bad performance of vehicles, damage equipments on vehicles, or even affect astronauts' health. In this paper, analysis on dynamic behavior of liquid oxygen (LOX) feeding pipe system in a large scale launch vehicle is performed, with the effect of fluid-structure interaction (FSI) taken into consideration. The pipe system is simplified as a planar FSI model with Poisson coupling and junction coupling. Numerical tests on pipes between the tank and the pump are solved by the finite volume method. Results show that restrictions weaken the interaction between axial and lateral vibrations. The reasonable results regarding frequencies and modes indicate that the FSI affects substantially the dynamic analysis, and thus highlight the usefulness of the proposed model. This study would provide a reference to the pipe test, as well as facilitate further studies on oscillation suppression.

Interaction between IGFBP7 and insulin: a theoretical and experimental study

NASA Astrophysics Data System (ADS)

Ruan, Wenjing; Kang, Zhengzhong; Li, Youzhao; Sun, Tianyang; Wang, Lipei; Liang, Lijun; Lai, Maode; Wu, Tao

2016-04-01

Insulin-like growth factor binding protein 7 (IGFBP7) can bind to insulin with high affinity which inhibits the early steps of insulin action. Lack of recognition mechanism impairs our understanding of insulin regulation before it binds to insulin receptor. Here we combine computational simulations with experimental methods to investigate the interaction between IGFBP7 and insulin. Molecular dynamics simulations indicated that His200 and Arg198 in IGFBP7 were key residues. Verified by experimental data, the interaction remained strong in single mutation systems R198E and H200F but became weak in double mutation system R198E-H200F relative to that in wild-type IGFBP7. The results and methods in present study could be adopted in future research of discovery of drugs by disrupting protein-protein interactions in insulin signaling. Nevertheless, the accuracy, reproducibility, and costs of free-energy calculation are still problems that need to be addressed before computational methods can become standard binding prediction tools in discovery pipelines.

A method for fast energy estimation and visualization of protein-ligand interaction

NASA Astrophysics Data System (ADS)

Tomioka, Nobuo; Itai, Akiko; Iitaka, Yoichi

1987-10-01

A new computational and graphical method for facilitating ligand-protein docking studies is developed on a three-dimensional computer graphics display. Various physical and chemical properties inside the ligand binding pocket of a receptor protein, whose structure is elucidated by X-ray crystal analysis, are calculated on three-dimensional grid points and are stored in advance. By utilizing those tabulated data, it is possible to estimate the non-bonded and electrostatic interaction energy and the number of possible hydrogen bonds between protein and ligand molecules in real time during an interactive docking operation. The method also provides a comprehensive visualization of the local environment inside the binding pocket. With this method, it becomes easier to find a roughly stable geometry of ligand molecules, and one can therefore make a rapid survey of the binding capability of many drug candidates. The method will be useful for drug design as well as for the examination of protein-ligand interactions.

Socratic Questioning in the Paideia Method to Encourage Dialogical Discussions

ERIC Educational Resources Information Center

Davies, Maree; Sinclair, Anne

2014-01-01

This study focused on the impact of using Socratic questioning, based on the Paideia Method, on the nature of middle-schools students' patterns of interaction and on the cognitive complexity of their discussions. The hypothesis is that an experimental group will increase in both interaction focus and complexity at T3, which is the face-to-face…

The Effects of Computer-Supported Inquiry-Based Learning Methods and Peer Interaction on Learning Stellar Parallax

ERIC Educational Resources Information Center

Ruzhitskaya, Lanika

2011-01-01

The presented research study investigated the effects of computer-supported inquiry-based learning and peer interaction methods on effectiveness of learning a scientific concept. The stellar parallax concept was selected as a basic, and yet important in astronomy, scientific construct, which is based on a straightforward relationship of several…

3-Dimensional and Interactive Istanbul University Virtual Laboratory Based on Active Learning Methods

ERIC Educational Resources Information Center

Ince, Elif; Kirbaslar, Fatma Gulay; Yolcu, Ergun; Aslan, Ayse Esra; Kayacan, Zeynep Cigdem; Alkan Olsson, Johanna; Akbasli, Ayse Ceylan; Aytekin, Mesut; Bauer, Thomas; Charalambis, Dimitris; Gunes, Zeliha Ozsoy; Kandemir, Ceyhan; Sari, Umit; Turkoglu, Suleyman; Yaman, Yavuz; Yolcu, Ozgu

2014-01-01

The purpose of this study is to develop a 3-dimensional interactive multi-user and multi-admin IUVIRLAB featuring active learning methods and techniques for university students and to introduce the Virtual Laboratory of Istanbul University and to show effects of IUVIRLAB on students' attitudes on communication skills and IUVIRLAB. Although there…

A Note on the Specification of Error Structures in Latent Interaction Models

ERIC Educational Resources Information Center

Mao, Xiulin; Harring, Jeffrey R.; Hancock, Gregory R.

2015-01-01

Latent interaction models have motivated a great deal of methodological research, mainly in the area of estimating such models. Product-indicator methods have been shown to be competitive with other methods of estimation in terms of parameter bias and standard error accuracy, and their continued popularity in empirical studies is due, in part, to…

Studying the Impact of Using Multimedia Interactive Programs at Children Ability to Learn Basic Math Skills

ERIC Educational Resources Information Center

Nusir, Sawsan; Alsmadi, Izzat; Al-Kabi, Mohammed; Sharadgah, Fatima

2012-01-01

The continuous inventions and evolutions in all information technology fields open new channels and opportunities to enhance teaching and educational methods. In one side, those may improve the abilities of educators to present information in an interactive and media enhanced formats relative to traditional methods. This may help students or…

Studying the Impact of Using Multimedia Interactive Programs on Children's Ability to Learn Basic Math Skills

ERIC Educational Resources Information Center

Nusir, Sawsan; Alsmadi, Izzat; Al-Kabi, Mohammed; Sharadgah, Fatima

2013-01-01

The continuous inventions and evolutions in all information technology fields open new channels and opportunities to enhance teaching and educational methods. On one side, these may improve the abilities of educators to present information in interactive and media-enhanced formats relative to traditional methods. This may help students or learners…

S66: A Well-balanced Database of Benchmark Interaction Energies Relevant to Biomolecular Structures

PubMed Central

2011-01-01

With numerous new quantum chemistry methods being developed in recent years and the promise of even more new methods to be developed in the near future, it is clearly critical that highly accurate, well-balanced, reference data for many different atomic and molecular properties be available for the parametrization and validation of these methods. One area of research that is of particular importance in many areas of chemistry, biology, and material science is the study of noncovalent interactions. Because these interactions are often strongly influenced by correlation effects, it is necessary to use computationally expensive high-order wave function methods to describe them accurately. Here, we present a large new database of interaction energies calculated using an accurate CCSD(T)/CBS scheme. Data are presented for 66 molecular complexes, at their reference equilibrium geometries and at 8 points systematically exploring their dissociation curves; in total, the database contains 594 points: 66 at equilibrium geometries, and 528 in dissociation curves. The data set is designed to cover the most common types of noncovalent interactions in biomolecules, while keeping a balanced representation of dispersion and electrostatic contributions. The data set is therefore well suited for testing and development of methods applicable to bioorganic systems. In addition to the benchmark CCSD(T) results, we also provide decompositions of the interaction energies by means of DFT-SAPT calculations. The data set was used to test several correlated QM methods, including those parametrized specifically for noncovalent interactions. Among these, the SCS-MI-CCSD method outperforms all other tested methods, with a root-mean-square error of 0.08 kcal/mol for the S66 data set. PMID:21836824

Cloud computing for detecting high-order genome-wide epistatic interaction via dynamic clustering.

PubMed

Guo, Xuan; Meng, Yu; Yu, Ning; Pan, Yi

2014-04-10

Taking the advantage of high-throughput single nucleotide polymorphism (SNP) genotyping technology, large genome-wide association studies (GWASs) have been considered to hold promise for unravelling complex relationships between genotype and phenotype. At present, traditional single-locus-based methods are insufficient to detect interactions consisting of multiple-locus, which are broadly existing in complex traits. In addition, statistic tests for high order epistatic interactions with more than 2 SNPs propose computational and analytical challenges because the computation increases exponentially as the cardinality of SNPs combinations gets larger. In this paper, we provide a simple, fast and powerful method using dynamic clustering and cloud computing to detect genome-wide multi-locus epistatic interactions. We have constructed systematic experiments to compare powers performance against some recently proposed algorithms, including TEAM, SNPRuler, EDCF and BOOST. Furthermore, we have applied our method on two real GWAS datasets, Age-related macular degeneration (AMD) and Rheumatoid arthritis (RA) datasets, where we find some novel potential disease-related genetic factors which are not shown up in detections of 2-loci epistatic interactions. Experimental results on simulated data demonstrate that our method is more powerful than some recently proposed methods on both two- and three-locus disease models. Our method has discovered many novel high-order associations that are significantly enriched in cases from two real GWAS datasets. Moreover, the running time of the cloud implementation for our method on AMD dataset and RA dataset are roughly 2 hours and 50 hours on a cluster with forty small virtual machines for detecting two-locus interactions, respectively. Therefore, we believe that our method is suitable and effective for the full-scale analysis of multiple-locus epistatic interactions in GWAS.

Cloud computing for detecting high-order genome-wide epistatic interaction via dynamic clustering

PubMed Central

2014-01-01

Backgroud Taking the advan tage of high-throughput single nucleotide polymorphism (SNP) genotyping technology, large genome-wide association studies (GWASs) have been considered to hold promise for unravelling complex relationships between genotype and phenotype. At present, traditional single-locus-based methods are insufficient to detect interactions consisting of multiple-locus, which are broadly existing in complex traits. In addition, statistic tests for high order epistatic interactions with more than 2 SNPs propose computational and analytical challenges because the computation increases exponentially as the cardinality of SNPs combinations gets larger. Results In this paper, we provide a simple, fast and powerful method using dynamic clustering and cloud computing to detect genome-wide multi-locus epistatic interactions. We have constructed systematic experiments to compare powers performance against some recently proposed algorithms, including TEAM, SNPRuler, EDCF and BOOST. Furthermore, we have applied our method on two real GWAS datasets, Age-related macular degeneration (AMD) and Rheumatoid arthritis (RA) datasets, where we find some novel potential disease-related genetic factors which are not shown up in detections of 2-loci epistatic interactions. Conclusions Experimental results on simulated data demonstrate that our method is more powerful than some recently proposed methods on both two- and three-locus disease models. Our method has discovered many novel high-order associations that are significantly enriched in cases from two real GWAS datasets. Moreover, the running time of the cloud implementation for our method on AMD dataset and RA dataset are roughly 2 hours and 50 hours on a cluster with forty small virtual machines for detecting two-locus interactions, respectively. Therefore, we believe that our method is suitable and effective for the full-scale analysis of multiple-locus epistatic interactions in GWAS. PMID:24717145

Identification of New Genetic Susceptibility Loci for Breast Cancer Through Consideration of Gene-Environment Interactions

PubMed Central

Schoeps, Anja; Rudolph, Anja; Seibold, Petra; Dunning, Alison M.; Milne, Roger L.; Bojesen, Stig E.; Swerdlow, Anthony; Andrulis, Irene; Brenner, Hermann; Behrens, Sabine; Orr, Nicholas; Jones, Michael; Ashworth, Alan; Li, Jingmei; Cramp, Helen; Connley, Dan; Czene, Kamila; Darabi, Hatef; Chanock, Stephen J.; Lissowska, Jolanta; Figueroa, Jonine D.; Knight, Julia; Glendon, Gord; Mulligan, Anna M.; Dumont, Martine; Severi, Gianluca; Baglietto, Laura; Olson, Janet; Vachon, Celine; Purrington, Kristen; Moisse, Matthieu; Neven, Patrick; Wildiers, Hans; Spurdle, Amanda; Kosma, Veli-Matti; Kataja, Vesa; Hartikainen, Jaana M.; Hamann, Ute; Ko, Yon-Dschun; Dieffenbach, Aida K.; Arndt, Volker; Stegmaier, Christa; Malats, Núria; Arias Perez, JoséI.; Benítez, Javier; Flyger, Henrik; Nordestgaard, Børge G.; Truong, Théresè; Cordina-Duverger, Emilie; Menegaux, Florence; Silva, Isabel dos Santos; Fletcher, Olivia; Johnson, Nichola; Häberle, Lothar; Beckmann, Matthias W.; Ekici, Arif B.; Braaf, Linde; Atsma, Femke; van den Broek, Alexandra J.; Makalic, Enes; Schmidt, Daniel F.; Southey, Melissa C.; Cox, Angela; Simard, Jacques; Giles, Graham G.; Lambrechts, Diether; Mannermaa, Arto; Brauch, Hiltrud; Guénel, Pascal; Peto, Julian; Fasching, Peter A.; Hopper, John; Flesch-Janys, Dieter; Couch, Fergus; Chenevix-Trench, Georgia; Pharoah, Paul D. P.; Garcia-Closas, Montserrat; Schmidt, Marjanka K.; Hall, Per; Easton, Douglas F.; Chang-Claude, Jenny

2014-01-01

Genes that alter disease risk only in combination with certain environmental exposures may not be detected in genetic association analysis. By using methods accounting for gene-environment (G × E) interaction, we aimed to identify novel genetic loci associated with breast cancer risk. Up to 34,475 cases and 34,786 controls of European ancestry from up to 23 studies in the Breast Cancer Association Consortium were included. Overall, 71,527 single nucleotide polymorphisms (SNPs), enriched for association with breast cancer, were tested for interaction with 10 environmental risk factors using three recently proposed hybrid methods and a joint test of association and interaction. Analyses were adjusted for age, study, population stratification, and confounding factors as applicable. Three SNPs in two independent loci showed statistically significant association: SNPs rs10483028 and rs2242714 in perfect linkage disequilibrium on chromosome 21 and rs12197388 in ARID1B on chromosome 6. While rs12197388 was identified using the joint test with parity and with age at menarche (P-values = 3 × 10−07), the variants on chromosome 21 q22.12, which showed interaction with adult body mass index (BMI) in 8,891 postmenopausal women, were identified by all methods applied. SNP rs10483028 was associated with breast cancer in women with a BMI below 25 kg/m2 (OR = 1.26, 95% CI 1.15–1.38) but not in women with a BMI of 30 kg/m2 or higher (OR = 0.89, 95% CI 0.72–1.11, P for interaction = 3.2 × 10−05). Our findings confirm comparable power of the recent methods for detecting G × E interaction and the utility of using G × E interaction analyses to identify new susceptibility loci. PMID:24248812

In vitro interaction study of retinoic acid isomers with telmisartan and amlodipine by equilibrium dialysis method using UV spectroscopy.

PubMed

Varghese, Susheel John; Johny, Sojimol K; Paul, David; Ravi, Thengungal Kochupappy

2011-07-01

The in vitro protein binding of retinoic acid isomers (isotretinoin and tretinoin) and the antihypertensive drugs (amlodipine and telmisartan) was studied by equilibrium dialysis method. In this study, free fraction of drugs and the % of binding of drugs in the mixture to bovine serum albumin (BSA) were calculated. The influence of retinoic acid isomers on the % of protein binding of telmisartan and amlodipine at physiological pH (7.4) and temperature (37±0.5°C) was also evaluated. The in vitro displacement interaction study of drugs telmisartan and amlodipine on retinoic acid isomers and also interaction of retinoic acid isomers on telmisartan and amlodipine were carried out. Copyright © 2011 Elsevier B.V. All rights reserved.

New Method for Insomnia Mongolian Mind-Body Interactive Psychotherapy in the Assessment of Chronic Insomnia: A Retrospective Study.

PubMed

He, Nagongbilige; Lan, Wu; Jiang, Aruna; Jia, Haserden; Bao, Shuzhi; Bao, Longmei; Qin, Altansha; Bao, Orgel; Bao, Shinjiltu; Wang, Nandin; Bao, Suyaltu; Dai, Shuangfu; Bao, Sarula; Arlud, Sarnai

2018-06-19

Insomnia is a common clinical complaint, and if not addressed it can increase the risk of developing other underlying diseases such as hypertension, depression and anxiety. The use of Mongolian mind-body interactive therapy as a comprehensive psychotherapeutic approach in chronic insomnia has been shown in this retrospective study. Subjects who had suffered insomnia for more than 1 month participated in the Mongolian mind-body interactive psychotherapy program between June 2012 and February 2014. They were interviewed by telephone at least 10 months before participating in the program. Their sleep was assessed using the Athens insomnia scale. Descriptive statistics, ANOVA and regression analysis were used for data analysis by SPSS software. Mongolian mind-body interactive psychotherapy significantly improved sleeping conditions. In ANOVA analysis, both short- and long-term outcomes were significantly affected by the treatment period. Patients who previously took medication and pre-treatment sleeping condition (ASI score) had a significant influence on long-term outcomes, as well as treatment time related to the duration of insomnia. Mongolian mind-body interactive psychotherapy is a new method for insomnia, and narrative therapy and hypnotic methods together improve the sleeping condition, However, a further controlled randomized clinical study is needed to understand the efficacy.

New techniques for experimental generation of two-dimensional blade-vortex interaction at low Reynolds numbers

NASA Technical Reports Server (NTRS)

Booth, E., Jr.; Yu, J. C.

1986-01-01

An experimental investigation of two dimensional blade vortex interaction was held at NASA Langley Research Center. The first phase was a flow visualization study to document the approach process of a two dimensional vortex as it encountered a loaded blade model. To accomplish the flow visualization study, a method for generating two dimensional vortex filaments was required. The numerical study used to define a new vortex generation process and the use of this process in the flow visualization study were documented. Additionally, photographic techniques and data analysis methods used in the flow visualization study are examined.

Cosmic ray radiography of the damaged cores of the Fukushima reactors

DOE PAGES

Borozdin, Konstantin; Greene, Steven; Lukić, Zarija; ...

2012-10-11

The passage of muons through matter is dominated by the Coulomb interaction with electrons and nuclei. The interaction with the electrons leads to continuous energy loss and stopping of the muons. The interaction with nuclei leads to angle “diffusion.” Two muon-imaging methods that use flux attenuation and multiple Coulomb scattering of cosmic-ray muons are being studied as tools for diagnosing the damaged cores of the Fukushima reactors. Here, we compare these two methods. We conclude that the scattering method can provide detailed information about the core. Lastly, attenuation has low contrast and little sensitivity to the core.

A comparison of estimators from self-controlled case series, case-crossover design, and sequence symmetry analysis for pharmacoepidemiological studies.

PubMed

Takeuchi, Yoshinori; Shinozaki, Tomohiro; Matsuyama, Yutaka

2018-01-08

Despite the frequent use of self-controlled methods in pharmacoepidemiological studies, the factors that may bias the estimates from these methods have not been adequately compared in real-world settings. Here, we comparatively examined the impact of a time-varying confounder and its interactions with time-invariant confounders, time trends in exposures and events, restrictions, and misspecification of risk period durations on the estimators from three self-controlled methods. This study analyzed self-controlled case series (SCCS), case-crossover (CCO) design, and sequence symmetry analysis (SSA) using simulated and actual electronic medical records datasets. We evaluated the performance of the three self-controlled methods in simulated cohorts for the following scenarios: 1) time-invariant confounding with interactions between the confounders, 2) time-invariant and time-varying confounding without interactions, 3) time-invariant and time-varying confounding with interactions among the confounders, 4) time trends in exposures and events, 5) restricted follow-up time based on event occurrence, and 6) patient restriction based on event history. The sensitivity of the estimators to misspecified risk period durations was also evaluated. As a case study, we applied these methods to evaluate the risk of macrolides on liver injury using electronic medical records. In the simulation analysis, time-varying confounding produced bias in the SCCS and CCO design estimates, which aggravated in the presence of interactions between the time-invariant and time-varying confounders. The SCCS estimates were biased by time trends in both exposures and events. Erroneously short risk periods introduced bias to the CCO design estimate, whereas erroneously long risk periods introduced bias to the estimates of all three methods. Restricting the follow-up time led to severe bias in the SSA estimates. The SCCS estimates were sensitive to patient restriction. The case study showed that although macrolide use was significantly associated with increased liver injury occurrence in all methods, the value of the estimates varied. The estimations of the three self-controlled methods depended on various underlying assumptions, and the violation of these assumptions may cause non-negligible bias in the resulting estimates. Pharmacoepidemiologists should select the appropriate self-controlled method based on how well the relevant key assumptions are satisfied with respect to the available data.

Predicting Protein-Protein Interactions by Combing Various Sequence-Derived.

PubMed

Zhao, Xiao-Wei; Ma, Zhi-Qiang; Yin, Ming-Hao

2011-09-20

Knowledge of protein-protein interactions (PPIs) plays an important role in constructing protein interaction networks and understanding the general machineries of biological systems. In this study, a new method is proposed to predict PPIs using a comprehensive set of 930 features based only on sequence information, these features measure the interactions between residues a certain distant apart in the protein sequences from different aspects. To achieve better performance, the principal component analysis (PCA) is first employed to obtain an optimized feature subset. Then, the resulting 67-dimensional feature vectors are fed to Support Vector Machine (SVM). Experimental results on Drosophila melanogaster and Helicobater pylori datasets show that our method is very promising to predict PPIs and may at least be a useful supplement tool to existing methods.

Using the Q-Connectivity Method to Study Frequency of Interaction with Multiple Peer Triads: Do Preschoolers' Peer Group Interactions at School Relate to Academic Skills?

ERIC Educational Resources Information Center

Hanish, Laura D.; Barcelo, Helene; Martin, Carol Lynn; Fabes, Richard A.; Holmwall, Jennifer; Palermo, Francisco

2007-01-01

How, when, and under what conditions do peer interactions contribute to variations in developmental trajectories along dimensions that are important to children's well-being? These compelling and fundamental questions have piqued the interest of developmental scientists and led to studies of the ways in which peers socialize and affect such…

Flow Cytometric Analysis of Bimolecular Fluorescence Complementation: A High Throughput Quantitative Method to Study Protein-protein Interaction

PubMed Central

Wang, Li; Carnegie, Graeme K.

2013-01-01

Among methods to study protein-protein interaction inside cells, Bimolecular Fluorescence Complementation (BiFC) is relatively simple and sensitive. BiFC is based on the production of fluorescence using two non-fluorescent fragments of a fluorescent protein (Venus, a Yellow Fluorescent Protein variant, is used here). Non-fluorescent Venus fragments (VN and VC) are fused to two interacting proteins (in this case, AKAP-Lbc and PDE4D3), yielding fluorescence due to VN-AKAP-Lbc-VC-PDE4D3 interaction and the formation of a functional fluorescent protein inside cells. BiFC provides information on the subcellular localization of protein complexes and the strength of protein interactions based on fluorescence intensity. However, BiFC analysis using microscopy to quantify the strength of protein-protein interaction is time-consuming and somewhat subjective due to heterogeneity in protein expression and interaction. By coupling flow cytometric analysis with BiFC methodology, the fluorescent BiFC protein-protein interaction signal can be accurately measured for a large quantity of cells in a short time. Here, we demonstrate an application of this methodology to map regions in PDE4D3 that are required for the interaction with AKAP-Lbc. This high throughput methodology can be applied to screening factors that regulate protein-protein interaction. PMID:23979513

Flow cytometric analysis of bimolecular fluorescence complementation: a high throughput quantitative method to study protein-protein interaction.

PubMed

Wang, Li; Carnegie, Graeme K

2013-08-15

Among methods to study protein-protein interaction inside cells, Bimolecular Fluorescence Complementation (BiFC) is relatively simple and sensitive. BiFC is based on the production of fluorescence using two non-fluorescent fragments of a fluorescent protein (Venus, a Yellow Fluorescent Protein variant, is used here). Non-fluorescent Venus fragments (VN and VC) are fused to two interacting proteins (in this case, AKAP-Lbc and PDE4D3), yielding fluorescence due to VN-AKAP-Lbc-VC-PDE4D3 interaction and the formation of a functional fluorescent protein inside cells. BiFC provides information on the subcellular localization of protein complexes and the strength of protein interactions based on fluorescence intensity. However, BiFC analysis using microscopy to quantify the strength of protein-protein interaction is time-consuming and somewhat subjective due to heterogeneity in protein expression and interaction. By coupling flow cytometric analysis with BiFC methodology, the fluorescent BiFC protein-protein interaction signal can be accurately measured for a large quantity of cells in a short time. Here, we demonstrate an application of this methodology to map regions in PDE4D3 that are required for the interaction with AKAP-Lbc. This high throughput methodology can be applied to screening factors that regulate protein-protein interaction.

A facile fluorescent "turn-off" method for sensing paraquat based on pyranine-paraquat interaction

NASA Astrophysics Data System (ADS)

Zhao, Zuzhi; Zhang, Fengwei; Zhang, Zipin

2018-06-01

Development of a technically simple yet effective method for paraquat (PQ) detection is of great importance due to its high clinical and environmental relevance. In this study, we developed a pyranine-based fluorescent "turn-off" method for PQ sensing based on pyranine-PQ interaction. We investigated the dependence of analytical performance of this method on the experimental conditions, such as the ion strength, medium pH, and so on. Under the optimized conditions, the method is sensitive and selective, and could be used for PQ detection in real-world sample. This study essentially provides a readily accessible fluorescent system for PQ sensing which is cheap, robust, and technically simple, and it is envisaged to find more interesting clinical and environmental applications.

The role of drug profiles as similarity metrics: applications to repurposing, adverse effects detection and drug-drug interactions.

PubMed

Vilar, Santiago; Hripcsak, George

2017-07-01

Explosion of the availability of big data sources along with the development in computational methods provides a useful framework to study drugs' actions, such as interactions with pharmacological targets and off-targets. Databases related to protein interactions, adverse effects and genomic profiles are available to be used for the construction of computational models. In this article, we focus on the description of biological profiles for drugs that can be used as a system to compare similarity and create methods to predict and analyze drugs' actions. We highlight profiles constructed with different biological data, such as target-protein interactions, gene expression measurements, adverse effects and disease profiles. We focus on the discovery of new targets or pathways for drugs already in the pharmaceutical market, also called drug repurposing, in the interaction with off-targets responsible for adverse reactions and in drug-drug interaction analysis. The current and future applications, strengths and challenges facing all these methods are also discussed. Biological profiles or signatures are an important source of data generation to deeply analyze biological actions with important implications in drug-related studies. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Development of Support Service for Prevention and Recovery from Dementia and Science of Lethe

NASA Astrophysics Data System (ADS)

Otake, Mihoko

Purpose of this study is to explore service design method through the development of support service for prevention and recovery from dementia towards science of lethe. We designed and implemented conversation support service via coimagination method based on multiscale service design method, both were proposed by the author. Multiscale service model consists of tool, event, human, network, style and rule. Service elements at different scales are developed according to the model. Interactive conversation supported by coimagination method activates cognitive functions so as to prevent progress of dementia. This paper proposes theoretical bases for science of lethe. Firstly, relationship among coimagination method and three cognitive functions including division of attention, planning, episodic memory which decline at mild cognitive imparement. Secondly, thought state transition model during conversation which describes cognitive enhancement via interactive communication. Thirdly, Set Theoretical Measure of Interaction is proposed for evaluating effectiveness of conversation to cognitive enhancement. Simulation result suggests that the ideas which cannot be explored by each speaker are explored during interactive conversation. Finally, coimagination method compared with reminiscence therapy and its possibility for collaboration is discussed.

Co-evolutionary Analysis of Domains in Interacting Proteins Reveals Insights into Domain–Domain Interactions Mediating Protein–Protein Interactions

PubMed Central

Jothi, Raja; Cherukuri, Praveen F.; Tasneem, Asba; Przytycka, Teresa M.

2006-01-01

Recent advances in functional genomics have helped generate large-scale high-throughput protein interaction data. Such networks, though extremely valuable towards molecular level understanding of cells, do not provide any direct information about the regions (domains) in the proteins that mediate the interaction. Here, we performed co-evolutionary analysis of domains in interacting proteins in order to understand the degree of co-evolution of interacting and non-interacting domains. Using a combination of sequence and structural analysis, we analyzed protein–protein interactions in F1-ATPase, Sec23p/Sec24p, DNA-directed RNA polymerase and nuclear pore complexes, and found that interacting domain pair(s) for a given interaction exhibits higher level of co-evolution than the noninteracting domain pairs. Motivated by this finding, we developed a computational method to test the generality of the observed trend, and to predict large-scale domain–domain interactions. Given a protein–protein interaction, the proposed method predicts the domain pair(s) that is most likely to mediate the protein interaction. We applied this method on the yeast interactome to predict domain–domain interactions, and used known domain–domain interactions found in PDB crystal structures to validate our predictions. Our results show that the prediction accuracy of the proposed method is statistically significant. Comparison of our prediction results with those from two other methods reveals that only a fraction of predictions are shared by all the three methods, indicating that the proposed method can detect known interactions missed by other methods. We believe that the proposed method can be used with other methods to help identify previously unrecognized domain–domain interactions on a genome scale, and could potentially help reduce the search space for identifying interaction sites. PMID:16949097

Multi-Dimensional Analysis of Dynamic Human Information Interaction

ERIC Educational Resources Information Center

Park, Minsoo

2013-01-01

Introduction: This study aims to understand the interactions of perception, effort, emotion, time and performance during the performance of multiple information tasks using Web information technologies. Method: Twenty volunteers from a university participated in this study. Questionnaires were used to obtain general background information and…

Patterns of Communicative Interaction between a Child with Severe Speech and Physical Impairments and Her Caregiver during a Mealtime Activity

ERIC Educational Resources Information Center

Ferm, Ulrika; Ahlsen, Elisabeth; Bjorck-Akesson, Eva

2012-01-01

Background: Interaction between caregivers and children with severe impairments is closely related to the demands of daily activities. This study examines the relationship between interaction and the routine mealtime activity at home. Method: Patterns of interaction between a child (aged 6 years and 6 months) with severe speech and physical…

Markov Logic Networks in the Analysis of Genetic Data

PubMed Central

Sakhanenko, Nikita A.

2010-01-01

Abstract Complex, non-additive genetic interactions are common and can be critical in determining phenotypes. Genome-wide association studies (GWAS) and similar statistical studies of linkage data, however, assume additive models of gene interactions in looking for genotype-phenotype associations. These statistical methods view the compound effects of multiple genes on a phenotype as a sum of influences of each gene and often miss a substantial part of the heritable effect. Such methods do not use any biological knowledge about underlying mechanisms. Modeling approaches from the artificial intelligence (AI) field that incorporate deterministic knowledge into models to perform statistical analysis can be applied to include prior knowledge in genetic analysis. We chose to use the most general such approach, Markov Logic Networks (MLNs), for combining deterministic knowledge with statistical analysis. Using simple, logistic regression-type MLNs we can replicate the results of traditional statistical methods, but we also show that we are able to go beyond finding independent markers linked to a phenotype by using joint inference without an independence assumption. The method is applied to genetic data on yeast sporulation, a complex phenotype with gene interactions. In addition to detecting all of the previously identified loci associated with sporulation, our method identifies four loci with smaller effects. Since their effect on sporulation is small, these four loci were not detected with methods that do not account for dependence between markers due to gene interactions. We show how gene interactions can be detected using more complex models, which can be used as a general framework for incorporating systems biology with genetics. PMID:20958249

A theoretical probe on the non-covalent interactions of sulfadoxine drug with pi-acceptors

NASA Astrophysics Data System (ADS)

Sandhiya, L.; Senthilkumar, K.

2014-09-01

A detailed analysis of the interaction between an antimalarial drug sulfadoxine and four pi-acceptors, tetrachloro-catechol, picric acid, chloranil, and 2,3-dichloro-5,6-dicyano-1,4-benzoquinone is presented in this study. The interaction of the amine, amide, methoxy, Csbnd H groups and π electron density of the drug molecule with the acceptors are studied using DFT method at M06-2X level of theory with 6-31G(d,p) basis set. The interaction energy of the complexes is calculated using M06-2X, M06-HF, B3LYP-D and MP2 methods with 6-31G(d,p) basis set. The role of weak interactions on the formation and stability of the complexes is discussed in detail. The two aromatic platforms of sulfadoxine play a major role in determining the stability of the complexes. The electron density difference maps have been plotted for the most stable drug interacting complexes to understand the changes in electron density delocalization upon the complex formation. The nature of the non-covalent interaction has been addressed from NCI plot. The infrared spectra calculated at M06-2X/6-31G(d,p) level of theory is used to characterize the most stable complexes. The SDOX-pi acceptor complexation leads to characteristic changes in the NMR spectra. The 13C, 1H, 17O and 15N NMR chemical shifts have been calculated using GIAO method at M06-2X/6-311+G(d,p)//M06-2X/6-31G(d,p) level of theory. The results obtained from this study confirm the role of non-covalent interactions on the function of the sulfadoxine drug.

Use of interactive multimedia disks in the applied environmental sciences program at the Oregon Institute of Technology

NASA Astrophysics Data System (ADS)

Jones, Charles R.

Although a number of studies have been performed regarding the use of interactive multimedia disks in education, none were found which investigated their effect on either retention or recruitment for universities. The purpose of this case study was to gather information regarding student and teacher perceptions on the use of interactive multimedia disks and their effect on retention and recruitment. The primary source of data for this case study was student and teacher interviews. A purposive sample of students taking courses using the interactive multimedia disks in course at the Oregon Institute of Technology and at two Oregon high schools was chosen for the case study. Major findings of the case study were as follows: (1) Students interviewed in this case study perceived the interactive multimedia disk-based instructional method to be equally as effective as the lecture method. (2) Time flexibility in class scheduling was slightly more beneficial to female students than male students and the lack of instructor-led classroom interaction was more of a problem for female students than male students. (3) There was no difference in the perceptions of the college students and the high school students regarding the benefits and drawbacks of the interactive multimedia disk-based classes. (4) The flexible class scheduling made possible through the use of interactive multimedia disks influences some Oregon Institute of Technology students to stay and complete their degree programs. (5) There is some potential for interactive multimedia disk-based courses to be a recruiting tool. However, there is no evidence that it has been a successful recruiting tool for the Oregon Institute of Technology yet.

The genetic interacting landscape of 63 candidate genes in Major Depressive Disorder: an explorative study.

PubMed

Lekman, Magnus; Hössjer, Ola; Andrews, Peter; Källberg, Henrik; Uvehag, Daniel; Charney, Dennis; Manji, Husseini; Rush, John A; McMahon, Francis J; Moore, Jason H; Kockum, Ingrid

2014-01-01

Genetic contributions to major depressive disorder (MDD) are thought to result from multiple genes interacting with each other. Different procedures have been proposed to detect such interactions. Which approach is best for explaining the risk of developing disease is unclear. This study sought to elucidate the genetic interaction landscape in candidate genes for MDD by conducting a SNP-SNP interaction analysis using an exhaustive search through 3,704 SNP-markers in 1,732 cases and 1,783 controls provided from the GAIN MDD study. We used three different methods to detect interactions, two logistic regressions models (multiplicative and additive) and one data mining and machine learning (MDR) approach. Although none of the interaction survived correction for multiple comparisons, the results provide important information for future genetic interaction studies in complex disorders. Among the 0.5% most significant observations, none had been reported previously for risk to MDD. Within this group of interactions, less than 0.03% would have been detectable based on main effect approach or an a priori algorithm. We evaluated correlations among the three different models and conclude that all three algorithms detected the same interactions to a low degree. Although the top interactions had a surprisingly large effect size for MDD (e.g. additive dominant model Puncorrected = 9.10E-9 with attributable proportion (AP) value = 0.58 and multiplicative recessive model with Puncorrected = 6.95E-5 with odds ratio (OR estimated from β3) value = 4.99) the area under the curve (AUC) estimates were low (< 0.54). Moreover, the population attributable fraction (PAF) estimates were also low (< 0.15). We conclude that the top interactions on their own did not explain much of the genetic variance of MDD. The different statistical interaction methods we used in the present study did not identify the same pairs of interacting markers. Genetic interaction studies may uncover previously unsuspected effects that could provide novel insights into MDD risk, but much larger sample sizes are needed before this strategy can be powerfully applied.

Kindergarten Children's Interactions with Touchscreen Mathematics Virtual Manipulatives: An Innovative Mixed Methods Analysis

ERIC Educational Resources Information Center

Tucker, Stephen I.; Lommatsch, Christina W.; Moyer-Packenham, Patricia S.; Anderson-Pence, Katie L.; Symanzik, Jürgen

2017-01-01

The purpose of this study was to examine patterns of mathematical practices evident during children's interactions with touchscreen mathematics virtual manipulatives. Researchers analyzed 33 Kindergarten children's interactions during activities involving apps featuring mathematical content of early number sense or quantity in base ten, recorded…

What Type of Lectures Students Want? - A Reaction Evaluation of Dental Students

PubMed Central

Roopa, Srinivasan; Geetha M, Bagavad; Rani, Anitha; Chacko, Thomas

2013-01-01

Introduction: An one hour didactic lecture is the common method of teaching in dental colleges in India. Lengthy lectures are boring and students are passive recipients of the information. Interactive lectures are suggested as a means of overcoming the disadvantages of regular lectures. Aims: The present study was conducted to pilot various methods of making lectures interactive and to find the students’ reactions to interactive lectures as compared to regular lectures. Material and Methods: An entire batch of first year dental students (n = 78) was exposed to both interactive and regular lectures for the cardiovascular system in physiology. Among the total number of 12 lectures, alternate lectures were conducted in an interactive style. At the end of the 12 lecture series, students’ opinions were obtained using a structured feedback evaluation questionnaire, consisting of five statements, on a five point Likert scale. Statistical Analysis was done using SPSS software, version 15. Results: Interactive lectures were found to be more useful than regular lectures by 92% of the students. Significantly more number of students agreed or strongly agreed that interactive lectures kept them attentive, created interest, overcame monotony, motivated them for self learning and provided well defined learning than regular lectures. Among the different techniques which were used, the students preferred use of video clippings (58.1%), followed by each-one-teach-one. Results of the present study support the use of interactive lectures for ensuring increased interest and attention of students during lectures. Conclusion: Interactive lectures were more accepted and considered to be more useful than regular lectures by the students. PMID:24298487

A Mobile Outdoor Augmented Reality Method Combining Deep Learning Object Detection and Spatial Relationships for Geovisualization

PubMed Central

Rao, Jinmeng; Qiao, Yanjun; Ren, Fu; Wang, Junxing; Du, Qingyun

2017-01-01

The purpose of this study was to develop a robust, fast and markerless mobile augmented reality method for registration, geovisualization and interaction in uncontrolled outdoor environments. We propose a lightweight deep-learning-based object detection approach for mobile or embedded devices; the vision-based detection results of this approach are combined with spatial relationships by means of the host device’s built-in Global Positioning System receiver, Inertial Measurement Unit and magnetometer. Virtual objects generated based on geospatial information are precisely registered in the real world, and an interaction method based on touch gestures is implemented. The entire method is independent of the network to ensure robustness to poor signal conditions. A prototype system was developed and tested on the Wuhan University campus to evaluate the method and validate its results. The findings demonstrate that our method achieves a high detection accuracy, stable geovisualization results and interaction. PMID:28837096

A Mobile Outdoor Augmented Reality Method Combining Deep Learning Object Detection and Spatial Relationships for Geovisualization.

PubMed

Rao, Jinmeng; Qiao, Yanjun; Ren, Fu; Wang, Junxing; Du, Qingyun

2017-08-24

The purpose of this study was to develop a robust, fast and markerless mobile augmented reality method for registration, geovisualization and interaction in uncontrolled outdoor environments. We propose a lightweight deep-learning-based object detection approach for mobile or embedded devices; the vision-based detection results of this approach are combined with spatial relationships by means of the host device's built-in Global Positioning System receiver, Inertial Measurement Unit and magnetometer. Virtual objects generated based on geospatial information are precisely registered in the real world, and an interaction method based on touch gestures is implemented. The entire method is independent of the network to ensure robustness to poor signal conditions. A prototype system was developed and tested on the Wuhan University campus to evaluate the method and validate its results. The findings demonstrate that our method achieves a high detection accuracy, stable geovisualization results and interaction.

Identification of Histone Deacetylase (HDAC) as a drug target against MRSA via interolog method of protein-protein interaction prediction.

PubMed

Uddin, Reaz; Tariq, Syeda Sumayya; Azam, Syed Sikander; Wadood, Abdul; Moin, Syed Tarique

2017-08-30

Patently, Protein-Protein Interactions (PPIs) lie at the core of significant biological functions and make the foundation of host-pathogen relationships. Hence, the current study is aimed to use computational biology techniques to predict host-pathogen Protein-Protein Interactions (HP-PPIs) between MRSA and Humans as potential drug targets ultimately proposing new possible inhibitors against them. As a matter of fact this study is based on the Interolog method which implies that homologous proteins retain their ability to interact. A distant homolog approach based on Interolog method was employed to speculate MRSA protein homologs in Humans using PSI-BLAST. In addition the protein interaction partners of these homologs as listed in Database of Interacting Proteins (DIP) were predicted to interact with MRSA as well. Moreover, a direct approach using BLAST was also applied so as to attain further confidence in the strategy. Consequently, the common HP-PPIs predicted by both approaches are suggested as potential drug targets (22%) whereas, the unique HP-PPIs estimated only through distant homolog approach are presented as novel drug targets (12%). Furthermore, the most repeated entry in our results was found to be MRSA Histone Deacetylase (HDAC) which was then modeled using SWISS-MODEL. Eventually, small molecules from ZINC, selected randomly, were docked against HDAC using Auto Dock and are suggested as potential binders (inhibitors) based on their energetic profiles. Thus the current study provides basis for further in-depth analysis of such data which not only include MRSA but other deadly pathogens as well. Copyright © 2017 Elsevier B.V. All rights reserved.

Perspectives on Using Video Recordings in Conversation Analytical Studies on Learning in Interaction

ERIC Educational Resources Information Center

Rusk, Fredrik; Pörn, Michaela; Sahlström, Fritjof; Slotte-Lüttge, Anna

2015-01-01

Video is currently used in many studies to document the interaction in conversation analytical (CA) studies on learning. The discussion on the method used in these studies has primarily focused on the analysis or the data construction, whereas the relation between data construction and analysis is rarely brought to attention. The aim of this…

Detection and characterization of nonspecific, sparsely-populated binding modes in the early stages of complexation

PubMed Central

Cardone, A.; Bornstein, A.; Pant, H. C.; Brady, M.; Sriram, R.; Hassan, S. A.

2015-01-01

A method is proposed to study protein-ligand binding in a system governed by specific and non-specific interactions. Strong associations lead to narrow distributions in the proteins configuration space; weak and ultra-weak associations lead instead to broader distributions, a manifestation of non-specific, sparsely-populated binding modes with multiple interfaces. The method is based on the notion that a discrete set of preferential first-encounter modes are metastable states from which stable (pre-relaxation) complexes at equilibrium evolve. The method can be used to explore alternative pathways of complexation with statistical significance and can be integrated into a general algorithm to study protein interaction networks. The method is applied to a peptide-protein complex. The peptide adopts several low-population conformers and binds in a variety of modes with a broad range of affinities. The system is thus well suited to analyze general features of binding, including conformational selection, multiplicity of binding modes, and nonspecific interactions, and to illustrate how the method can be applied to study these problems systematically. The equilibrium distributions can be used to generate biasing functions for simulations of multiprotein systems from which bulk thermodynamic quantities can be calculated. PMID:25782918

A dynamical proximity analysis of interacting galaxy pairs

NASA Technical Reports Server (NTRS)

Chatterjee, Tapan K.

1990-01-01

Using the impulsive approximation to study the velocity changes of stars during disk-sphere collisions and a method due to Bottlinger to study the post collision orbits of stars, the formation of various types of interacting galaxies is studied as a function of the distance of closest approach between the two galaxies.

Lutheran School Teachers' Instructional Usage of the Interactive Whiteboard

ERIC Educational Resources Information Center

Powers, Jillian R.

2014-01-01

The purpose of this mixed methods study was twofold. First, the study assessed whether Davis' (1989) Technology Acceptance Model (TAM) was useful in predicting instructional usage of the interactive whiteboard (IWB), as reported by K-8 teachers. Second, the study set out to understand what motivated those teachers to use the IWB for classroom…

Perceived Norms for Interactive Teaching and Their Relationship to Instructional Decision-Making: A Mixed Methods Study

ERIC Educational Resources Information Center

Hora, Matthew T.; Anderson, Craig

2012-01-01

Normative expectations for acceptable behaviors related to undergraduate instruction are known to exist within academic settings. Yet few studies have examined disciplinary variation in norms for interactive teaching, and their relationship to teaching practice, particularly from a cognitive perspective. This study examines these problems using…

Investigating Research Approaches: Classroom-Based Interaction Studies in Physical and Virtual Contexts

ERIC Educational Resources Information Center

Hartwick, Peggy

2018-01-01

This article investigates research approaches used in traditional classroom-based interaction studies for identifying a suitable research method for studies in three-dimensional virtual learning environments (3DVLEs). As opportunities for language learning and teaching in virtual worlds emerge, so too do new research questions. An understanding of…

Microteaching Lesson Study: Mentor Interaction Structure and Its Relation to Elementary Preservice Mathematics Teacher Knowledge Development

ERIC Educational Resources Information Center

Molina, Roxanne V.

2012-01-01

This study investigated Microteaching Lesson Study (MLS) and three possible MLS mentor interaction structures during the debriefing sessions in relation to elementary preservice teacher development of knowledge for teaching. One hundred three elementary preservice teachers enrolled in five different sections of a mathematics methods course at a…

Root–root interactions: extending our perspective to be more inclusive of the range of theories in ecology and agriculture using in-vivo analyses

PubMed Central

Faget, Marc; Nagel, Kerstin A.; Walter, Achim; Herrera, Juan M.; Jahnke, Siegfried; Schurr, Ulrich; Temperton, Vicky M.

2013-01-01

Background There is a large body of literature on competitive interactions among plants, but many studies have only focused on above-ground interactions and little is known about root–root dynamics between interacting plants. The perspective on possible mechanisms that explain the outcome of root–root interactions has recently been extended to include non-resource-driven mechanisms (as well as resource-driven mechanisms) of root competition and positive interactions such as facilitation. These approaches have often suffered from being static, partly due to the lack of appropriate methodologies for in-situ non-destructive root characterization. Scope Recent studies show that interactive effects of plant neighbourhood interactions follow non-linear and non-additive paths that are hard to explain. Common outcomes such as accumulation of roots mainly in the topsoil cannot be explained solely by competition theory but require a more inclusive theoretical, as well as an improved methodological framework. This will include the question of whether we can apply the same conceptual framework to crop versus natural species. Conclusions The development of non-invasive methods to dynamically study root–root interactions in vivo will provide the necessary tools to study a more inclusive conceptual framework for root–root interactions. By following the dynamics of root–root interactions through time in a whole range of scenarios and systems, using a wide variety of non-invasive methods, (such as fluorescent protein which now allows us to separately identify the roots of several individuals within soil), we will be much better equipped to answer some of the key questions in root physiology, ecology and agronomy. PMID:23378521

Exchange coupling and magnetic anisotropy of exchanged-biased quantum tunnelling single-molecule magnet Ni3Mn2 complexes using theoretical methods based on Density Functional Theory.

PubMed

Gómez-Coca, Silvia; Ruiz, Eliseo

2012-03-07

The magnetic properties of a new family of single-molecule magnet Ni(3)Mn(2) complexes were studied using theoretical methods based on Density Functional Theory (DFT). The first part of this study is devoted to analysing the exchange coupling constants, focusing on the intramolecular as well as the intermolecular interactions. The calculated intramolecular J values were in excellent agreement with the experimental data, which show that all the couplings are ferromagnetic, leading to an S = 7 ground state. The intermolecular interactions were investigated because the two complexes studied do not show tunnelling at zero magnetic field. Usually, this exchange-biased quantum tunnelling is attributed to the presence of intermolecular interactions calculated with the help of theoretical methods. The results indicate the presence of weak intermolecular antiferromagnetic couplings that cannot explain the ferromagnetic value found experimentally for one of the systems. In the second part, the goal is to analyse magnetic anisotropy through the calculation of the zero-field splitting parameters (D and E), using DFT methods including the spin-orbit effect.

An improved method for pancreas segmentation using SLIC and interactive region merging

NASA Astrophysics Data System (ADS)

Zhang, Liyuan; Yang, Huamin; Shi, Weili; Miao, Yu; Li, Qingliang; He, Fei; He, Wei; Li, Yanfang; Zhang, Huimao; Mori, Kensaku; Jiang, Zhengang

2017-03-01

Considering the weak edges in pancreas segmentation, this paper proposes a new solution which integrates more features of CT images by combining SLIC superpixels and interactive region merging. In the proposed method, Mahalanobis distance is first utilized in SLIC method to generate better superpixel images. By extracting five texture features and one gray feature, the similarity measure between two superpixels becomes more reliable in interactive region merging. Furthermore, object edge blocks are accurately addressed by re-segmentation merging process. Applying the proposed method to four cases of abdominal CT images, we segment pancreatic tissues to verify the feasibility and effectiveness. The experimental results show that the proposed method can make segmentation accuracy increase to 92% on average. This study will boost the application process of pancreas segmentation for computer-aided diagnosis system.

Interactive visualization of public health indicators to support policymaking: An exploratory study

PubMed Central

Zakkar, Moutasem; Sedig, Kamran

2017-01-01

Purpose The purpose of this study is to examine the use of interactive visualizations to represent data/information related to social determinants of health and public health indicators, and to investigate the benefits of such visualizations for health policymaking. Methods: The study developed a prototype for an online interactive visualization tool that represents the social determinants of health. The study participants explored and used the tool. The tool was evaluated using the informal user experience evaluation method. This method involves the prospective users of a tool to use and play with it and their feedback to be collected through interviews. Results: Using visualizations to represent and interact with health indicators has advantages over traditional representation techniques that do not allow users to interact with the information. Communicating healthcare indicators to policymakers is a complex task because of the complexity of the indicators, diversity of audiences, and different audience needs. This complexity can lead to information misinterpretation, which occurs when users of the health data ignore or do not know why, where, and how the data has been produced, or where and how it can be used. Conclusions: Public health policymaking is a complex process, and data is only one element among others needed in this complex process. Researchers and healthcare organizations should conduct a strategic evaluation to assess the usability of interactive visualizations and decision support tools before investing in these tools. Such evaluation should take into consideration the cost, ease of use, learnability, and efficiency of those tools, and the factors that influence policymaking. PMID:29026455

Patterns of Relating between Mothers and Preschool-Aged Children Using the Marschak Interaction Method Rating System

ERIC Educational Resources Information Center

Martin, Erin E.; Snow, Marilyn S.; Sullivan, Kathleen

2008-01-01

This study assesses the relationship of patterns of relating between mothers and their preschool-aged children. Thirty-one families were used, and the mother and child participated in the Marschak Interaction Method Rating System (MIM-RS). Mothers also completed the Demographic Data Questionnaire. Correlations based upon the MIM-RS for mothers and…

Handling qualities of large flexible control-configured aircraft

NASA Technical Reports Server (NTRS)

Swaim, R. L.

1979-01-01

The approach to an analytical study of flexible airplane longitudinal handling qualities was to parametrically vary the natural frequencies of two symmetric elastic modes to induce mode interactions with the rigid body dynamics. Since the structure of the pilot model was unknown for such dynamic interactions, the optimal control pilot modeling method is being applied and used in conjunction with pilot rating method.

Evaluation of Two Methods for Modeling Measurement Errors When Testing Interaction Effects with Observed Composite Scores

ERIC Educational Resources Information Center

Hsiao, Yu-Yu; Kwok, Oi-Man; Lai, Mark H. C.

2018-01-01

Path models with observed composites based on multiple items (e.g., mean or sum score of the items) are commonly used to test interaction effects. Under this practice, researchers generally assume that the observed composites are measured without errors. In this study, we reviewed and evaluated two alternative methods within the structural…

Study of structure defect interactions in aluminum by the acoustic method. [internal friction in pure aluminum

NASA Technical Reports Server (NTRS)

Nicolaescu, I. I.

1974-01-01

Using echo pulse and resonance rod methods, internal friction in pure aluminum was studied as a function of frequency, hardening temperature, time (internal friction relaxation) and impurity content. These studies led to the conclusion that internal friction in these materials depends strongly on dislocation structure and on elastic interactions between structure defects. It was found experimentally that internal friction relaxation depends on the cooling rate and on the impurity content. Some parameters of the dislocation structure and of the diffusion process were determined. It is shown that the dislocated dependence of internal friction can be used as a method of nondestructive testing of the impurity content of high-purity materials.

A convenient method for synthesis of glyconanoparticles for colorimetric measuring carbohydrate-protein interactions

PubMed Central

Chuang, Yen-Jun; Zhou, Xichun; Pan, Zhengwei; Turchi, Craig

2009-01-01

Carbohydrate functionalized nanoparticles, i.e., the glyconanoparticles, have wide application ranging from studies of carbohydrate-protein interactions, in vivo cell imaging, biolabeling, etc. Currently reported methods for preparation of glyconanoaprticles require multi-step modifications of carbohydrates moieties to conjugate to nanoparticle surface. However, the required synthetic manipulations are difficult and time consuming. We report herewith a simple and versatile method for preparing glyconanoparticles. This method is based on the utilization of clean and convenient microwave irradiation energy for one-step, site-specific conjugation of unmodified carbohydrates onto hydrazide-functionalized Au nanoparticles. A colorimetric assay that utilizes the ensemble of gold glyconanoparticles and Concanavalin A (ConA) was also presented. This feasible assay system was developed to analyze multivalent interactions and to determine the dissociation constant (Kd) for five kind of Au glyconanoparticles with lectin. Surface plasmon changes of the Au glyconanparticles as a function of lectin-carbohydrate interactions were measured and the dissociation constants were determined based on non-linear curve fitting. The strength of the interaction of carbohydrates with ConA was found to be as follows: Maltose > Mannose > Glucose > Lactose > MAN5. PMID:19698698

Prediction of cancer proteins by integrating protein interaction, domain frequency, and domain interaction data using machine learning algorithms.

PubMed

Huang, Chien-Hung; Peng, Huai-Shun; Ng, Ka-Lok

2015-01-01

Many proteins are known to be associated with cancer diseases. It is quite often that their precise functional role in disease pathogenesis remains unclear. A strategy to gain a better understanding of the function of these proteins is to make use of a combination of different aspects of proteomics data types. In this study, we extended Aragues's method by employing the protein-protein interaction (PPI) data, domain-domain interaction (DDI) data, weighted domain frequency score (DFS), and cancer linker degree (CLD) data to predict cancer proteins. Performances were benchmarked based on three kinds of experiments as follows: (I) using individual algorithm, (II) combining algorithms, and (III) combining the same classification types of algorithms. When compared with Aragues's method, our proposed methods, that is, machine learning algorithm and voting with the majority, are significantly superior in all seven performance measures. We demonstrated the accuracy of the proposed method on two independent datasets. The best algorithm can achieve a hit ratio of 89.4% and 72.8% for lung cancer dataset and lung cancer microarray study, respectively. It is anticipated that the current research could help understand disease mechanisms and diagnosis.

Prediction of Cancer Proteins by Integrating Protein Interaction, Domain Frequency, and Domain Interaction Data Using Machine Learning Algorithms

PubMed Central

2015-01-01

Many proteins are known to be associated with cancer diseases. It is quite often that their precise functional role in disease pathogenesis remains unclear. A strategy to gain a better understanding of the function of these proteins is to make use of a combination of different aspects of proteomics data types. In this study, we extended Aragues's method by employing the protein-protein interaction (PPI) data, domain-domain interaction (DDI) data, weighted domain frequency score (DFS), and cancer linker degree (CLD) data to predict cancer proteins. Performances were benchmarked based on three kinds of experiments as follows: (I) using individual algorithm, (II) combining algorithms, and (III) combining the same classification types of algorithms. When compared with Aragues's method, our proposed methods, that is, machine learning algorithm and voting with the majority, are significantly superior in all seven performance measures. We demonstrated the accuracy of the proposed method on two independent datasets. The best algorithm can achieve a hit ratio of 89.4% and 72.8% for lung cancer dataset and lung cancer microarray study, respectively. It is anticipated that the current research could help understand disease mechanisms and diagnosis. PMID:25866773

Content-related interactions and methods of reasoning within self-initiated organic chemistry study groups

NASA Astrophysics Data System (ADS)

Christian, Karen Jeanne

2011-12-01

Students often use study groups to prepare for class or exams; yet to date, we know very little about how these groups actually function. This study looked at the ways in which undergraduate organic chemistry students prepared for exams through self-initiated study groups. We sought to characterize the methods of social regulation, levels of content processing, and types of reasoning processes used by students within their groups. Our analysis showed that groups engaged in predominantly three types of interactions when discussing chemistry content: co-construction, teaching, and tutoring. Although each group engaged in each of these types of interactions at some point, their prevalence varied between groups and group members. Our analysis suggests that the types of interactions that were most common depended on the relative content knowledge of the group members as well as on the difficulty of the tasks in which they were engaged. Additionally, we were interested in characterizing the reasoning methods used by students within their study groups. We found that students used a combination of three content-relevant methods of reasoning: model-based reasoning, case-based reasoning, or rule-based reasoning, in conjunction with one chemically-irrelevant method of reasoning: symbol-based reasoning. The most common way for groups to reason was to use rules, whereas the least common way was for students to work from a model. In general, student reasoning correlated strongly to the subject matter to which students were paying attention, and was only weakly related to student interactions. Overall, results from this study may help instructors to construct appropriate tasks to guide what and how students study outside of the classroom. We found that students had a decidedly strategic approach in their study groups, relying heavily on material provided by their instructors, and using the reasoning strategies that resulted in the lowest levels of content processing. We suggest that instructors create more opportunities for students to explore model-based reasoning, and to create opportunities for students to be able to co-construct in a collaborative manner within the context of their organic chemistry course.

[Early interaction is a prerequisite for favorable psychic development].

PubMed

Pesonen, Anu-Katriina

2010-01-01

Empirical studies on the parent-baby interaction have greatly influenced our insight into the child's psychological development. Initial stages of the research attempted to reveal features in the mother's action that would predict the child's favorable development. Since then, also fathers and the child's development in a more broad sense have been studied. The most prominent progress has taken place in microanalytical methods for these interactions. The research has increased our knowledge of the baby's interactive capabilities and the significance of successful interactive events for the child's development, laying the basis for various interventions related to parenthood.

Strategy and model building in the fourth dimension: a null model for genotype x age interaction as a Gaussian stationary stochastic process.

PubMed

Diego, Vincent P; Almasy, Laura; Dyer, Thomas D; Soler, Júlia M P; Blangero, John

2003-12-31

Using univariate and multivariate variance components linkage analysis methods, we studied possible genotype x age interaction in cardiovascular phenotypes related to the aging process from the Framingham Heart Study. We found evidence for genotype x age interaction for fasting glucose and systolic blood pressure. There is polygenic genotype x age interaction for fasting glucose and systolic blood pressure and quantitative trait locus x age interaction for a linkage signal for systolic blood pressure phenotypes located on chromosome 17 at 67 cM.

Modal interactions due to friction in the nonlinear vibration response of the "Harmony" test structure: Experiments and simulations

NASA Astrophysics Data System (ADS)

Claeys, M.; Sinou, J.-J.; Lambelin, J.-P.; Todeschini, R.

2016-08-01

The nonlinear vibration response of an assembly with friction joints - named "Harmony" - is studied both experimentally and numerically. The experimental results exhibit a softening effect and an increase of dissipation with excitation level. Modal interactions due to friction are also evidenced. The numerical methodology proposed groups together well-known structural dynamic methods, including finite elements, substructuring, Harmonic Balance and continuation methods. On the one hand, the application of this methodology proves its capacity to treat a complex system where several friction movements occur at the same time. On the other hand, the main contribution of this paper is the experimental and numerical study of evidence of modal interactions due to friction. The simulation methodology succeeds in reproducing complex form of dynamic behavior such as these modal interactions.

Characteristics of Interactive Learning Environments in Business Management Courses.

ERIC Educational Resources Information Center

Nicastro, Mary L.

This study sought to develop theoretical propositions for the institutional, course, instructor, and student characteristics of the learning environment where interactive learning techniques are used in college-level business courses. Using an interpretive case study method with examination of documents, observations of instructors and students,…

Identification of interfaces involved in weak interactions with application to F-actin-aldolase rafts.

PubMed

Hu, Guiqing; Taylor, Dianne W; Liu, Jun; Taylor, Kenneth A

2018-03-01

Macromolecular interactions occur with widely varying affinities. Strong interactions form well defined interfaces but weak interactions are more dynamic and variable. Weak interactions can collectively lead to large structures such as microvilli via cooperativity and are often the precursors of much stronger interactions, e.g. the initial actin-myosin interaction during muscle contraction. Electron tomography combined with subvolume alignment and classification is an ideal method for the study of weak interactions because a 3-D image is obtained for the individual interactions, which subsequently are characterized collectively. Here we describe a method to characterize heterogeneous F-actin-aldolase interactions in 2-D rafts using electron tomography. By forming separate averages of the two constituents and fitting an atomic structure to each average, together with the alignment information which relates the raw motif to the average, an atomic model of each crosslink is determined and a frequency map of contact residues is computed. The approach should be applicable to any large structure composed of constituents that interact weakly and heterogeneously. Copyright © 2017 Elsevier Inc. All rights reserved.

The Role of Context in the Development of Second Language Interactional Competence: A Comparative Microanalysis of Topic Initiation Practices in the Study Abroad Homestay and the Language Classroom

ERIC Educational Resources Information Center

Van Booven, Christopher D.

2017-01-01

This dissertation research aims to better specify the role of context in the development of second language interactional competence. Drawing on conversation-analytic methods and Wong and Waring's (2010) model of interactional practices, I described and compared the opportunities that two study abroad contexts--the homestay and the language…

Basics for the preparation of quantum dots and their interactions with living cells.

PubMed

Jiang, Xiue; Bai, Jing; Wang, Tiantian

2014-01-01

A study of the interactions between nanoparticles and living cells is invaluable in understanding the nano-biological effect and the mechanism of cellular endocytosis. Here we describe two methods for the preparation of semiconductor quantum dots with different physiochemical properties. Furthermore, we describe how to study the interaction of the two quantum dots with living HeLa cells and red blood cells with confocal microscopy.

The Pseudopod System for Axon-Glia Interactions: Stimulation and Isolation of Schwann Cell Protrusions that Form in Response to Axonal Membranes.

PubMed

Poitelon, Yannick; Feltri, M Laura

2018-01-01

In the peripheral nervous system, axons dictate the differentiation state of Schwann cells. Most of this axonal influence on Schwann cells is due to juxtacrine interactions between axonal transmembrane molecules (e.g., the neuregulin growth factor) and receptors on the Schwann cell (e.g., the ErbB2/ErbB3 receptor). The fleeting nature of this interaction together with the lack of synchronicity in the development of the Schwann cell population limits our capability to study this phenomenon in vivo. Here we present a simple Boyden Chamber-based method to study this important cell-cell interaction event. We isolate the early protrusions of Schwann cells that are generated in response to juxtacrine stimulation by sensory neuronal membranes. This method is compatible with a large array of current biochemical analyses and provides an effective approach to study biomolecules that are differentially localized in Schwann cell protrusions and cell bodies in response to axonal signals. A similar approach can be extended to different kinds of cell-cell interactions.

UV-Visible and Infrared Methods for Investigating Lipid-Rhodopsin Membrane Interactions

PubMed Central

Brown, Michael F.

2017-01-01

Summary Experimental UV-visible and Fourier transform infrared (FTIR) spectroscopic methods are described for characterizing lipid-protein interactions for the example of rhodopsin in a membrane bilayer environment. The combined use of FTIR and UV-visible difference spectroscopy monitors the structural and functional changes during rhodopsin activation. Such studies investigate how membrane lipids stabilize the various rhodopsin photoproducts, analogous to mutating the protein. Interpretation of the results entails a non-specific flexible surface model for explaining the role of membrane lipid-protein interactions in biological functions. PMID:22976026

Study on interaction between induced and natural fractures by extended finite element method

NASA Astrophysics Data System (ADS)

Xu, DanDan; Liu, ZhanLi; Zhuang, Zhuo; Zeng, QingLei; Wang, Tao

2017-02-01

Fracking is one of the kernel technologies in the remarkable shale gas revolution. The extended finite element method is used in this paper to numerically investigate the interaction between hydraulic and natural fractures, which is an important issue of the enigmatic fracture network formation in fracking. The criteria which control the opening of natural fracture and crossing of hydraulic fracture are tentatively presented. Influence factors on the interaction process are systematically analyzed, which include the approach angle, anisotropy of in-situ stress and fluid pressure profile.

Predicting protein-protein interactions by combing various sequence- derived features into the general form of Chou's Pseudo amino acid composition.

PubMed

Zhao, Xiao-Wei; Ma, Zhi-Qiang; Yin, Ming-Hao

2012-05-01

Knowledge of protein-protein interactions (PPIs) plays an important role in constructing protein interaction networks and understanding the general machineries of biological systems. In this study, a new method is proposed to predict PPIs using a comprehensive set of 930 features based only on sequence information, these features measure the interactions between residues a certain distant apart in the protein sequences from different aspects. To achieve better performance, the principal component analysis (PCA) is first employed to obtain an optimized feature subset. Then, the resulting 67-dimensional feature vectors are fed to Support Vector Machine (SVM). Experimental results on Drosophila melanogaster and Helicobater pylori datasets show that our method is very promising to predict PPIs and may at least be a useful supplement tool to existing methods.

3D-QSAR studies of some reversible Acetyl cholinesterase inhibitors based on CoMFA and ligand protein interaction fingerprints using PC-LS-SVM and PLS-LS-SVM.

PubMed

Ghafouri, Hamidreza; Ranjbar, Mohsen; Sakhteman, Amirhossein

2017-08-01

A great challenge in medicinal chemistry is to develop different methods for structural design based on the pattern of the previously synthesized compounds. In this study two different QSAR methods were established and compared for a series of piperidine acetylcholinesterase inhibitors. In one novel approach, PC-LS-SVM and PLS-LS-SVM was used for modeling 3D interaction descriptors, and in the other method the same nonlinear techniques were used to build QSAR equations based on field descriptors. Different validation methods were used to evaluate the models and the results revealed the more applicability and predictive ability of the model generated by field descriptors (Q 2 LOO-CV =1, R 2 ext =0.97). External validation criteria revealed that both methods can be used in generating reasonable QSAR models. It was concluded that due to ability of interaction descriptors in prediction of binding mode, using this approach can be implemented in future 3D-QSAR softwares. Copyright © 2017 Elsevier Ltd. All rights reserved.

Interactive computer training to teach discrete-trial instruction to undergraduates and special educators in Brazil: A replication and extension.

PubMed

Higbee, Thomas S; Aporta, Ana Paula; Resende, Alice; Nogueira, Mateus; Goyos, Celso; Pollard, Joy S

2016-12-01

Discrete-trial instruction (DTI) is a behavioral method of teaching young children with autism spectrum disorders (ASD) that has received a significant amount of research support. Because of a lack of qualified trainers in many areas of the world, researchers have recently begun to investigate alternative methods of training professionals to implement behavioral teaching procedures. One promising training method is interactive computer training, in which slides with recorded narration, video modeling, and embedded evaluation of content knowledge are used to teach a skill. In the present study, the effectiveness of interactive computer training developed by Pollard, Higbee, Akers, and Brodhead (2014), translated into Brazilian Portuguese, was evaluated with 4 university students (Study 1) and 4 special education teachers (Study 2). We evaluated the effectiveness of training on DTI skills during role-plays with research assistants (Study 1) and during DTI sessions with young children with ASD (Studies 1 and 2) using a multiple baseline design. All participants acquired DTI skills after interactive computer training, although 5 of 8 participants required some form of feedback to reach proficiency. Responding generalized to untaught teaching programs for all participants. We evaluated maintenance with the teachers in Study 2, and DTI skills were maintained with 3 of 4 participants. © 2016 Society for the Experimental Analysis of Behavior.

Effect of reference genome selection on the performance of computational methods for genome-wide protein-protein interaction prediction.

PubMed

Muley, Vijaykumar Yogesh; Ranjan, Akash

2012-01-01

Recent progress in computational methods for predicting physical and functional protein-protein interactions has provided new insights into the complexity of biological processes. Most of these methods assume that functionally interacting proteins are likely to have a shared evolutionary history. This history can be traced out for the protein pairs of a query genome by correlating different evolutionary aspects of their homologs in multiple genomes known as the reference genomes. These methods include phylogenetic profiling, gene neighborhood and co-occurrence of the orthologous protein coding genes in the same cluster or operon. These are collectively known as genomic context methods. On the other hand a method called mirrortree is based on the similarity of phylogenetic trees between two interacting proteins. Comprehensive performance analyses of these methods have been frequently reported in literature. However, very few studies provide insight into the effect of reference genome selection on detection of meaningful protein interactions. We analyzed the performance of four methods and their variants to understand the effect of reference genome selection on prediction efficacy. We used six sets of reference genomes, sampled in accordance with phylogenetic diversity and relationship between organisms from 565 bacteria. We used Escherichia coli as a model organism and the gold standard datasets of interacting proteins reported in DIP, EcoCyc and KEGG databases to compare the performance of the prediction methods. Higher performance for predicting protein-protein interactions was achievable even with 100-150 bacterial genomes out of 565 genomes. Inclusion of archaeal genomes in the reference genome set improves performance. We find that in order to obtain a good performance, it is better to sample few genomes of related genera of prokaryotes from the large number of available genomes. Moreover, such a sampling allows for selecting 50-100 genomes for comparable accuracy of predictions when computational resources are limited.

A new strategic neurosurgical planning tool for brainstem cavernous malformations using interactive computer graphics with multimodal fusion images.

PubMed

Kin, Taichi; Nakatomi, Hirofumi; Shojima, Masaaki; Tanaka, Minoru; Ino, Kenji; Mori, Harushi; Kunimatsu, Akira; Oyama, Hiroshi; Saito, Nobuhito

2012-07-01

In this study, the authors used preoperative simulation employing 3D computer graphics (interactive computer graphics) to fuse all imaging data for brainstem cavernous malformations. The authors evaluated whether interactive computer graphics or 2D imaging correlated better with the actual operative field, particularly in identifying a developmental venous anomaly (DVA). The study population consisted of 10 patients scheduled for surgical treatment of brainstem cavernous malformations. Data from preoperative imaging (MRI, CT, and 3D rotational angiography) were automatically fused using a normalized mutual information method, and then reconstructed by a hybrid method combining surface rendering and volume rendering methods. With surface rendering, multimodality and multithreshold techniques for 1 tissue were applied. The completed interactive computer graphics were used for simulation of surgical approaches and assumed surgical fields. Preoperative diagnostic rates for a DVA associated with brainstem cavernous malformation were compared between conventional 2D imaging and interactive computer graphics employing receiver operating characteristic (ROC) analysis. The time required for reconstruction of 3D images was 3-6 hours for interactive computer graphics. Observation in interactive mode required approximately 15 minutes. Detailed anatomical information for operative procedures, from the craniotomy to microsurgical operations, could be visualized and simulated three-dimensionally as 1 computer graphic using interactive computer graphics. Virtual surgical views were consistent with actual operative views. This technique was very useful for examining various surgical approaches. Mean (±SEM) area under the ROC curve for rate of DVA diagnosis was significantly better for interactive computer graphics (1.000±0.000) than for 2D imaging (0.766±0.091; p<0.001, Mann-Whitney U-test). The authors report a new method for automatic registration of preoperative imaging data from CT, MRI, and 3D rotational angiography for reconstruction into 1 computer graphic. The diagnostic rate of DVA associated with brainstem cavernous malformation was significantly better using interactive computer graphics than with 2D images. Interactive computer graphics was also useful in helping to plan the surgical access corridor.

Interaction in Distance Nursing Education

ERIC Educational Resources Information Center

Boz Yuksekdag, Belgin

2012-01-01

The purpose of this study is to determine psychiatry nurses' attitudes toward the interactions in distance nursing education, and also scrunize their attitudes based on demographics and computer/Internet usage. The comparative relational scanning model is the method of this study. The research data were collected through "The Scale of Attitudes of…

Negotiated Interaction in the L2 Classroom

ERIC Educational Resources Information Center

Eckerth, Johannes

2009-01-01

The present paper reports on an approximate replication of Foster's (1998) study on the negotiation of meaning. Foster investigated the interactional adjustments produced by L2 English learners working on different types of language learning tasks in a classroom setting. The replication study duplicates the methods of data collection and data…

Learning with Interactive Computer Graphics in the Undergraduate Neuroscience Classroom

ERIC Educational Resources Information Center

Pani, John R.; Chariker, Julia H.; Naaz, Farah; Mattingly, William; Roberts, Joshua; Sephton, Sandra E.

2014-01-01

Instruction of neuroanatomy depends on graphical representation and extended self-study. As a consequence, computer-based learning environments that incorporate interactive graphics should facilitate instruction in this area. The present study evaluated such a system in the undergraduate neuroscience classroom. The system used the method of…

Bridge Building Potential in Cross-Cultural Learning: A Mixed Method Study

ERIC Educational Resources Information Center

Rienties, Bart; Johan, Novie; Jindal-Snape, Divya

2015-01-01

Although many international students experience transitional issues, most research assumes that these issues will disappear over time with increased interaction. Using principles of social network theory, this study addressed why some students become bridge builders between international and host students, while others primarily interact with…

Putting Life into Computer-Based Training: The Creation of an Epidemiologic Case Study.

ERIC Educational Resources Information Center

Gathany, Nancy C.; Stehr-Green, Jeanette K.

1994-01-01

Describes the design of "Pharyngitis in Louisiana," a computer-based epidemiologic case study that was created to teach students how to conduct disease outbreak investigations. Topics discussed include realistic content portrayals; graphics; interactive teaching methods; interaction between the instructional designer and the medical…

Bacterial molecular networks: bridging the gap between functional genomics and dynamical modelling.

PubMed

van Helden, Jacques; Toussaint, Ariane; Thieffry, Denis

2012-01-01

This introductory review synthesizes the contents of the volume Bacterial Molecular Networks of the series Methods in Molecular Biology. This volume gathers 9 reviews and 16 method chapters describing computational protocols for the analysis of metabolic pathways, protein interaction networks, and regulatory networks. Each protocol is documented by concrete case studies dedicated to model bacteria or interacting populations. Altogether, the chapters provide a representative overview of state-of-the-art methods for data integration and retrieval, network visualization, graph analysis, and dynamical modelling.

Method and apparatus to image biological interactions in plants

DOEpatents

Weisenberger, Andrew; Bonito, Gregory M.; Reid, Chantal D.; Smith, Mark Frederick

2015-12-22

A method to dynamically image the actual translocation of molecular compounds of interest in a plant root, root system, and rhizosphere without disturbing the root or the soil. The technique makes use of radioactive isotopes as tracers to label molecules of interest and to image their distribution in the plant and/or soil. The method allows for the study and imaging of various biological and biochemical interactions in the rhizosphere of a plant, including, but not limited to, mycorrhizal associations in such regions.

Inclusion of fluorophores in cyclodextrins: a closer look at the fluorometric determination of association constants by linear and nonlinear fitting procedures

NASA Astrophysics Data System (ADS)

Hutterer, Rudi

2018-01-01

The author discusses methods for the fluorometric determination of affinity constants by linear and nonlinear fitting methods. This is outlined in particular for the interaction between cyclodextrins and several anesthetic drugs including benzocaine. Special emphasis is given to the limitations of certain fits, and the impact of such studies on enzyme-substrate interactions are demonstrated. Both the experimental part and methods of analysis are well suited for students in an advanced lab.

Developing L2 Interactional Competence: Increasing Participation through Self-Selection in Post-Expansion Sequences

ERIC Educational Resources Information Center

Watanabe, Aya

2017-01-01

Using longitudinal conversation analysis as a methodological framework, this study documents the development of second language (L2) interactional competence by focusing on a recurrent interactional practice observed in an English as a foreign language (EFL) classroom. Through observing a novice L2 learner's developing methods of participation in…

Examining Interactive and Metacognitive Processes in Student Learning: Findings from a Hybrid Instructional Environment

ERIC Educational Resources Information Center

Meyers, Shelly; Feeney, Linda D.

2016-01-01

This study examines the interaction behaviors and metacognitive behaviors of graduate students in the online portion of a flipped classroom. For their time outside the face to face classroom, students were given the choice of two online methods for their interactions--synchronous verbal discussions and asynchronous written discussions. Students…

The Role of Group Interaction in Collective Efficacy and CSCL Performance

ERIC Educational Resources Information Center

Wang, Shu-Ling; Hsu, Hsien-Yuan; Lin, Sunny S. J.; Hwang, Gwo-Jen

2014-01-01

Although research has identified the importance of interaction behaviors in computer-supported collaborative learning (CSCL), very few attempts have been made to carry out in-depth analysis of interaction behaviors. This study thus applies both qualitative (e.g., content analyses, interviews) and quantitative methods in an attempt to investigate…

Application of linker technique to trap transiently interacting protein complexes for structural studies

PubMed Central

Reddy Chichili, Vishnu Priyanka; Kumar, Veerendra; Sivaraman, J.

2016-01-01

Protein-protein interactions are key events controlling several biological processes. We have developed and employed a method to trap transiently interacting protein complexes for structural studies using glycine-rich linkers to fuse interacting partners, one of which is unstructured. Initial steps involve isothermal titration calorimetry to identify the minimum binding region of the unstructured protein in its interaction with its stable binding partner. This is followed by computational analysis to identify the approximate site of the interaction and to design an appropriate linker length. Subsequently, fused constructs are generated and characterized using size exclusion chromatography and dynamic light scattering experiments. The structure of the chimeric protein is then solved by crystallization, and validated both in vitro and in vivo by substituting key interacting residues of the full length, unlinked proteins with alanine. This protocol offers the opportunity to study crucial and currently unattainable transient protein interactions involved in various biological processes. PMID:26985443

Identifying functional cancer-specific miRNA-mRNA interactions in testicular germ cell tumor.

PubMed

Sedaghat, Nafiseh; Fathy, Mahmood; Modarressi, Mohammad Hossein; Shojaie, Ali

2016-09-07

Testicular cancer is the most common cancer in men aged between 15 and 35 and more than 90% of testicular neoplasms are originated at germ cells. Recent research has shown the impact of microRNAs (miRNAs) in different types of cancer, including testicular germ cell tumor (TGCT). MicroRNAs are small non-coding RNAs which affect the development and progression of cancer cells by binding to mRNAs and regulating their expressions. The identification of functional miRNA-mRNA interactions in cancers, i.e. those that alter the expression of genes in cancer cells, can help delineate post-regulatory mechanisms and may lead to new treatments to control the progression of cancer. A number of sequence-based methods have been developed to predict miRNA-mRNA interactions based on the complementarity of sequences. While necessary, sequence complementarity is, however, not sufficient for presence of functional interactions. Alternative methods have thus been developed to refine the sequence-based interactions using concurrent expression profiles of miRNAs and mRNAs. This study aims to find functional cancer-specific miRNA-mRNA interactions in TGCT. To this end, the sequence-based predicted interactions are first refined using an ensemble learning method, based on two well-known methods of learning miRNA-mRNA interactions, namely, TaLasso and GenMiR++. Additional functional analyses were then used to identify a subset of interactions to be most likely functional and specific to TGCT. The final list of 13 miRNA-mRNA interactions can be potential targets for identifying TGCT-specific interactions and future laboratory experiments to develop new therapies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Physician Interactions with Electronic Health Records in Primary Care

PubMed Central

Montague, Enid; Asan, Onur

2013-01-01

Objective It is essential to design technologies and systems that promote appropriate interactions between physicians and patients. This study explored how physicians interact with Electronic Health Records (EHRs) to understand the qualities of the interaction between the physician and the EHR that may contribute to positive physician-patient interactions. Study Design Video-taped observations of 100 medical consultations were used to evaluate interaction patterns between physicians and EHRs. Quantified observational methods were used to contribute to ecological validity. Methods Ten primary care physicians and 100 patients from five clinics participated in the study. Clinical encounters were recorded with video cameras and coded using a validated objective coding methodology in order to examine how physicians interact with electronic health records. Results Three distinct styles were identified that characterize physician interactions with the EHR: technology-centered, human-centered, and mixed. Physicians who used a technology-centered style spent more time typing and gazing at the computer during the visit. Physicians who used a mixed style shifted their attention and body language between their patients and the technology throughout the visit. Physicians who used the human-centered style spent the least amount of time typing and focused more on the patient. Conclusion A variety of EHR interaction styles may be effective in facilitating patient-centered care. However, potential drawbacks of each style exist and are discussed. Future research on this topic and design strategies for effective health information technology in primary care are also discussed. PMID:24009982

Intuitive Density Functional Theory-Based Energy Decomposition Analysis for Protein-Ligand Interactions.

PubMed

Phipps, M J S; Fox, T; Tautermann, C S; Skylaris, C-K

2017-04-11

First-principles quantum mechanical calculations with methods such as density functional theory (DFT) allow the accurate calculation of interaction energies between molecules. These interaction energies can be dissected into chemically relevant components such as electrostatics, polarization, and charge transfer using energy decomposition analysis (EDA) approaches. Typically EDA has been used to study interactions between small molecules; however, it has great potential to be applied to large biomolecular assemblies such as protein-protein and protein-ligand interactions. We present an application of EDA calculations to the study of ligands that bind to the thrombin protein, using the ONETEP program for linear-scaling DFT calculations. Our approach goes beyond simply providing the components of the interaction energy; we are also able to provide visual representations of the changes in density that happen as a result of polarization and charge transfer, thus pinpointing the functional groups between the ligand and protein that participate in each kind of interaction. We also demonstrate with this approach that we can focus on studying parts (fragments) of ligands. The method is relatively insensitive to the protocol that is used to prepare the structures, and the results obtained are therefore robust. This is an application to a real protein drug target of a whole new capability where accurate DFT calculations can produce both energetic and visual descriptors of interactions. These descriptors can be used to provide insights for tailoring interactions, as needed for example in drug design.

Identification of multi-loci hubs from 4C-seq demonstrates the functional importance of simultaneous interactions.

PubMed

Jiang, Tingting; Raviram, Ramya; Snetkova, Valentina; Rocha, Pedro P; Proudhon, Charlotte; Badri, Sana; Bonneau, Richard; Skok, Jane A; Kluger, Yuval

2016-10-14

Use of low resolution single cell DNA FISH and population based high resolution chromosome conformation capture techniques have highlighted the importance of pairwise chromatin interactions in gene regulation. However, it is unlikely that associations involving regulatory elements act in isolation of other interacting partners that also influence their impact. Indeed, the influence of multi-loci interactions remains something of an enigma as beyond low-resolution DNA FISH we do not have the appropriate tools to analyze these. Here we present a method that uses standard 4C-seq data to identify multi-loci interactions from the same cell. We demonstrate the feasibility of our method using 4C-seq data sets that identify known pairwise and novel tri-loci interactions involving the Tcrb and Igk antigen receptor enhancers. We further show that the three Igk enhancers, MiEκ, 3'Eκ and Edκ, interact simultaneously in this super-enhancer cluster, which add to our previous findings showing that loss of one element decreases interactions between all three elements as well as reducing their transcriptional output. These findings underscore the functional importance of simultaneous interactions and provide new insight into the relationship between enhancer elements. Our method opens the door for studying multi-loci interactions and their impact on gene regulation in other biological settings. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Identification of multi-loci hubs from 4C-seq demonstrates the functional importance of simultaneous interactions

PubMed Central

Jiang, Tingting; Raviram, Ramya; Snetkova, Valentina; Rocha, Pedro P.; Proudhon, Charlotte; Badri, Sana; Bonneau, Richard; Skok, Jane A.; Kluger, Yuval

2016-01-01

Use of low resolution single cell DNA FISH and population based high resolution chromosome conformation capture techniques have highlighted the importance of pairwise chromatin interactions in gene regulation. However, it is unlikely that associations involving regulatory elements act in isolation of other interacting partners that also influence their impact. Indeed, the influence of multi-loci interactions remains something of an enigma as beyond low-resolution DNA FISH we do not have the appropriate tools to analyze these. Here we present a method that uses standard 4C-seq data to identify multi-loci interactions from the same cell. We demonstrate the feasibility of our method using 4C-seq data sets that identify known pairwise and novel tri-loci interactions involving the Tcrb and Igk antigen receptor enhancers. We further show that the three Igk enhancers, MiEκ, 3′Eκ and Edκ, interact simultaneously in this super-enhancer cluster, which add to our previous findings showing that loss of one element decreases interactions between all three elements as well as reducing their transcriptional output. These findings underscore the functional importance of simultaneous interactions and provide new insight into the relationship between enhancer elements. Our method opens the door for studying multi-loci interactions and their impact on gene regulation in other biological settings. PMID:27439714

A Density Perturbation Method to Study the Eigenstructure of Two-Phase Flow Equation Systems

NASA Astrophysics Data System (ADS)

Cortes, J.; Debussche, A.; Toumi, I.

1998-12-01

Many interesting and challenging physical mechanisms are concerned with the mathematical notion of eigenstructure. In two-fluid models, complex phasic interactions yield a complex eigenstructure which may raise numerous problems in numerical simulations. In this paper, we develop a perturbation method to examine the eigenvalues and eigenvectors of two-fluid models. This original method, based on the stiffness of the density ratio, provides a convenient tool to study the relevance of pressure momentum interactions and allows us to get precise approximations of the whole flow eigendecomposition for minor requirements. Roe scheme is successfully implemented and some numerical tests are presented.

Coupling functions: Universal insights into dynamical interaction mechanisms

NASA Astrophysics Data System (ADS)

Stankovski, Tomislav; Pereira, Tiago; McClintock, Peter V. E.; Stefanovska, Aneta

2017-10-01

The dynamical systems found in nature are rarely isolated. Instead they interact and influence each other. The coupling functions that connect them contain detailed information about the functional mechanisms underlying the interactions and prescribe the physical rule specifying how an interaction occurs. A coherent and comprehensive review is presented encompassing the rapid progress made recently in the analysis, understanding, and applications of coupling functions. The basic concepts and characteristics of coupling functions are presented through demonstrative examples of different domains, revealing the mechanisms and emphasizing their multivariate nature. The theory of coupling functions is discussed through gradually increasing complexity from strong and weak interactions to globally coupled systems and networks. A variety of methods that have been developed for the detection and reconstruction of coupling functions from measured data is described. These methods are based on different statistical techniques for dynamical inference. Stemming from physics, such methods are being applied in diverse areas of science and technology, including chemistry, biology, physiology, neuroscience, social sciences, mechanics, and secure communications. This breadth of application illustrates the universality of coupling functions for studying the interaction mechanisms of coupled dynamical systems.

Final project report for NEET pulsed ion beam project

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

Kucheyev, S. O.

The major goal of this project was to develop and demonstrate a novel experimental approach to access the dynamic regime of radiation damage formation in nuclear materials. In particular, the project exploited a pulsed-ion-beam method in order to gain insight into defect interaction dynamics by measuring effective defect interaction time constants and defect diffusion lengths. This project had the following four major objectives: (i) the demonstration of the pulsed ion beam method for a prototypical nuclear ceramic material, SiC; (ii) the evaluation of the robustness of the pulsed beam method from studies of defect generation rate effects; (iii) the measurementmore » of the temperature dependence of defect dynamics and thermally activated defect-interaction processes by pulsed ion beam techniques; and (iv) the demonstration of alternative characterization techniques to study defect dynamics. As we describe below, all these objectives have been met.« less

Classroom Interaction Strategies Employed by English Teachers at Lower Secondary Schools

ERIC Educational Resources Information Center

Suryati, Nunung

2015-01-01

This article reports a study on teachers' use of interaction strategies in English Language Teaching (ELT) in lower secondary level of education. The study involved eighteen teachers from Lower Secondary Schools in Malang, East Java. Classroom observation was selected as a method in this study by utilizing Self Evaluation Teacher Talk (SETT) as…

Interactional Markers in English Medical Research Articles Written by Iranian and Native Authors: A Contrastive Metadiscourse Analysis of Method Section

ERIC Educational Resources Information Center

Ghadyani, Fariba; Tahririan, Mohammad Hassan

2014-01-01

To determine the issue of whether there were any significant differences between the groups including Iran ISI, Iran non- ISI, and native authors in binary comparisons as for employing interactional markers, the present study was conducted. To collect the data, 90 "method sections" of English medical research articles within Iranian ISI,…

Boosting compound-protein interaction prediction by deep learning.

PubMed

Tian, Kai; Shao, Mingyu; Wang, Yang; Guan, Jihong; Zhou, Shuigeng

2016-11-01

The identification of interactions between compounds and proteins plays an important role in network pharmacology and drug discovery. However, experimentally identifying compound-protein interactions (CPIs) is generally expensive and time-consuming, computational approaches are thus introduced. Among these, machine-learning based methods have achieved a considerable success. However, due to the nonlinear and imbalanced nature of biological data, many machine learning approaches have their own limitations. Recently, deep learning techniques show advantages over many state-of-the-art machine learning methods in some applications. In this study, we aim at improving the performance of CPI prediction based on deep learning, and propose a method called DL-CPI (the abbreviation of Deep Learning for Compound-Protein Interactions prediction), which employs deep neural network (DNN) to effectively learn the representations of compound-protein pairs. Extensive experiments show that DL-CPI can learn useful features of compound-protein pairs by a layerwise abstraction, and thus achieves better prediction performance than existing methods on both balanced and imbalanced datasets. Copyright © 2016 Elsevier Inc. All rights reserved.

A centrifugation-based physicochemical characterization method for the interaction between proteins and nanoparticles

NASA Astrophysics Data System (ADS)

Bekdemir, Ahmet; Stellacci, Francesco

2016-10-01

Nanomedicine requires in-depth knowledge of nanoparticle-protein interactions. These interactions are studied with methods limited to large or fluorescently labelled nanoparticles as they rely on scattering or fluorescence-correlation signals. Here, we have developed a method based on analytical ultracentrifugation (AUC) as an absorbance-based, label-free tool to determine dissociation constants (KD), stoichiometry (Nmax), and Hill coefficient (n), for the association of bovine serum albumin (BSA) with gold nanoparticles. Absorption at 520 nm in AUC renders the measurements insensitive to unbound and aggregated proteins. Measurements remain accurate and do not become more challenging for small (sub-10 nm) nanoparticles. In AUC, frictional ratio analysis allows for the qualitative assessment of the shape of the analyte. Data suggests that small-nanoparticles/protein complexes significantly deviate from a spherical shape even at maximum coverage. We believe that this method could become one of the established approaches for the characterization of the interaction of (small) nanoparticles with proteins.

Improving the accuracy of Møller-Plesset perturbation theory with neural networks

NASA Astrophysics Data System (ADS)

McGibbon, Robert T.; Taube, Andrew G.; Donchev, Alexander G.; Siva, Karthik; Hernández, Felipe; Hargus, Cory; Law, Ka-Hei; Klepeis, John L.; Shaw, David E.

2017-10-01

Noncovalent interactions are of fundamental importance across the disciplines of chemistry, materials science, and biology. Quantum chemical calculations on noncovalently bound complexes, which allow for the quantification of properties such as binding energies and geometries, play an essential role in advancing our understanding of, and building models for, a vast array of complex processes involving molecular association or self-assembly. Because of its relatively modest computational cost, second-order Møller-Plesset perturbation (MP2) theory is one of the most widely used methods in quantum chemistry for studying noncovalent interactions. MP2 is, however, plagued by serious errors due to its incomplete treatment of electron correlation, especially when modeling van der Waals interactions and π-stacked complexes. Here we present spin-network-scaled MP2 (SNS-MP2), a new semi-empirical MP2-based method for dimer interaction-energy calculations. To correct for errors in MP2, SNS-MP2 uses quantum chemical features of the complex under study in conjunction with a neural network to reweight terms appearing in the total MP2 interaction energy. The method has been trained on a new data set consisting of over 200 000 complete basis set (CBS)-extrapolated coupled-cluster interaction energies, which are considered the gold standard for chemical accuracy. SNS-MP2 predicts gold-standard binding energies of unseen test compounds with a mean absolute error of 0.04 kcal mol-1 (root-mean-square error 0.09 kcal mol-1), a 6- to 7-fold improvement over MP2. To the best of our knowledge, its accuracy exceeds that of all extant density functional theory- and wavefunction-based methods of similar computational cost, and is very close to the intrinsic accuracy of our benchmark coupled-cluster methodology itself. Furthermore, SNS-MP2 provides reliable per-conformation confidence intervals on the predicted interaction energies, a feature not available from any alternative method.

Improving the accuracy of Møller-Plesset perturbation theory with neural networks.

PubMed

McGibbon, Robert T; Taube, Andrew G; Donchev, Alexander G; Siva, Karthik; Hernández, Felipe; Hargus, Cory; Law, Ka-Hei; Klepeis, John L; Shaw, David E

2017-10-28

Noncovalent interactions are of fundamental importance across the disciplines of chemistry, materials science, and biology. Quantum chemical calculations on noncovalently bound complexes, which allow for the quantification of properties such as binding energies and geometries, play an essential role in advancing our understanding of, and building models for, a vast array of complex processes involving molecular association or self-assembly. Because of its relatively modest computational cost, second-order Møller-Plesset perturbation (MP2) theory is one of the most widely used methods in quantum chemistry for studying noncovalent interactions. MP2 is, however, plagued by serious errors due to its incomplete treatment of electron correlation, especially when modeling van der Waals interactions and π-stacked complexes. Here we present spin-network-scaled MP2 (SNS-MP2), a new semi-empirical MP2-based method for dimer interaction-energy calculations. To correct for errors in MP2, SNS-MP2 uses quantum chemical features of the complex under study in conjunction with a neural network to reweight terms appearing in the total MP2 interaction energy. The method has been trained on a new data set consisting of over 200 000 complete basis set (CBS)-extrapolated coupled-cluster interaction energies, which are considered the gold standard for chemical accuracy. SNS-MP2 predicts gold-standard binding energies of unseen test compounds with a mean absolute error of 0.04 kcal mol -1 (root-mean-square error 0.09 kcal mol -1 ), a 6- to 7-fold improvement over MP2. To the best of our knowledge, its accuracy exceeds that of all extant density functional theory- and wavefunction-based methods of similar computational cost, and is very close to the intrinsic accuracy of our benchmark coupled-cluster methodology itself. Furthermore, SNS-MP2 provides reliable per-conformation confidence intervals on the predicted interaction energies, a feature not available from any alternative method.

Measurement of Vehicle-Bridge-Interaction force using dynamic tire pressure monitoring

NASA Astrophysics Data System (ADS)

Chen, Zhao; Xie, Zhipeng; Zhang, Jian

2018-05-01

The Vehicle-Bridge-Interaction (VBI) force, i.e., the normal contact force of a tire, is a key component in the VBI mechanism. The VBI force measurement can facilitate experimental studies of the VBI as well as input-output bridge structural identification. This paper introduces an innovative method for calculating the interaction force by using dynamic tire pressure monitoring. The core idea of the proposed method combines the ideal gas law and a basic force model to build a relationship between the tire pressure and the VBI force. Then, unknown model parameters are identified by the Extended Kalman Filter using calibration data. A signal filter based on the wavelet analysis is applied to preprocess the effect that the tire rotation has on the pressure data. Two laboratory tests were conducted to check the proposed method's validity. The effects of different road irregularities, loads and forward velocities were studied. Under the current experiment setting, the proposed method was robust to different road irregularities, and the increase in load and velocity benefited the performance of the proposed method. A high-speed test further supported the use of this method in rapid bridge tests. Limitations of the derived theories and experiment were also discussed.

Approaches for Studying the Subcellular Localization, Interactions, and Regulation of Histone Deacetylase 5 (HDAC5)

PubMed Central

Guise, Amanda J.; Cristea, Ileana M.

2017-01-01

As a member of the class IIa family of histone deacetylases, the histone deacetylase 5 (HDAC5) is known to undergo nuclear–cytoplasmic shuttling and to be a critical transcriptional regulator. Its misregulation has been linked to prominent human diseases, including cardiac diseases and tumorigenesis. In this chapter, we describe several experimental methods that have proven effective for studying the functions and regulatory features of HDAC5. We present methods for assessing the subcellular localization, protein interactions, posttranslational modifications (PTMs), and activity of HDAC5 from the standpoint of investigating either the endogenous protein or tagged protein forms in human cells. Specifically, given that at the heart of HDAC5 regulation lie its dynamic localization, interactions, and PTMs, we present methods for assessing HDAC5 localization in fixed and live cells, for isolating HDAC5-containing protein complexes to identify its interactions and modifications, and for determining how these PTMs map to predicted HDAC5 structural motifs. Lastly, we provide examples of approaches for studying HDAC5 functions with a focus on its regulation during cell-cycle progression. These methods can readily be adapted for the study of other HDACs or non-HDAC-proteins of interest. Individually, these techniques capture temporal and spatial snapshots of HDAC5 functions; yet together, these approaches provide powerful tools for investigating both the regulation and regulatory roles of HDAC5 in different cell contexts relevant to health and disease. PMID:27246208

Dual Logic and Cerebral Coordinates for Reciprocal Interaction in Eye Contact

PubMed Central

Lee, Ray F.

2015-01-01

In order to scientifically study the human brain’s response to face-to-face social interaction, the scientific method itself needs to be reconsidered so that both quantitative observation and symbolic reasoning can be adapted to the situation where the observer is also observed. In light of the recent development of dyadic fMRI which can directly observe dyadic brain interacting in one MRI scanner, this paper aims to establish a new form of logic, dual logic, which provides a theoretical platform for deductive reasoning in a complementary dual system with emergence mechanism. Applying the dual logic in the dfMRI experimental design and data analysis, the exogenous and endogenous dual systems in the BOLD responses can be identified; the non-reciprocal responses in the dual system can be suppressed; a cerebral coordinate for reciprocal interaction can be generated. Elucidated by dual logic deductions, the cerebral coordinate for reciprocal interaction suggests: the exogenous and endogenous systems consist of the empathy network and the mentalization network respectively; the default-mode network emerges from the resting state to activation in the endogenous system during reciprocal interaction; the cingulate plays an essential role in the emergence from the exogenous system to the endogenous system. Overall, the dual logic deductions are supported by the dfMRI experimental results and are consistent with current literature. Both the theoretical framework and experimental method set the stage to formally apply the scientific method in studying complex social interaction. PMID:25885446

Interaction entropy for protein-protein binding.

PubMed

Sun, Zhaoxi; Yan, Yu N; Yang, Maoyou; Zhang, John Z H

2017-03-28

Protein-protein interactions are at the heart of signal transduction and are central to the function of protein machine in biology. The highly specific protein-protein binding is quantitatively characterized by the binding free energy whose accurate calculation from the first principle is a grand challenge in computational biology. In this paper, we show how the interactionentropy approach, which was recently proposed for protein-ligand binding free energy calculation, can be applied to computing the entropic contribution to the protein-protein binding free energy. Explicit theoretical derivation of the interactionentropy approach for protein-protein interaction system is given in detail from the basic definition. Extensive computational studies for a dozen realistic protein-protein interaction systems are carried out using the present approach and comparisons of the results for these protein-protein systems with those from the standard normal mode method are presented. Analysis of the present method for application in protein-protein binding as well as the limitation of the method in numerical computation is discussed. Our study and analysis of the results provided useful information for extracting correct entropic contribution in protein-protein binding from molecular dynamics simulations.

The chemical basis for the origin of the genetic code and the process of protein synthesis

NASA Technical Reports Server (NTRS)

1981-01-01

The principles upon which the process of protein synthesis and the genetic code were established are elucidated. Extensive work on nuclear magnetic resonance studies of both monomermonomer and monoamino acid polynucleotide interactions is included. A new method of general utility for studying any amino acid interacting with any polynucleotide was developed. This system involves the use of methyl esters of amino acids interacting with polynucleotides.

Interactive Performance and Focus Groups with Adolescents: The Power of Play

PubMed Central

Norris, Anne E.; Aroian, Karen J.; Warren, Stefanie

2012-01-01

Conducting focus groups with adolescents can be challenging given their developmental needs, particularly with sensitive topics. These challenges include intense need for peer approval, declining social trust, short attention span, and reliance on concrete operations thinking. In this article we describe an adaptation of interactive performance as an alternative to traditional focus group method. We used this method in a study of discrimination experienced by Muslims (ages 13-17) and of peer pressure to engage in sexual behavior experienced by Hispanic girls (ages 10-14). Recommendations for use of this method include using an interdisciplinary team, planning for large amounts of disclosure towards the end of the focus group, and considering the fit of this method to the study topic. PMID:22949032

An Interactive Image Segmentation Method in Hand Gesture Recognition

PubMed Central

Chen, Disi; Li, Gongfa; Sun, Ying; Kong, Jianyi; Jiang, Guozhang; Tang, Heng; Ju, Zhaojie; Yu, Hui; Liu, Honghai

2017-01-01

In order to improve the recognition rate of hand gestures a new interactive image segmentation method for hand gesture recognition is presented, and popular methods, e.g., Graph cut, Random walker, Interactive image segmentation using geodesic star convexity, are studied in this article. The Gaussian Mixture Model was employed for image modelling and the iteration of Expectation Maximum algorithm learns the parameters of Gaussian Mixture Model. We apply a Gibbs random field to the image segmentation and minimize the Gibbs Energy using Min-cut theorem to find the optimal segmentation. The segmentation result of our method is tested on an image dataset and compared with other methods by estimating the region accuracy and boundary accuracy. Finally five kinds of hand gestures in different backgrounds are tested on our experimental platform, and the sparse representation algorithm is used, proving that the segmentation of hand gesture images helps to improve the recognition accuracy. PMID:28134818

Analysis of iced wings

NASA Technical Reports Server (NTRS)

Cebeci, T.; Chen, H. H.; Kaups, K.; Schimke, S.; Shin, J.

1992-01-01

A method for computing ice shapes along the leading edge of a wing and a method for predicting its aerodynamic performance degradation due to icing is described. Ice shapes are computed using an extension of the LEWICE code which was developed for airfoils. The aerodynamic properties of the iced wing are determined with an interactive scheme in which the solutions of the inviscid flow equations are obtained from a panel method and the solutions of the viscous flow equations are obtained from an inverse three-dimensional finite-difference boundary-layer method. A new interaction law is used to couple the inviscid and viscous flow solutions. The application of the LEWICE wing code to the calculation of ice shapes on a MS-317 swept wing shows good agreement with measurements. The interactive boundary-layer method is applied to a tapered ice wing in order to study the effect of icing on the aerodynamic properties of the wing at several angles of attack.

Geo-Sandbox: An Interactive Geoscience Training Tool with Analytics to Better Understand Student Problem Solving Approaches

NASA Astrophysics Data System (ADS)

Butt, N.; Pidlisecky, A.; Ganshorn, H.; Cockett, R.

2015-12-01

The software company 3 Point Science has developed three interactive learning programs designed to teach, test and practice visualization skills and geoscience concepts. A study was conducted with 21 geoscience students at the University of Calgary who participated in 2 hour sessions of software interaction and written pre and post-tests. Computer and SMART touch table interfaces were used to analyze user interaction, problem solving methods and visualization skills. By understanding and pinpointing user problem solving methods it is possible to reconstruct viewpoints and thought processes. This could allow us to give personalized feedback in real time, informing the user of problem solving tips and possible misconceptions.

Predicting Drug-Target Interactions With Multi-Information Fusion.

PubMed

Peng, Lihong; Liao, Bo; Zhu, Wen; Li, Zejun; Li, Keqin

2017-03-01

Identifying potential associations between drugs and targets is a critical prerequisite for modern drug discovery and repurposing. However, predicting these associations is difficult because of the limitations of existing computational methods. Most models only consider chemical structures and protein sequences, and other models are oversimplified. Moreover, datasets used for analysis contain only true-positive interactions, and experimentally validated negative samples are unavailable. To overcome these limitations, we developed a semi-supervised based learning framework called NormMulInf through collaborative filtering theory by using labeled and unlabeled interaction information. The proposed method initially determines similarity measures, such as similarities among samples and local correlations among the labels of the samples, by integrating biological information. The similarity information is then integrated into a robust principal component analysis model, which is solved using augmented Lagrange multipliers. Experimental results on four classes of drug-target interaction networks suggest that the proposed approach can accurately classify and predict drug-target interactions. Part of the predicted interactions are reported in public databases. The proposed method can also predict possible targets for new drugs and can be used to determine whether atropine may interact with alpha1B- and beta1- adrenergic receptors. Furthermore, the developed technique identifies potential drugs for new targets and can be used to assess whether olanzapine and propiomazine may target 5HT2B. Finally, the proposed method can potentially address limitations on studies of multitarget drugs and multidrug targets.

Interaction energies for the purine inhibitor roscovitine with cyclin-dependent kinase 2: correlated ab initio quantum-chemical, DFT and empirical calculations.

PubMed

Dobes, Petr; Otyepka, Michal; Strnad, Miroslav; Hobza, Pavel

2006-05-24

The interaction between roscovitine and cyclin-dependent kinase 2 (cdk2) was investigated by performing correlated ab initio quantum-chemical calculations. The whole protein was fragmented into smaller systems consisting of one or a few amino acids, and the interaction energies of these fragments with roscovitine were determined by using the MP2 method with the extended aug-cc-pVDZ basis set. For selected complexes, the complete basis set limit MP2 interaction energies, as well as the coupled-cluster corrections with inclusion of single, double and noninteractive triples contributions [CCSD(T)], were also evaluated. The energies of interaction between roscovitine and small fragments and between roscovitine and substantial sections of protein (722 atoms) were also computed by using density-functional tight-binding methods covering dispersion energy (DFTB-D) and the Cornell empirical potential. Total stabilisation energy originates predominantly from dispersion energy and methods that do not account for the dispersion energy cannot, therefore, be recommended for the study of protein-inhibitor interactions. The Cornell empirical potential describes reasonably well the interaction between roscovitine and protein; therefore, this method can be applied in future thermodynamic calculations. A limited number of amino acid residues contribute significantly to the binding of roscovitine and cdk2, whereas a rather large number of amino acids make a negligible contribution.

Studies of Phonon Anharmonicity in Solids

NASA Astrophysics Data System (ADS)

Lan, Tian

Today our understanding of the vibrational thermodynamics of materials at low temperatures is emerging nicely, based on the harmonic model in which phonons are independent. At high temperatures, however, this understanding must accommodate how phonons interact with other phonons or with other excitations. We shall see that the phonon-phonon interactions give rise to interesting coupling problems, and essentially modify the equilibrium and non-equilibrium properties of materials, e.g., thermodynamic stability, heat capacity, optical properties and thermal transport of materials. Despite its great importance, to date the anharmonic lattice dynamics is poorly understood and most studies on lattice dynamics still rely on the harmonic or quasiharmonic models. There have been very few studies on the pure phonon anharmonicity and phonon-phonon interactions. The work presented in this thesis is devoted to the development of experimental and computational methods on this subject. Modern inelastic scattering techniques with neutrons or photons are ideal for sorting out the anharmonic contribution. Analysis of the experimental data can generate vibrational spectra of the materials, i.e., their phonon densities of states or phonon dispersion relations. We obtained high quality data from laser Raman spectrometer, Fourier transform infrared spectrometer and inelastic neutron spectrometer. With accurate phonon spectra data, we obtained the energy shifts and lifetime broadenings of the interacting phonons, and the vibrational entropies of different materials. The understanding of them then relies on the development of the fundamental theories and the computational methods. We developed an efficient post-processor for analyzing the anharmonic vibrations from the molecular dynamics (MD) calculations. Currently, most first principles methods are not capable of dealing with strong anharmonicity, because the interactions of phonons are ignored at finite temperatures. Our method adopts the Fourier transformed velocity autocorrelation method to handle the big data of time-dependent atomic velocities from MD calculations, and efficiently reconstructs the phonon DOS and phonon dispersion relations. Our calculations can reproduce the phonon frequency shifts and lifetime broadenings very well at various temperatures. To understand non-harmonic interactions in a microscopic way, we have developed a numerical fitting method to analyze the decay channels of phonon-phonon interactions. Based on the quantum perturbation theory of many-body interactions, this method is used to calculate the three-phonon and four-phonon kinematics subject to the conservation of energy and momentum, taking into account the weight of phonon couplings. We can assess the strengths of phonon-phonon interactions of different channels and anharmonic orders with the calculated two-phonon DOS. This method, with high computational efficiency, is a promising direction to advance our understandings of non-harmonic lattice dynamics and thermal transport properties. These experimental techniques and theoretical methods have been successfully performed in the study of anharmonic behaviors of metal oxides, including rutile and cuprite stuctures, and will be discussed in detail in Chapters 4 to 6. For example, for rutile titanium dioxide (TiO2), we found that the anomalous anharmonic behavior of the B1g mode can be explained by the volume effects on quasiharmonic force constants, and by the explicit cubic and quartic anharmonicity. For rutile tin dioxide (SnO2), the broadening of the B2 g mode with temperature showed an unusual concave downwards curvature. This curvature was caused by a change with temperature in the number of down-conversion decay channels, originating with the wide band gap in the phonon dispersions. For silver oxide (Ag2O), strong anharmonic effects were found for both phonons and for the negative thermal expansion.

Screening large-scale association study data: exploiting interactions using random forests.

PubMed

Lunetta, Kathryn L; Hayward, L Brooke; Segal, Jonathan; Van Eerdewegh, Paul

2004-12-10

Genome-wide association studies for complex diseases will produce genotypes on hundreds of thousands of single nucleotide polymorphisms (SNPs). A logical first approach to dealing with massive numbers of SNPs is to use some test to screen the SNPs, retaining only those that meet some criterion for further study. For example, SNPs can be ranked by p-value, and those with the lowest p-values retained. When SNPs have large interaction effects but small marginal effects in a population, they are unlikely to be retained when univariate tests are used for screening. However, model-based screens that pre-specify interactions are impractical for data sets with thousands of SNPs. Random forest analysis is an alternative method that produces a single measure of importance for each predictor variable that takes into account interactions among variables without requiring model specification. Interactions increase the importance for the individual interacting variables, making them more likely to be given high importance relative to other variables. We test the performance of random forests as a screening procedure to identify small numbers of risk-associated SNPs from among large numbers of unassociated SNPs using complex disease models with up to 32 loci, incorporating both genetic heterogeneity and multi-locus interaction. Keeping other factors constant, if risk SNPs interact, the random forest importance measure significantly outperforms the Fisher Exact test as a screening tool. As the number of interacting SNPs increases, the improvement in performance of random forest analysis relative to Fisher Exact test for screening also increases. Random forests perform similarly to the univariate Fisher Exact test as a screening tool when SNPs in the analysis do not interact. In the context of large-scale genetic association studies where unknown interactions exist among true risk-associated SNPs or SNPs and environmental covariates, screening SNPs using random forest analyses can significantly reduce the number of SNPs that need to be retained for further study compared to standard univariate screening methods.

Random vs. Combinatorial Methods for Discrete Event Simulation of a Grid Computer Network

NASA Technical Reports Server (NTRS)

Kuhn, D. Richard; Kacker, Raghu; Lei, Yu

2010-01-01

This study compared random and t-way combinatorial inputs of a network simulator, to determine if these two approaches produce significantly different deadlock detection for varying network configurations. Modeling deadlock detection is important for analyzing configuration changes that could inadvertently degrade network operations, or to determine modifications that could be made by attackers to deliberately induce deadlock. Discrete event simulation of a network may be conducted using random generation, of inputs. In this study, we compare random with combinatorial generation of inputs. Combinatorial (or t-way) testing requires every combination of any t parameter values to be covered by at least one test. Combinatorial methods can be highly effective because empirical data suggest that nearly all failures involve the interaction of a small number of parameters (1 to 6). Thus, for example, if all deadlocks involve at most 5-way interactions between n parameters, then exhaustive testing of all n-way interactions adds no additional information that would not be obtained by testing all 5-way interactions. While the maximum degree of interaction between parameters involved in the deadlocks clearly cannot be known in advance, covering all t-way interactions may be more efficient than using random generation of inputs. In this study we tested this hypothesis for t = 2, 3, and 4 for deadlock detection in a network simulation. Achieving the same degree of coverage provided by 4-way tests would have required approximately 3.2 times as many random tests; thus combinatorial methods were more efficient for detecting deadlocks involving a higher degree of interactions. The paper reviews explanations for these results and implications for modeling and simulation.

Selective IR multiphoton dissociation of molecules in a pulsed gas-dynamically cooled molecular flow interacting with a solid surface as an alternative to low-energy methods of molecular laser isotope separation

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

Makarov, G N; Petin, A N

2016-03-31

We report the results of studies on the isotope-selective infrared multiphoton dissociation (IR MFD) of SF{sub 6} and CF{sub 3}I molecules in a pulsed, gas-dynamically cooled molecular flow interacting with a solid surface. The productivity of this method in the conditions of a specific experiment (by the example of SF{sub 6} molecules) is evaluated. A number of low-energy methods of molecular laser isotope separation based on the use of infrared lasers for selective excitation of molecules are analysed and their productivity is estimated. The methods are compared with those of selective dissociation of molecules in the flow interacting with amore » surface. The advantages of this method compared to the low-energy methods of molecular laser isotope separation and the IR MPD method in the unperturbed jets and flows are shown. It is concluded that this method could be a promising alternative to the low-energy methods of molecular laser isotope separation. (laser separation of isotopes)« less

The Use of Two-Photon FRET-FLIM to Study Protein Interactions During Nuclear Envelope Fusion In Vivo and In Vitro.

PubMed

Byrne, Richard D; Larijani, Banafshé; Poccia, Dominic L

2016-01-01

FRET-FLIM techniques have wide application in the study of protein and protein-lipid interactions in cells. We have pioneered an imaging platform for accurate detection of functional states of proteins and their interactions in fixed cells. This platform, two-site-amplified Förster resonance energy transfer (a-FRET), allows greater signal generation while retaining minimal noise thus enabling application of fluorescence lifetime imaging microscopy (FLIM) to be routinely deployed in different types of cells and tissue. We have used the method described here, time-resolved FRET monitored by two-photon FLIM, to demonstrate the direct interaction of Phospholipase Cγ (PLCγ) by Src Family Kinase 1 (SFK1) during nuclear envelope formation and during male and female pronuclear membrane fusion in fertilized sea urchin eggs. We describe here a generic method that can be applied to monitor any proteins of interest.

Protein electrostatics: a review of the equations and methods used to model electrostatic equations in biomolecules--applications in biotechnology.

PubMed

Neves-Petersen, Maria Teresa; Petersen, Steffen B

2003-01-01

The molecular understanding of the initial interaction between a protein and, e.g., its substrate, a surface or an inhibitor is essentially an understanding of the role of electrostatics in intermolecular interactions. When studying biomolecules it is becoming increasingly evident that electrostatic interactions play a role in folding, conformational stability, enzyme activity and binding energies as well as in protein-protein interactions. In this chapter we present the key basic equations of electrostatics necessary to derive the equations used to model electrostatic interactions in biomolecules. We will also address how to solve such equations. This chapter is divided into two major sections. In the first part we will review the basic Maxwell equations of electrostatics equations called the Laws of Electrostatics that combined will result in the Poisson equation. This equation is the starting point of the Poisson-Boltzmann (PB) equation used to model electrostatic interactions in biomolecules. Concepts as electric field lines, equipotential surfaces, electrostatic energy and when can electrostatics be applied to study interactions between charges will be addressed. In the second part we will arrive at the electrostatic equations for dielectric media such as a protein. We will address the theory of dielectrics and arrive at the Poisson equation for dielectric media and at the PB equation, the main equation used to model electrostatic interactions in biomolecules (e.g., proteins, DNA). It will be shown how to compute forces and potentials in a dielectric medium. In order to solve the PB equation we will present the continuum electrostatic models, namely the Tanford-Kirkwood and the modified Tandord-Kirkwood methods. Priority will be given to finding the protonation state of proteins prior to solving the PB equation. We also present some methods that can be used to map and study the electrostatic potential distribution on the molecular surface of proteins. The combination of graphical visualisation of the electrostatic fields combined with knowledge about the location of key residues on the protein surface allows us to envision atomic models for enzyme function. Finally, we exemplify the use of some of these methods on the enzymes of the lipase family.

Meta-analysis identifies gene-by-environment interactions as demonstrated in a study of 4,965 mice.

PubMed

Kang, Eun Yong; Han, Buhm; Furlotte, Nicholas; Joo, Jong Wha J; Shih, Diana; Davis, Richard C; Lusis, Aldons J; Eskin, Eleazar

2014-01-01

Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta-analysis approach is that our combined study has significantly higher power and improved resolution compared to any single study thus explaining the large number of loci discovered in the combined study.

Meta-Analysis Identifies Gene-by-Environment Interactions as Demonstrated in a Study of 4,965 Mice

PubMed Central

Joo, Jong Wha J.; Shih, Diana; Davis, Richard C.; Lusis, Aldons J.; Eskin, Eleazar

2014-01-01

Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta-analysis approach is that our combined study has significantly higher power and improved resolution compared to any single study thus explaining the large number of loci discovered in the combined study. PMID:24415945

Super-resolution imaging and tracking of protein-protein interactions in sub-diffraction cellular space

NASA Astrophysics Data System (ADS)

Liu, Zhen; Xing, Dong; Su, Qian Peter; Zhu, Yun; Zhang, Jiamei; Kong, Xinyu; Xue, Boxin; Wang, Sheng; Sun, Hao; Tao, Yile; Sun, Yujie

2014-07-01

Imaging the location and dynamics of individual interacting protein pairs is essential but often difficult because of the fluorescent background from other paired and non-paired molecules, particularly in the sub-diffraction cellular space. Here we develop a new method combining bimolecular fluorescence complementation and photoactivated localization microscopy for super-resolution imaging and single-molecule tracking of specific protein-protein interactions. The method is used to study the interaction of two abundant proteins, MreB and EF-Tu, in Escherichia coli cells. The super-resolution imaging shows interesting distribution and domain sizes of interacting MreB-EF-Tu pairs as a subpopulation of total EF-Tu. The single-molecule tracking of MreB, EF-Tu and MreB-EF-Tu pairs reveals intriguing localization-dependent heterogonous dynamics and provides valuable insights to understanding the roles of MreB-EF-Tu interactions.

Super-resolution imaging and tracking of protein–protein interactions in sub-diffraction cellular space

PubMed Central

Liu, Zhen; Xing, Dong; Su, Qian Peter; Zhu, Yun; Zhang, Jiamei; Kong, Xinyu; Xue, Boxin; Wang, Sheng; Sun, Hao; Tao, Yile; Sun, Yujie

2014-01-01

Imaging the location and dynamics of individual interacting protein pairs is essential but often difficult because of the fluorescent background from other paired and non-paired molecules, particularly in the sub-diffraction cellular space. Here we develop a new method combining bimolecular fluorescence complementation and photoactivated localization microscopy for super-resolution imaging and single-molecule tracking of specific protein–protein interactions. The method is used to study the interaction of two abundant proteins, MreB and EF-Tu, in Escherichia coli cells. The super-resolution imaging shows interesting distribution and domain sizes of interacting MreB–EF-Tu pairs as a subpopulation of total EF-Tu. The single-molecule tracking of MreB, EF-Tu and MreB–EF-Tu pairs reveals intriguing localization-dependent heterogonous dynamics and provides valuable insights to understanding the roles of MreB–EF-Tu interactions. PMID:25030837

Large-scale protein-protein interactions detection by integrating big biosensing data with computational model.

PubMed

You, Zhu-Hong; Li, Shuai; Gao, Xin; Luo, Xin; Ji, Zhen

2014-01-01

Protein-protein interactions are the basis of biological functions, and studying these interactions on a molecular level is of crucial importance for understanding the functionality of a living cell. During the past decade, biosensors have emerged as an important tool for the high-throughput identification of proteins and their interactions. However, the high-throughput experimental methods for identifying PPIs are both time-consuming and expensive. On the other hand, high-throughput PPI data are often associated with high false-positive and high false-negative rates. Targeting at these problems, we propose a method for PPI detection by integrating biosensor-based PPI data with a novel computational model. This method was developed based on the algorithm of extreme learning machine combined with a novel representation of protein sequence descriptor. When performed on the large-scale human protein interaction dataset, the proposed method achieved 84.8% prediction accuracy with 84.08% sensitivity at the specificity of 85.53%. We conducted more extensive experiments to compare the proposed method with the state-of-the-art techniques, support vector machine. The achieved results demonstrate that our approach is very promising for detecting new PPIs, and it can be a helpful supplement for biosensor-based PPI data detection.

Using imputed genotype data in the joint score tests for genetic association and gene-environment interactions in case-control studies.

PubMed

Song, Minsun; Wheeler, William; Caporaso, Neil E; Landi, Maria Teresa; Chatterjee, Nilanjan

2018-03-01

Genome-wide association studies (GWAS) are now routinely imputed for untyped single nucleotide polymorphisms (SNPs) based on various powerful statistical algorithms for imputation trained on reference datasets. The use of predicted allele counts for imputed SNPs as the dosage variable is known to produce valid score test for genetic association. In this paper, we investigate how to best handle imputed SNPs in various modern complex tests for genetic associations incorporating gene-environment interactions. We focus on case-control association studies where inference for an underlying logistic regression model can be performed using alternative methods that rely on varying degree on an assumption of gene-environment independence in the underlying population. As increasingly large-scale GWAS are being performed through consortia effort where it is preferable to share only summary-level information across studies, we also describe simple mechanisms for implementing score tests based on standard meta-analysis of "one-step" maximum-likelihood estimates across studies. Applications of the methods in simulation studies and a dataset from GWAS of lung cancer illustrate ability of the proposed methods to maintain type-I error rates for the underlying testing procedures. For analysis of imputed SNPs, similar to typed SNPs, the retrospective methods can lead to considerable efficiency gain for modeling of gene-environment interactions under the assumption of gene-environment independence. Methods are made available for public use through CGEN R software package. © 2017 WILEY PERIODICALS, INC.

Quantitative analysis of protein-ligand interactions by NMR.

PubMed

Furukawa, Ayako; Konuma, Tsuyoshi; Yanaka, Saeko; Sugase, Kenji

2016-08-01

Protein-ligand interactions have been commonly studied through static structures of the protein-ligand complex. Recently, however, there has been increasing interest in investigating the dynamics of protein-ligand interactions both for fundamental understanding of the underlying mechanisms and for drug development. NMR is a versatile and powerful tool, especially because it provides site-specific quantitative information. NMR has widely been used to determine the dissociation constant (KD), in particular, for relatively weak interactions. The simplest NMR method is a chemical-shift titration experiment, in which the chemical-shift changes of a protein in response to ligand titration are measured. There are other quantitative NMR methods, but they mostly apply only to interactions in the fast-exchange regime. These methods derive the dissociation constant from population-averaged NMR quantities of the free and bound states of a protein or ligand. In contrast, the recent advent of new relaxation-based experiments, including R2 relaxation dispersion and ZZ-exchange, has enabled us to obtain kinetic information on protein-ligand interactions in the intermediate- and slow-exchange regimes. Based on R2 dispersion or ZZ-exchange, methods that can determine the association rate, kon, dissociation rate, koff, and KD have been developed. In these approaches, R2 dispersion or ZZ-exchange curves are measured for multiple samples with different protein and/or ligand concentration ratios, and the relaxation data are fitted to theoretical kinetic models. It is critical to choose an appropriate kinetic model, such as the two- or three-state exchange model, to derive the correct kinetic information. The R2 dispersion and ZZ-exchange methods are suitable for the analysis of protein-ligand interactions with a micromolar or sub-micromolar dissociation constant but not for very weak interactions, which are typical in very fast exchange. This contrasts with the NMR methods that are used to analyze population-averaged NMR quantities. Essentially, to apply NMR successfully, both the type of experiment and equation to fit the data must be carefully and specifically chosen for the protein-ligand interaction under analysis. In this review, we first explain the exchange regimes and kinetic models of protein-ligand interactions, and then describe the NMR methods that quantitatively analyze these specific interactions. Copyright © 2016 Elsevier B.V. All rights reserved.

A new 3D immersed boundary method for non-Newtonian fluid-structure-interaction with application

NASA Astrophysics Data System (ADS)

Zhu, Luoding

2017-11-01

Motivated by fluid-structure-interaction (FSI) phenomena in life sciences (e.g., motions of sperm and cytoskeleton in complex fluids), we introduce a new immersed boundary method for FSI problems involving non-Newtonian fluids in three dimensions. The non-Newtonian fluids are modelled by the FENE-P model (including the Oldroyd-B model as an especial case) and numerically solved by a lattice Boltzmann scheme (the D3Q7 model). The fluid flow is modelled by the lattice Boltzmann equations and numerically solved by the D3Q19 model. The deformable structure and the fluid-structure-interaction are handled by the immersed boundary method. As an application, we study a FSI toy problem - interaction of an elastic plate (flapped at its leading edge and restricted nowhere else) with a non-Newtonian fluid in a 3D flow. Thanks to the support of NSF-DMS support under research Grant 1522554.

Network-Induced Classification Kernels for Gene Expression Profile Analysis

PubMed Central

Dror, Gideon; Shamir, Ron

2012-01-01

Abstract Computational classification of gene expression profiles into distinct disease phenotypes has been highly successful to date. Still, robustness, accuracy, and biological interpretation of the results have been limited, and it was suggested that use of protein interaction information jointly with the expression profiles can improve the results. Here, we study three aspects of this problem. First, we show that interactions are indeed relevant by showing that co-expressed genes tend to be closer in the network of interactions. Second, we show that the improved performance of one extant method utilizing expression and interactions is not really due to the biological information in the network, while in another method this is not the case. Finally, we develop a new kernel method—called NICK—that integrates network and expression data for SVM classification, and demonstrate that overall it achieves better results than extant methods while running two orders of magnitude faster. PMID:22697242

Use of Live Interactive Webcasting for an International Postgraduate Module in eHealth: Case Study Evaluation

PubMed Central

Maramba, Inocencio; Boulos, Maged N Kamel; Alexander, Tara

2009-01-01

Background Producing “traditional” e-learning can be time consuming, and in a topic such as eHealth, it may have a short shelf-life. Students sometimes report feeling isolated and lacking in motivation. Synchronous methods can play an important part in any blended approach to learning. Objective The aim was to develop, deliver, and evaluate an international postgraduate module in eHealth using live interactive webcasting. Methods We developed a hybrid solution for live interactive webcasting using a scan converter, mixer, and digitizer, and video server to embed a presenter-controlled talking head or copy of the presenter’s computer screen (normally a PowerPoint slide) in a student chat room. We recruited 16 students from six countries and ran weekly 2.5-hour live sessions for 10 weeks. The content included the use of computers by patients, patient access to records, different forms of e-learning for patients and professionals, research methods in eHealth, geographic information systems, and telehealth. All sessions were recorded—presentations as video files and the student interaction as text files. Students were sent an email questionnaire of mostly open questions seeking their views of this form of learning. Responses were collated and anonymized by a colleague who was not part of the teaching team. Results Sessions were generally very interactive, with most students participating actively in breakout or full-class discussions. In a typical 2.5-hour session, students posted about 50 messages each. Two students did not complete all sessions; one withdrew from the pressure of work after session 6, and one from illness after session 7. Fourteen of the 16 responded to the feedback questionnaire. Most students (12/14) found the module useful or very useful, and all would recommend the module to others. All liked the method of delivery, in particular the interactivity, the variety of students, and the “closeness” of the group. Most (11/14) felt “connected” with the other students on the course. Many students (11/14) had previous experience with asynchronous e-learning, two as teachers; 12/14 students suggested advantages of synchronous methods, mostly associated with the interaction and feedback from teachers and peers. Conclusions This model of synchronous e-learning based on interactive live webcasting was a successful method of delivering an international postgraduate module. Students found it engaging over a 10-week course. Although this is a small study, given that synchronous methods such as interactive webcasting are a much easier transition for lecturers used to face-to-face teaching than are asynchronous methods, they should be considered as part of the blend of e-learning methods. Further research and development is needed on interfaces and methods that are robust and accessible, on the most appropriate blend of synchronous and asynchronous work for different student groups, and on learning outcomes and effectiveness. PMID:19914901

Prioritization of candidate disease genes by combining topological similarity and semantic similarity.

PubMed

Liu, Bin; Jin, Min; Zeng, Pan

2015-10-01

The identification of gene-phenotype relationships is very important for the treatment of human diseases. Studies have shown that genes causing the same or similar phenotypes tend to interact with each other in a protein-protein interaction (PPI) network. Thus, many identification methods based on the PPI network model have achieved good results. However, in the PPI network, some interactions between the proteins encoded by candidate gene and the proteins encoded by known disease genes are very weak. Therefore, some studies have combined the PPI network with other genomic information and reported good predictive performances. However, we believe that the results could be further improved. In this paper, we propose a new method that uses the semantic similarity between the candidate gene and known disease genes to set the initial probability vector of a random walk with a restart algorithm in a human PPI network. The effectiveness of our method was demonstrated by leave-one-out cross-validation, and the experimental results indicated that our method outperformed other methods. Additionally, our method can predict new causative genes of multifactor diseases, including Parkinson's disease, breast cancer and obesity. The top predictions were good and consistent with the findings in the literature, which further illustrates the effectiveness of our method. Copyright © 2015 Elsevier Inc. All rights reserved.

The Development of Interactive Mathematics Learning Material Based on Local Wisdom with .swf Format

NASA Astrophysics Data System (ADS)

Abadi, M. K.; Asih, E. C. M.; Jupri, A.

2018-05-01

Learning materials used by students and schools in Serang district are lacking because they do not contain local wisdom content. The aim of this study is to improve the deficiencies in learning materials used by students by making interactive materials based on local wisdom content with format .swf. The method in this research is research and development (RnD) with ADDIE model. In making this interactive learning materials in accordance with the stages of the ADDIE study. The results of this study include interactive learning materials based on local wisdom. This learning material is suitable for digital students.

A novel approach to simulate gene-environment interactions in complex diseases.

PubMed

Amato, Roberto; Pinelli, Michele; D'Andrea, Daniel; Miele, Gennaro; Nicodemi, Mario; Raiconi, Giancarlo; Cocozza, Sergio

2010-01-05

Complex diseases are multifactorial traits caused by both genetic and environmental factors. They represent the major part of human diseases and include those with largest prevalence and mortality (cancer, heart disease, obesity, etc.). Despite a large amount of information that has been collected about both genetic and environmental risk factors, there are few examples of studies on their interactions in epidemiological literature. One reason can be the incomplete knowledge of the power of statistical methods designed to search for risk factors and their interactions in these data sets. An improvement in this direction would lead to a better understanding and description of gene-environment interactions. To this aim, a possible strategy is to challenge the different statistical methods against data sets where the underlying phenomenon is completely known and fully controllable, for example simulated ones. We present a mathematical approach that models gene-environment interactions. By this method it is possible to generate simulated populations having gene-environment interactions of any form, involving any number of genetic and environmental factors and also allowing non-linear interactions as epistasis. In particular, we implemented a simple version of this model in a Gene-Environment iNteraction Simulator (GENS), a tool designed to simulate case-control data sets where a one gene-one environment interaction influences the disease risk. The main aim has been to allow the input of population characteristics by using standard epidemiological measures and to implement constraints to make the simulator behaviour biologically meaningful. By the multi-logistic model implemented in GENS it is possible to simulate case-control samples of complex disease where gene-environment interactions influence the disease risk. The user has full control of the main characteristics of the simulated population and a Monte Carlo process allows random variability. A knowledge-based approach reduces the complexity of the mathematical model by using reasonable biological constraints and makes the simulation more understandable in biological terms. Simulated data sets can be used for the assessment of novel statistical methods or for the evaluation of the statistical power when designing a study.

Interaction Equivalency in Self-Paced Online Learning Environments: An Exploration of Learner Preferences

ERIC Educational Resources Information Center

Rhode, Jason F.

2009-01-01

This mixed methods study explored the dynamics of interaction within a self-paced online learning environment. It used rich media and a mix of traditional and emerging asynchronous computer-mediated communication tools to determine what forms of interaction learners in a self-paced online course value most and what impact they perceive interaction…

Evaluation of an Interactive Case-Based Online Network (ICON) in a Problem Based Learning Environment

ERIC Educational Resources Information Center

Nathoo, Arif N.; Goldhoff, Patricia; Quattrochi, James J.

2005-01-01

Purpose: This study sought to assess the introduction of a web-based innovation in medical education that complements traditional problem-based learning curricula. Utilizing the case method as its fundamental educational approach, the Interactive Case-based Online Network (ICON) allows students to interact with each other, faculty and a virtual…

The Validation of an Interactive Videodisc as an Alternative to Traditional Teaching Techniques: Auscultation of the Heart.

ERIC Educational Resources Information Center

Branck, Charles E.; And Others

1987-01-01

This study of 87 veterinary medical students at Auburn University tests the effectiveness and student acceptance of interactive videodisc as an alternative to animal experimentation and other traditional teaching methods in analyzing canine cardiovascular sounds. Results of the questionnaire used are presented, and benefits of interactive video…

The Reliability and Validity of the Dominic Interactive: A Computerized Child Report Instrument for Mental Health Problems

ERIC Educational Resources Information Center

Kuijpers, Rowella C. W. M.; Otten, Roy; Krol, Nicole P. C. M.; Vermulst, Ad A.; Engels, Rutger C. M. E.

2013-01-01

Background: Children and youths' self-report of mental health problems is considered essential but complicated. Objective: This study examines the psychometric properties of the Dominic Interactive, a computerized DSM-IV based self-report questionnaire and explores informant correspondence. Methods: The Dominic Interactive was administered to 214…

Temporal changes in species interactions in simple aquatic bacterial communities

PubMed Central

2012-01-01

Background Organisms modify their environment and in doing so change the quantity and possibly the quality of available resources. Due to the two-way relationship between organisms and their resource environment, and the complexity it brings to biological communities, measuring species interactions reliably in any biological system is a challenging task. As the resource environment changes, the intensity and even the sign of interactions may vary in time. We used Serratia marcescens and Novosphingobium capsulatum bacteria to study how the interaction between resource environment and organisms influence the growth of the bacterial species during circa 200 generations. We used a sterile-filtering method to measure how changes in resource environment are reflected in growth rates of the two species. Results Changes in the resource environment caused complex time and species composition-dependent effects on bacterial growth performance. Variation in the quality of the growth medium indicated existence of temporally fluctuating within-species facilitation and inhibition, and between-species asymmetric facilitation. Conclusions The interactions between the community members could not be fully predicted based only on the knowledge of the growth performance of each member in isolation. Growth dynamics in sterile-filtered samples of the conditioned growth medium can reveal both biologically meaningful changes in resource availability and temporally changing facilitative resource-mediated interactions between study species. This is the first study we are aware of where the filter-sterilization – growth assay method is applied to study the effect of long-term changes in the environment on species interactions. PMID:22984961

Efficacy of Parent-Child Interaction Therapy with Chinese ADHD Children: Randomized Controlled Trial

ERIC Educational Resources Information Center

Leung, Cynthia; Tsang, Sandra; Ng, Gene S. H.; Choi, S. Y.

2017-01-01

Purpose: This study aimed to evaluate the efficacy of Parent-Child Interaction Therapy (PCIT) in Chinese children with attention-deficit/hyperactivity disorder (ADHD) or ADHD features. Methods: This study adopted a randomized controlled trial design without blinding. Participants were randomized into either the intervention group (n = 32) and…

The Social Climate and Peer Interaction on Outdoor Courses

ERIC Educational Resources Information Center

Mirkin, Benjamin J.; Middleton, Michael J.

2014-01-01

This two-study report investigates achievement goal theory in the social domain to gain greater understanding of how the social climate of outdoor courses relates to peer interactions. In Study 1, we used mixed methods to examine how adolescents experienced the social climate of weeklong outdoor courses and how those perceptions related to peer…

Analysis of solute-protein interactions and solute-solute competition by zonal elution affinity chromatography.

PubMed

Tao, Pingyang; Poddar, Saumen; Sun, Zuchen; Hage, David S; Chen, Jianzhong

2018-02-02

Many biological processes involve solute-protein interactions and solute-solute competition for protein binding. One method that has been developed to examine these interactions is zonal elution affinity chromatography. This review discusses the theory and principles of zonal elution affinity chromatography, along with its general applications. Examples of applications that are examined include the use of this method to estimate the relative extent of solute-protein binding, to examine solute-solute competition and displacement from proteins, and to measure the strength of these interactions. It is also shown how zonal elution affinity chromatography can be used in solvent and temperature studies and to characterize the binding sites for solutes on proteins. In addition, several alternative applications of zonal elution affinity chromatography are discussed, which include the analysis of binding by a solute with a soluble binding agent and studies of allosteric effects. Other recent applications that are considered are the combined use of immunoextraction and zonal elution for drug-protein binding studies, and binding studies that are based on immobilized receptors or small targets. Copyright © 2018 Elsevier Inc. All rights reserved.

Effects of interactive teaching on university students’ knowledge and attitude toward reproductive health: a pilot study in Jordan

PubMed Central

Ali, Reem A; Alnatour, Ahlam; Alnuaimi, Karimeh; Alzoubi, Fatmeh; Almomani, Maysa; Othman, Areej

2018-01-01

Background Youths in Jordan lack knowledge related to reproductive health (RH). Interactive teaching methods showed positive results in enhancing health awareness and adopting healthy practices among students. Objectives The objective of this study was to examine the usefulness of interactive teaching in promoting health awareness of RH among nonmedical university students in Jordan. Methods We employed a quasi-experimental one group pretest and posttest design for a purposive sample of 210 students (18–24 years). Knowledge and attitudes regarding RH issues were assessed using a questionnaire developed by the researchers. Results A significant improvement in students’ knowledge and attitudes toward RH was evident. Female students had higher scores on knowledge than male students in the pretest; this difference was smaller in the posttest. Also, female students had significantly more positive attitudes toward RH in pretest than males, although this difference vanished in the posttest. Study results indicated that students benefit from study intervention regardless their gender. Conclusion Integrating RH into university’s curriculum coupled with interactive learning approach is a powerful way to promote RH awareness among youths. PMID:29719404

Short-ranged interaction effects on Z2 topological phase transitions: The perturbative mean-field method

NASA Astrophysics Data System (ADS)

Lai, Hsin-Hua; Hung, Hsiang-Hsuan

2015-02-01

Time-reversal symmetric topological insulator (TI) is a novel state of matter that a bulk-insulating state carries dissipationless spin transport along the surfaces, embedded by the Z2 topological invariant. In the noninteracting limit, this exotic state has been intensively studied and explored with realistic systems, such as HgTe/(Hg, Cd)Te quantum wells. On the other hand, electronic correlation plays a significant role in many solid-state systems, which further influences topological properties and triggers topological phase transitions. Yet an interacting TI is still an elusive subject and most related analyses rely on the mean-field approximation and numerical simulations. Among the approaches, the mean-field approximation fails to predict the topological phase transition, in particular at intermediate interaction strength without spontaneously breaking symmetry. In this paper, we develop an analytical approach based on a combined perturbative and self-consistent mean-field treatment of interactions that is capable of capturing topological phase transitions beyond either method when used independently. As an illustration of the method, we study the effects of short-ranged interactions on the Z2 TI phase, also known as the quantum spin Hall (QSH) phase, in three generalized versions of the Kane-Mele (KM) model at half-filling on the honeycomb lattice. The results are in excellent agreement with quantum Monte Carlo (QMC) calculations on the same model and cannot be reproduced by either a perturbative treatment or a self-consistent mean-field treatment of the interactions. Our analytical approach helps to clarify how the symmetries of the one-body terms of the Hamiltonian determine whether interactions tend to stabilize or destabilize a topological phase. Moreover, our method should be applicable to a wide class of models where topological transitions due to interactions are in principle possible, but are not correctly predicted by either perturbative or self-consistent treatments.

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

Marion, Antoine; Monard, Gérald; Ruiz-López, Manuel F., E-mail: Manuel.Ruiz@univ-lorraine.fr

In this work, we present a study of the ability of different semiempirical methods to describe intermolecular interactions in water solution. In particular, we focus on methods based on the Neglect of Diatomic Differential Overlap approximation. Significant improvements of these methods have been reported in the literature in the past years regarding the description of non-covalent interactions. In particular, a broad range of methodologies has been developed to deal with the properties of hydrogen-bonded systems, with varying degrees of success. In contrast, the interactions between water and a molecule containing hydrophobic groups have been little analyzed. Indeed, by considering themore » potential energy surfaces obtained using different semiempirical Hamiltonians for the intermolecular interactions of model systems, we found that none of the available methods provides an entirely satisfactory description of both hydrophobic and hydrophilic interactions in water. In addition, a vibrational analysis carried out in a model system for these interactions, a methane clathrate cluster, showed that some recent methods cannot be used to carry out studies of vibrational properties. Following a procedure established in our group [M. I. Bernal-Uruchurtu, M. T. C. Martins-Costa, C. Millot, and M. F. Ruiz-López, J. Comput. Chem. 21, 572 (2000); W. Harb, M. I. Bernal-Uruchurtu, and M. F. Ruiz-López, Theor. Chem. Acc. 112, 204 (2004)], we developed new parameters for the core-core interaction terms based on fitting potential energy curves obtained at the MP2 level for our model system. We investigated the transferability of the new parameters to describe a system, having both hydrophilic and hydrophobic groups, interacting with water. We found that only by introducing two different sets of parameters for hydrophilic and hydrophobic hydrogen atom types we are able to match the features of the ab initio calculated properties. Once this assumption is made, a good agreement with the MP2 reference is achieved. The results reported in this work provide therefore a direction for future developments of semiempirical approaches that are still required to investigate chemical processes in biomolecules and in large disordered systems.« less

Quality of the parent-child interaction in young children with type 1 diabetes mellitus: study protocol

PubMed Central

2011-01-01

Background In young children with type 1 diabetes mellitus (T1DM) parents have full responsibility for the diabetes-management of their child (e.g. blood glucose monitoring, and administering insulin). Behavioral tasks in childhood, such as developing autonomy, and oppositional behavior (e.g. refusing food) may interfere with the diabetes-management to achieve an optimal blood glucose control. Furthermore, higher blood glucose levels are related to more behavioral problems. So parents might need to negotiate with their child on the diabetes-management to avoid this direct negative effect. This interference, the negotiations, and the parent's responsibility for diabetes may negatively affect the quality of parent-child interaction. Nevertheless, there is little knowledge about the quality of interaction between parents and young children with T1DM, and the possible impact this may have on glycemic control and psychosocial functioning of the child. While widely used global parent-child interaction observational methods are available, there is a need for an observational tool specifically tailored to the interaction patterns of parents and children with T1DM. The main aim of this study is to construct a disease-specific observational method to assess diabetes-specific parent-child interaction. Additional aim is to explore whether the quality of parent-child interactions is associated with the glycemic control, and psychosocial functioning (resilience, behavioral problems, and quality of life). Methods/Design First, we will examine which situations are most suitable for observing diabetes-specific interactions. Then, these situations will be video-taped in a pilot study (N = 15). Observed behaviors are described into rating scales, with each scale describing characteristics of parent-child interactional behaviors. Next, we apply the observational tool on a larger scale for further evaluation of the instrument (N = 120). The parents are asked twice (with two years in between) to fill out questionnaires about psychosocial functioning of their child with T1DM. Furthermore, glycemic control (HbA1c) will be obtained from their medical records. Discussion A disease-specific observational tool will enable the detailed assessment of the quality of diabetes-specific parent-child interactions. The availability of such a tool will facilitate future (intervention) studies that will yield more knowledge about impact of parent-child interactions on psychosocial functioning, and glycemic control of children with T1DM. PMID:21492413

Protein-Phospholipid Interactions in Nonclassical Protein Secretion: Problem and Methods of Study

PubMed Central

Prudovsky, Igor; Kumar, Thallapuranam Krishnaswamy Suresh; Sterling, Sarah; Neivandt, David

2013-01-01

Extracellular proteins devoid of signal peptides use nonclassical secretion mechanisms for their export. These mechanisms are independent of the endoplasmic reticulum and Golgi. Some nonclassically released proteins, particularly fibroblast growth factors (FGF) 1 and 2, are exported as a result of their direct translocation through the cell membrane. This process requires specific interactions of released proteins with membrane phospholipids. In this review written by a cell biologist, a structural biologist and two membrane engineers, we discuss the following subjects: (i) Phenomenon of nonclassical protein release and its biological significance; (ii) Composition of the FGF1 multiprotein release complex (MRC); (iii) The relationship between FGF1 export and acidic phospholipid externalization; (iv) Interactions of FGF1 MRC components with acidic phospholipids; (v) Methods to study the transmembrane translocation of proteins; (vi) Membrane models to study nonclassical protein release. PMID:23396106

Evolutionary games with coordination and self-dependent interactions

NASA Astrophysics Data System (ADS)

Király, Balázs; Szabó, György

2017-01-01

Multistrategy evolutionary games are studied on a square lattice when the pair interactions are composed of coordinations between strategy pairs and an additional term with self-dependent payoff. We describe a method for determining the strength of each elementary coordination component in n -strategy potential games. Using analytical and numerical methods, the presence and absence of Ising-type order-disorder phase transitions are studied when a single pair coordination is extended by some types of self-dependent elementary games. We also introduce noise-dependent three-strategy equivalents of the n -strategy elementary coordination games.

Correlation effects in superconducting quantum dot systems

NASA Astrophysics Data System (ADS)

Pokorný, Vladislav; Žonda, Martin

2018-05-01

We study the effect of electron correlations on a system consisting of a single-level quantum dot with local Coulomb interaction attached to two superconducting leads. We use the single-impurity Anderson model with BCS superconducting baths to study the interplay between the proximity induced electron pairing and the local Coulomb interaction. We show how to solve the model using the continuous-time hybridization-expansion quantum Monte Carlo method. The results obtained for experimentally relevant parameters are compared with results of self-consistent second order perturbation theory as well as with the numerical renormalization group method.

Adaptation of Tri-molecular fluorescence complementation allows assaying of regulatory Csr RNA-protein interactions in bacteria.

PubMed

Gelderman, Grant; Sivakumar, Anusha; Lipp, Sarah; Contreras, Lydia

2015-02-01

sRNAs play a significant role in controlling and regulating cellular metabolism. One of the more interesting aspects of certain sRNAs is their ability to make global changes in the cell by interacting with regulatory proteins. In this work, we demonstrate the use of an in vivo Tri-molecular Fluorescence Complementation assay to detect and visualize the central regulatory sRNA-protein interaction of the Carbon Storage Regulatory system in E. coli. The Carbon Storage Regulator consists primarily of an RNA binding protein, CsrA, that alters the activity of mRNA targets and of an sRNA, CsrB, that modulates the activity of CsrA. We describe the construction of a fluorescence complementation system that detects the interactions between CsrB and CsrA. Additionally, we demonstrate that the intensity of the fluorescence of this system is able to detect changes in the affinity of the CsrB-CsrA interaction, as caused by mutations in the protein sequence of CsrA. While previous methods have adopted this technique to study mRNA or RNA localization, this is the first attempt to use this technique to study the sRNA-protein interaction directly in bacteria. This method presents a potentially powerful tool to study complex bacterial RNA protein interactions in vivo. © 2014 Wiley Periodicals, Inc.

Tiny moments of great importance: the Marte Meo method applied in the context of early mother-infant interaction and postnatal depression. Utilizing Daniel Stern's theory of 'schemas of being with' in understanding empirical findings and developing a stringent Marte Meo methodology.

PubMed

Vik, Kari; Rohde, Rolf

2014-01-01

This paper provides an overview of basic Marte Meo video interaction guidance concepts and describes the therapeutic performance of the method applied in the context of early mother-infant interaction and postnatal depression. Weight is put upon the importance of the therapeutic relationship. Further Marte Meo therapy is understood in the light of Daniel Stern's theory of 'schemas of being with' and accompanied by clinical vignettes from therapy sessions. The empirical basis for the paper is a study of postnatal depression, mother-infant interaction and video guidance, carried out in Southern Norway. The study examined Marte Meo from a phenomenological perspective. Marte Meo was offered to mothers with either postnatal depression or depressive symptoms. In in-depth interviews the participants reported that the Marte Meo method, 'from the outside looking in', increased their reflections about their infants and their own mental states as well as their sensitive interaction with their newborn. Their mothering was improved and they reported feeling less depressed. We argue that Marte Meo methodology can guide new mothers with depressive symptoms, and contribute to the creation of new schemas of being together.

A Fictitious Domain Method for Resolving the Interaction of Blood Flow with Clot Growth

NASA Astrophysics Data System (ADS)

Mukherjee, Debanjan; Shadden, Shawn

2016-11-01

Thrombosis and thrombo-embolism cause a range of diseases including heart attack and stroke. Closer understanding of clot and blood flow mechanics provides valuable insights on the etiology, diagnosis, and treatment of thrombotic diseases. Such mechanics are complicated, however, by the discrete and multi-scale phenomena underlying thrombosis, and the complex interactions of unsteady, pulsatile hemodynamics with a clot of arbitrary shape and microstructure. We have developed a computational technique, based on a fictitious domain based finite element method, to study these interactions. The method can resolve arbitrary clot geometries, and dynamically couple fluid flow with static or growing clot boundaries. Macroscopic thrombus-hemodynamics interactions were investigated within idealized vessel geometries representative of the common carotid artery, with realistic unsteady flow profiles as inputs. The method was also employed successfully to resolve micro-scale interactions using a model driven by in-vivo morphology data. The results provide insights into the flow structures and hemodynamic loading around an arbitrarily grown clot at arterial length-scales, as well as flow and transport within the interstices of platelet aggregates composing the clot. The work was supported by AHA Award No: 16POST27500023.

Ties That Work: The Interaction between Group Assignment Method and a Culturally-Relevant Curriculum in the Context of Middle School Anti-Tobacco Program

ERIC Educational Resources Information Center

Carolan, Brian V.; Unger, Jennifer B.; Johnson, C. Anderson; Valente, Thomas W.

2007-01-01

Peer-led programs that employ classroom-based group exercises have been shown to be the most effective in preventing adolescent tobacco use. In addition, health promotion programs that include cultural referents have also been shown to be advantageous. The purpose of this study was to test the interaction between the method by which leaders and…

Understanding the Effect of Response Rate and Class Size Interaction on Students Evaluation of Teaching in a Higher Education

ERIC Educational Resources Information Center

Al Kuwaiti, Ahmed; AlQuraan, Mahmoud; Subbarayalu, Arun Vijay

2016-01-01

Objective: This study aims to investigate the interaction between response rate and class size and its effects on students' evaluation of instructors and the courses offered at a higher education Institution in Saudi Arabia. Study Design: A retrospective study design was chosen. Methods: One thousand four hundred and forty four different courses…

Network topological analysis reveals the functional cohesiveness for the newly discovered links by Yeast 2 Hybrid approach

NASA Astrophysics Data System (ADS)

Ghiassian, Susan; Pevzner, Sam; Rolland, Thomas; Tassan, Murat; Barabasi, Albert Laszlo; Vidal, Mark; CCNR, Northeastern University Collaboration; Dana Farber Cancer Institute Collaboration

2014-03-01

Protein-protein interaction maps and interactomes are the blueprint of Network Medicine and systems biology and are being experimentally studied by different groups. Despite the wide usage of Literature Curated Interactome (LCI), these sources are biased towards different parameters such as highly studied proteins. Yeast two hybrid method is a high throughput experimental setup which screens proteins in an unbiased fashion. Current knowledge of protein interactions is far from complete. In fact the previous offered data from Y2H method (2005), is estimated to offer only 5% of all potential protein interactions. Currently this coverage has increased to 20% of what is known as reference HI In this work we study the topological properties of Y2H protein-protein interactions network with LCI and show although they both agree on some properties, LCI shows a clear unbiased nature of interaction selections. Most importantly, we assess the properties of PPI as it evolves with increasing the coverage. We show that, the newly discovered interactions tend to connect proteins that have been closer than average in the previous PPI release. reinforcing the modular structure of PPI. Furthermore, we show, some unseen effects on PPI (as opposed to LCI) can be explained by its incompleteness.

New insights into protein-protein interaction data lead to increased estimates of the S. cerevisiae interactome size.

PubMed

Sambourg, Laure; Thierry-Mieg, Nicolas

2010-12-21

As protein interactions mediate most cellular mechanisms, protein-protein interaction networks are essential in the study of cellular processes. Consequently, several large-scale interactome mapping projects have been undertaken, and protein-protein interactions are being distilled into databases through literature curation; yet protein-protein interaction data are still far from comprehensive, even in the model organism Saccharomyces cerevisiae. Estimating the interactome size is important for evaluating the completeness of current datasets, in order to measure the remaining efforts that are required. We examined the yeast interactome from a new perspective, by taking into account how thoroughly proteins have been studied. We discovered that the set of literature-curated protein-protein interactions is qualitatively different when restricted to proteins that have received extensive attention from the scientific community. In particular, these interactions are less often supported by yeast two-hybrid, and more often by more complex experiments such as biochemical activity assays. Our analysis showed that high-throughput and literature-curated interactome datasets are more correlated than commonly assumed, but that this bias can be corrected for by focusing on well-studied proteins. We thus propose a simple and reliable method to estimate the size of an interactome, combining literature-curated data involving well-studied proteins with high-throughput data. It yields an estimate of at least 37, 600 direct physical protein-protein interactions in S. cerevisiae. Our method leads to higher and more accurate estimates of the interactome size, as it accounts for interactions that are genuine yet difficult to detect with commonly-used experimental assays. This shows that we are even further from completing the yeast interactome map than previously expected.

[POSSIBILITIES OF APPLICATION OF MALDI-TOF MASS-SPECTROMETRY FOR STUDY OF CARBOHYDRATE-SPECIFIC RECEPTORS FOR DIAGNOSTIC BACTERIOPHAGE EL TOR].

PubMed

Telesmanich, N R; Goncharenko, E V; Chaika, S O; Chaika, I A; Telicheva, V O

2016-01-01

Study mechanisms of interaction of diagnostic bacteriophage El Tor with sensitive strain Vibrio cholerae El Tor 18507 using direct protein profiling, identification of constant and variable proteins, taking part in interaction of the phage and cell, as well as carbohydrate-specific phage receptors. . A commercial preparation of cholera diagnostic bacteriophage El Tor, strain V. cholerae El Tor 18507 were used. Effect of carbohydrates on bacteriophage activity was determined in experiments with phage by a classic and modified by us method. Protein profiles of the studied objects were studied using MSP-analysis method. Sucrose was shown to inhibit lytic activity of bacteriophage. Proteome profiles of El Tor bacteriophage and sensitive indicator strains were studied, identification of constant and variable proteins of the studied objects by MSP Peak-list program was carried out. Analysis of changes of profiles of phage and microbial cell during interaction with sucrose gave a basis for assuming, that sucrose in the mixture of culture-phage enters interaction namely with phage protein receptors, blocking receptors specific for cholera vibrio, that subsequently manifests in a sharp decrease of phage activity against the sensitive strain.

Interaction of indole-papaverine with DNA in solutions of various ionic strength

NASA Astrophysics Data System (ADS)

Travkina, V. I.; Moroshkina, E. B.; Osinnikova, D. N.

2017-11-01

Interaction of synthetic alkaloid of isoquinoline series, which is an analogue of the biologically active compound papaverine, was studied by spectral, microcalorimetric, optical and hydrodynamic methods at different ionic strengths of medium. It was found that the investigated compound may interact with DNA in various ways depending on the ratio of ligand - DNA concentrations and ionic strength of solution (μ). When μ = 0.001, indole-papaverine intercalates into the double helix of DNA. The increase of μ resulted in a decrease of the affinity of the compound to DNA and a change its binding method.

Hexahistidine (6xHis) fusion-based assays for protein-protein interactions.

PubMed

Puckett, Mary C

2015-01-01

Fusion-protein tags provide a useful method to study protein-protein interactions. One widely used fusion tag is hexahistidine (6xHis). This tag has unique advantages over others due to its small size and the relatively low abundance of naturally occurring consecutive histidine repeats. 6xHis tags can interact with immobilized metal cations to provide for the capture of proteins and protein complexes of interest. In this chapter, a description of the benefits and uses of 6xHis-fusion proteins as well as a detailed method for performing a 6xHis-pulldown assay are described.

A Method for Overcoming the Problem of Concept-Scale Interaction in Semantic Differential Research

ERIC Educational Resources Information Center

Bynner, John; Romney, David

1972-01-01

Data collected in a study of hospital staff attitudes to drug addicts and other types of patients are used to illustrate the problem of concept-scale interaction in semantic differential research. (Authors)

Mechanism of Coomassie Brilliant Blue G-250 binding to cetyltrimethylammonium bromide: an interference with the Bradford assay.

PubMed

Aminian, Mahdi; Nabatchian, Fariba; Vaisi-Raygani, Asad; Torabi, Mojgan

2013-03-15

The Bradford protein assay is a popular method because of its rapidity, sensitivity, and relative specificity. This method is subject to some interference by nonprotein compounds. In this study, we describe the interference of cetyltrimethylammonium bromide (CTAB) with the Bradford assay. This interference is based on the interaction of Coomassie Brilliant Blue G-250 (CBB) with this cationic detergent. This study suggests that both electrostatic and hydrophobic interactions are involved in the interaction of CTAB and CBB. The anionic and neutral forms of CBB bind to CTAB by electrostatic attraction, which accelerates hydrophobic interactions of these CBB forms and the hydrophobic tail of CTAB. Consequently, the hydrophobic regions of the dominant free cationic form of CBB dye compete for the tail of CTAB with two other forms of the dye and gradually displace the primary hydrophobic interactions and rearrange the primary CBB-CTAB complex. This interaction of CTAB and CBB dye produces a primary 650-nm-absorbing complex that then gradually rearranges to a complex that shows an absorbance shoulder at 800-950 nm. This study conclusively shows a strong response of CBB to CTAB that causes a time-dependent and nearly additive interference with the Bradford assay. This study also may promote an application of CBB for CTAB quantification. Copyright © 2012 Elsevier Inc. All rights reserved.

Computing Normal Shock-Isotropic Turbulence Interaction With Tetrahedral Meshes and the Space-Time CESE Method

NASA Astrophysics Data System (ADS)

Venkatachari, Balaji Shankar; Chang, Chau-Lyan

2016-11-01

The focus of this study is scale-resolving simulations of the canonical normal shock- isotropic turbulence interaction using unstructured tetrahedral meshes and the space-time conservation element solution element (CESE) method. Despite decades of development in unstructured mesh methods and its potential benefits of ease of mesh generation around complex geometries and mesh adaptation, direct numerical or large-eddy simulations of turbulent flows are predominantly carried out using structured hexahedral meshes. This is due to the lack of consistent multi-dimensional numerical formulations in conventional schemes for unstructured meshes that can resolve multiple physical scales and flow discontinuities simultaneously. The CESE method - due to its Riemann-solver-free shock capturing capabilities, non-dissipative baseline schemes, and flux conservation in time as well as space - has the potential to accurately simulate turbulent flows using tetrahedral meshes. As part of the study, various regimes of the shock-turbulence interaction (wrinkled and broken shock regimes) will be investigated along with a study on how adaptive refinement of tetrahedral meshes benefits this problem. The research funding for this paper has been provided by Revolutionary Computational Aerosciences (RCA) subproject under the NASA Transformative Aeronautics Concepts Program (TACP).

The role of environmental heterogeneity in meta-analysis of gene-environment interactions with quantitative traits.

PubMed

Li, Shi; Mukherjee, Bhramar; Taylor, Jeremy M G; Rice, Kenneth M; Wen, Xiaoquan; Rice, John D; Stringham, Heather M; Boehnke, Michael

2014-07-01

With challenges in data harmonization and environmental heterogeneity across various data sources, meta-analysis of gene-environment interaction studies can often involve subtle statistical issues. In this paper, we study the effect of environmental covariate heterogeneity (within and between cohorts) on two approaches for fixed-effect meta-analysis: the standard inverse-variance weighted meta-analysis and a meta-regression approach. Akin to the results in Simmonds and Higgins (), we obtain analytic efficiency results for both methods under certain assumptions. The relative efficiency of the two methods depends on the ratio of within versus between cohort variability of the environmental covariate. We propose to use an adaptively weighted estimator (AWE), between meta-analysis and meta-regression, for the interaction parameter. The AWE retains full efficiency of the joint analysis using individual level data under certain natural assumptions. Lin and Zeng (2010a, b) showed that a multivariate inverse-variance weighted estimator retains full efficiency as joint analysis using individual level data, if the estimates with full covariance matrices for all the common parameters are pooled across all studies. We show consistency of our work with Lin and Zeng (2010a, b). Without sacrificing much efficiency, the AWE uses only univariate summary statistics from each study, and bypasses issues with sharing individual level data or full covariance matrices across studies. We compare the performance of the methods both analytically and numerically. The methods are illustrated through meta-analysis of interaction between Single Nucleotide Polymorphisms in FTO gene and body mass index on high-density lipoprotein cholesterol data from a set of eight studies of type 2 diabetes. © 2014 WILEY PERIODICALS, INC.

The Biomolecular Interaction Network Database and related tools 2005 update

PubMed Central

Alfarano, C.; Andrade, C. E.; Anthony, K.; Bahroos, N.; Bajec, M.; Bantoft, K.; Betel, D.; Bobechko, B.; Boutilier, K.; Burgess, E.; Buzadzija, K.; Cavero, R.; D'Abreo, C.; Donaldson, I.; Dorairajoo, D.; Dumontier, M. J.; Dumontier, M. R.; Earles, V.; Farrall, R.; Feldman, H.; Garderman, E.; Gong, Y.; Gonzaga, R.; Grytsan, V.; Gryz, E.; Gu, V.; Haldorsen, E.; Halupa, A.; Haw, R.; Hrvojic, A.; Hurrell, L.; Isserlin, R.; Jack, F.; Juma, F.; Khan, A.; Kon, T.; Konopinsky, S.; Le, V.; Lee, E.; Ling, S.; Magidin, M.; Moniakis, J.; Montojo, J.; Moore, S.; Muskat, B.; Ng, I.; Paraiso, J. P.; Parker, B.; Pintilie, G.; Pirone, R.; Salama, J. J.; Sgro, S.; Shan, T.; Shu, Y.; Siew, J.; Skinner, D.; Snyder, K.; Stasiuk, R.; Strumpf, D.; Tuekam, B.; Tao, S.; Wang, Z.; White, M.; Willis, R.; Wolting, C.; Wong, S.; Wrong, A.; Xin, C.; Yao, R.; Yates, B.; Zhang, S.; Zheng, K.; Pawson, T.; Ouellette, B. F. F.; Hogue, C. W. V.

2005-01-01

The Biomolecular Interaction Network Database (BIND) (http://bind.ca) archives biomolecular interaction, reaction, complex and pathway information. Our aim is to curate the details about molecular interactions that arise from published experimental research and to provide this information, as well as tools to enable data analysis, freely to researchers worldwide. BIND data are curated into a comprehensive machine-readable archive of computable information and provides users with methods to discover interactions and molecular mechanisms. BIND has worked to develop new methods for visualization that amplify the underlying annotation of genes and proteins to facilitate the study of molecular interaction networks. BIND has maintained an open database policy since its inception in 1999. Data growth has proceeded at a tremendous rate, approaching over 100 000 records. New services provided include a new BIND Query and Submission interface, a Standard Object Access Protocol service and the Small Molecule Interaction Database (http://smid.blueprint.org) that allows users to determine probable small molecule binding sites of new sequences and examine conserved binding residues. PMID:15608229

Macromolecular Competition Titration Method: Accessing Thermodynamics of the Unmodified Macromolecule–Ligand Interactions Through Spectroscopic Titrations of Fluorescent Analogs

PubMed Central

Bujalowski, Wlodzimierz; Jezewska, Maria J.

2011-01-01

Analysis of thermodynamically rigorous binding isotherms provides fundamental information about the energetics of the ligand–macromolecule interactions and often an invaluable insight about the structure of the formed complexes. The Macromolecular Competition Titration (MCT) method enables one to quantitatively obtain interaction parameters of protein–nucleic acid interactions, which may not be available by other methods, particularly for the unmodified long polymer lattices and specific nucleic acid substrates, if the binding is not accompanied by adequate spectroscopic signal changes. The method can be applied using different fluorescent nucleic acids or fluorophores, although the etheno-derivatives of nucleic acid are especially suitable as they are relatively easy to prepare, have significant blue fluorescence, their excitation band lies far from the protein absorption spectrum, and the modification eliminates the possibility of base pairing with other nucleic acids. The MCT method is not limited to the specific size of the reference nucleic acid. Particularly, a simple analysis of the competition titration experiments is described in which the fluorescent, short fragment of nucleic acid, spanning the exact site-size of the protein–nucleic acid complex, and binding with only a 1:1 stoichiometry to the protein, is used as a reference macromolecule. Although the MCT method is predominantly discussed as applied to studying protein–nucleic acid interactions, it can generally be applied to any ligand–macromolecule system by monitoring the association reaction using the spectroscopic signal originating from the reference macromolecule in the presence of the competing macromolecule, whose interaction parameters with the ligand are to be determined. PMID:21195223

Complex molecular assemblies at hand via interactive simulations.

PubMed

Delalande, Olivier; Férey, Nicolas; Grasseau, Gilles; Baaden, Marc

2009-11-30

Studying complex molecular assemblies interactively is becoming an increasingly appealing approach to molecular modeling. Here we focus on interactive molecular dynamics (IMD) as a textbook example for interactive simulation methods. Such simulations can be useful in exploring and generating hypotheses about the structural and mechanical aspects of biomolecular interactions. For the first time, we carry out low-resolution coarse-grain IMD simulations. Such simplified modeling methods currently appear to be more suitable for interactive experiments and represent a well-balanced compromise between an important gain in computational speed versus a moderate loss in modeling accuracy compared to higher resolution all-atom simulations. This is particularly useful for initial exploration and hypothesis development for rare molecular interaction events. We evaluate which applications are currently feasible using molecular assemblies from 1900 to over 300,000 particles. Three biochemical systems are discussed: the guanylate kinase (GK) enzyme, the outer membrane protease T and the soluble N-ethylmaleimide-sensitive factor attachment protein receptors complex involved in membrane fusion. We induce large conformational changes, carry out interactive docking experiments, probe lipid-protein interactions and are able to sense the mechanical properties of a molecular model. Furthermore, such interactive simulations facilitate exploration of modeling parameters for method improvement. For the purpose of these simulations, we have developed a freely available software library called MDDriver. It uses the IMD protocol from NAMD and facilitates the implementation and application of interactive simulations. With MDDriver it becomes very easy to render any particle-based molecular simulation engine interactive. Here we use its implementation in the Gromacs software as an example. Copyright 2009 Wiley Periodicals, Inc.

Interaction Models for Functional Regression.

PubMed

Usset, Joseph; Staicu, Ana-Maria; Maity, Arnab

2016-02-01

A functional regression model with a scalar response and multiple functional predictors is proposed that accommodates two-way interactions in addition to their main effects. The proposed estimation procedure models the main effects using penalized regression splines, and the interaction effect by a tensor product basis. Extensions to generalized linear models and data observed on sparse grids or with measurement error are presented. A hypothesis testing procedure for the functional interaction effect is described. The proposed method can be easily implemented through existing software. Numerical studies show that fitting an additive model in the presence of interaction leads to both poor estimation performance and lost prediction power, while fitting an interaction model where there is in fact no interaction leads to negligible losses. The methodology is illustrated on the AneuRisk65 study data.

Research and Teaching: Implementation of Interactive Engagement Teaching Methods in a Physical Oceanography Course

ERIC Educational Resources Information Center

Keiner, Louis E.; Gilman, Craig

2015-01-01

This study measures the effects of increased faculty-student engagement on student learning, success rates, and perceptions in a Physical Oceanography course. The study separately implemented two teaching methods that had been shown to be successful in a different discipline, introductory physics. These methods were the use of interactive…

Interactive Learning in the Classroom: Is Student Response Method Related to Performance?

ERIC Educational Resources Information Center

Elicker, Joelle D.; McConnell, Nicole L.

2011-01-01

This study examined three methods of responding to in-class multiple-choice concept questions in an Introduction to Psychology course. Specifically, this study compared exam performance and student reactions using three methods of responding to concept questions: (a) a technology-based network system, (b) hand-held flashcards, and (c) hand…

Why Synchrony Matters during Mother-Child Interactions: A Systematic Review

PubMed Central

Leclère, Chloë; Viaux, Sylvie; Avril, Marie; Achard, Catherine; Chetouani, Mohamed; Missonnier, Sylvain; Cohen, David

2014-01-01

Background Assessment of mother-child interactions is a core issue of early child development and psychopathology. This paper focuses on the concept of “synchrony” and examines (1) how synchrony in mother-child interaction is defined and operationalized; (2) the contribution that the concept of synchrony has brought to understanding the nature of mother-child interactions. Method Between 1977 and 2013, we searched several databases using the following key-words: « synchrony » « interaction » and « mother-child ». We focused on studies examining parent-child interactions among children aged 2 months to 5 years. From the 63 relevant studies, we extracted study description variables (authors, year, design, number of subjects, age); assessment conditions and modalities; and main findings. Results The most common terms referring to synchrony were mutuality, reciprocity, rhythmicity, harmonious interaction, turn-taking and shared affect; all terms were used to characterize the mother-child dyad. As a consequence, we propose defining synchrony as a dynamic and reciprocal adaptation of the temporal structure of behaviors and shared affect between interactive partners. Three main types of assessment methods for studying synchrony emerged: (1) global interaction scales with dyadic items; (2) specific synchrony scales; and (3) micro-coded time-series analyses. It appears that synchrony should be regarded as a social signal per se as it has been shown to be valid in both normal and pathological populations. Better mother-child synchrony is associated with familiarity (vs. unknown partner), a healthy mother (vs. pathological mother), typical development (vs. psychopathological development), and a more positive child outcomes. Discussion Synchrony is a key feature of mother-infant interactions. Adopting an objective approach in studying synchrony is not a simple task given available assessment tools and due to its temporality and multimodal expression. We propose an integrative approach combining clinical observation and engineering techniques to improve the quality of synchrony analysis. PMID:25469637

Culture, interpersonal perceptions, and happiness in social interactions.

PubMed

Oishi, Shigehiro; Koo, Minkyung; Akimoto, Sharon

2008-03-01

The authors examined cultural differences in interpersonal processes associated with happiness felt in social interactions. In a false feedback experiment (Study 1a), they found that European Americans felt happier when their interaction partner perceived their personal self accurately, whereas Asian Americans felt happier when their interaction partner perceived their collective self accurately. In Study 1b, the authors further demonstrated that the results from Study 1a were not because of cultural differences in desirability of the traits used in Study 1a. In Studies 2 and 3, they used a 2-week event sampling method and replicated Study 1. Unlike Asian Americans, African Americans were not significantly different from European Americans in the predictors of happiness in social interactions. Together, this research shows that interpersonal affirmation of important aspects of the self leads to happiness and that cultural differences are likely to emerge from the emphasis placed on different aspects of the self.

A quantum description of linear, and non-linear optical interactions in arrays of plasmonic nanoparticles

NASA Astrophysics Data System (ADS)

Arabahmadi, Ehsan; Ahmadi, Zabihollah; Rashidian, Bizhan

2018-06-01

A quantum theory for describing the interaction of photons and plasmons, in one- and two-dimensional arrays is presented. Ohmic losses and inter-band transitions are not considered. We use macroscopic approach, and quantum field theory methods including S-matrix expansion, and Feynman diagrams for this purpose. Non-linear interactions are also studied, and increasing the probability of such interactions, and its application are also discussed.

Drug-target interaction prediction via class imbalance-aware ensemble learning.

PubMed

Ezzat, Ali; Wu, Min; Li, Xiao-Li; Kwoh, Chee-Keong

2016-12-22

Multiple computational methods for predicting drug-target interactions have been developed to facilitate the drug discovery process. These methods use available data on known drug-target interactions to train classifiers with the purpose of predicting new undiscovered interactions. However, a key challenge regarding this data that has not yet been addressed by these methods, namely class imbalance, is potentially degrading the prediction performance. Class imbalance can be divided into two sub-problems. Firstly, the number of known interacting drug-target pairs is much smaller than that of non-interacting drug-target pairs. This imbalance ratio between interacting and non-interacting drug-target pairs is referred to as the between-class imbalance. Between-class imbalance degrades prediction performance due to the bias in prediction results towards the majority class (i.e. the non-interacting pairs), leading to more prediction errors in the minority class (i.e. the interacting pairs). Secondly, there are multiple types of drug-target interactions in the data with some types having relatively fewer members (or are less represented) than others. This variation in representation of the different interaction types leads to another kind of imbalance referred to as the within-class imbalance. In within-class imbalance, prediction results are biased towards the better represented interaction types, leading to more prediction errors in the less represented interaction types. We propose an ensemble learning method that incorporates techniques to address the issues of between-class imbalance and within-class imbalance. Experiments show that the proposed method improves results over 4 state-of-the-art methods. In addition, we simulated cases for new drugs and targets to see how our method would perform in predicting their interactions. New drugs and targets are those for which no prior interactions are known. Our method displayed satisfactory prediction performance and was able to predict many of the interactions successfully. Our proposed method has improved the prediction performance over the existing work, thus proving the importance of addressing problems pertaining to class imbalance in the data.

Impact of risk attitudes and perception on game theoretic driving interactions and safety.

PubMed

Arbis, David; Dixit, Vinayak V; Rashidi, Taha Hossein

2016-09-01

This study employs game theory to investigate behavioural norms of interaction between drivers at a signalised intersection. The choice framework incorporates drivers' risk perception as well as their risk attitudes. A laboratory experiment is conducted to study the impact of risk attitudes and perception in crossing behaviour at a signalised intersection. The laboratory experiment uses methods from experimental economics to induce incentives and study revealed behaviour. Conflicting drivers are considered to have symmetric disincentives for crashing, to represent a no-fault car insurance environment. The study is novel as it uses experimental data collection methods to investigate perceived risk. Further, it directly integrates perceived risk of crashing with other active drivers into the modelling structure. A theoretical model of intersection crossing behaviour is also developed in this paper. This study shows that right-of-way entitlements assigned without authoritative penalties to at-fault drivers may still improve perceptions of safety. Further, risk aversion amongst drivers attributes to manoeuvring strategies at or below Nash mixed strategy equilibrium. These findings offer a theoretical explanation for interactive manoeuvres that lead to crashes, as opposed to purely statistical methods which provide correlation but not necessarily explanation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Finding the best density functional approximation to describe interaction energies and structures of ionic liquids in molecular dynamics studies

NASA Astrophysics Data System (ADS)

Perlt, Eva; Ray, Promit; Hansen, Andreas; Malberg, Friedrich; Grimme, Stefan; Kirchner, Barbara

2018-05-01

Ionic liquids raise interesting but complicated questions for theoretical investigations due to the fact that a number of different inter-molecular interactions, e.g., hydrogen bonding, long-range Coulomb interactions, and dispersion interactions, need to be described properly. Here, we present a detailed study on the ionic liquids ethylammonium nitrate and 1-ethyl-3-methylimidazolium acetate, in which we compare different dispersion corrected density functional approximations to accurate local coupled cluster data in static calculations on ionic liquid clusters. The efficient new composite method B97-3c is tested and has been implemented in CP2K for future studies. Furthermore, tight-binding based approaches which may be used in large scale simulations are assessed. Subsequently, ab initio as well as classical molecular dynamics simulations are conducted and structural analyses are presented in order to shed light on the different short- and long-range structural patterns depending on the method and the system size considered in the simulation. Our results indicate the presence of strong hydrogen bonds in ionic liquids as well as the aggregation of alkyl side chains due to dispersion interactions.

Charmonium-nucleon interactions from the time-dependent HAL QCD method

NASA Astrophysics Data System (ADS)

Sugiura, Takuya; Ikeda, Yoichi; Ishii, Noriyoshi

2018-03-01

The charmonium-nucleon effective central interactions have been computed by the time-dependent HAL QCD method. This gives an updated result of a previous study based on the time-independent method, which is now known to be problematic because of the difficulty in achieving the ground-state saturation. We discuss that the result is consistent with the heavy quark symmetry. No bound state is observed from the analysis of the scattering phase shift; however, this shall lead to a future search of the hidden-charm pentaquarks by considering channel-coupling effects.

Confidence intervals for distinguishing ordinal and disordinal interactions in multiple regression.

PubMed

Lee, Sunbok; Lei, Man-Kit; Brody, Gene H

2015-06-01

Distinguishing between ordinal and disordinal interaction in multiple regression is useful in testing many interesting theoretical hypotheses. Because the distinction is made based on the location of a crossover point of 2 simple regression lines, confidence intervals of the crossover point can be used to distinguish ordinal and disordinal interactions. This study examined 2 factors that need to be considered in constructing confidence intervals of the crossover point: (a) the assumption about the sampling distribution of the crossover point, and (b) the possibility of abnormally wide confidence intervals for the crossover point. A Monte Carlo simulation study was conducted to compare 6 different methods for constructing confidence intervals of the crossover point in terms of the coverage rate, the proportion of true values that fall to the left or right of the confidence intervals, and the average width of the confidence intervals. The methods include the reparameterization, delta, Fieller, basic bootstrap, percentile bootstrap, and bias-corrected accelerated bootstrap methods. The results of our Monte Carlo simulation study suggest that statistical inference using confidence intervals to distinguish ordinal and disordinal interaction requires sample sizes more than 500 to be able to provide sufficiently narrow confidence intervals to identify the location of the crossover point. (c) 2015 APA, all rights reserved).

Interactive performance and focus groups with adolescents: the power of play.

PubMed

Norris, Anne E; Aroian, Karen J; Warren, Stefanie; Wirth, Jeff

2012-12-01

Conducting focus groups with adolescents can be challenging given their developmental needs, particularly with sensitive topics. These challenges include intense need for peer approval, declining social trust, short attention span, and reliance on concrete operations thinking. In this article, we describe an adaptation of interactive performance as an alternative to traditional focus group method. We used this method in a study of discrimination experienced by Muslims (ages 13-17) and of peer pressure to engage in sexual behavior experienced by Hispanic girls (ages 10-14). Recommendations for use of this method include using an interdisciplinary team, planning for large amounts of disclosure towards the end of the focus group, and considering the fit of this method to the study topic. Copyright © 2012 Wiley Periodicals, Inc.

A nonparametric method for assessment of interactions in a median regression model for analyzing right censored data.

PubMed

Lee, MinJae; Rahbar, Mohammad H; Talebi, Hooshang

2018-01-01

We propose a nonparametric test for interactions when we are concerned with investigation of the simultaneous effects of two or more factors in a median regression model with right censored survival data. Our approach is developed to detect interaction in special situations, when the covariates have a finite number of levels with a limited number of observations in each level, and it allows varying levels of variance and censorship at different levels of the covariates. Through simulation studies, we compare the power of detecting an interaction between the study group variable and a covariate using our proposed procedure with that of the Cox Proportional Hazard (PH) model and censored quantile regression model. We also assess the impact of censoring rate and type on the standard error of the estimators of parameters. Finally, we illustrate application of our proposed method to real life data from Prospective Observational Multicenter Major Trauma Transfusion (PROMMTT) study to test an interaction effect between type of injury and study sites using median time for a trauma patient to receive three units of red blood cells. The results from simulation studies indicate that our procedure performs better than both Cox PH model and censored quantile regression model based on statistical power for detecting the interaction, especially when the number of observations is small. It is also relatively less sensitive to censoring rates or even the presence of conditionally independent censoring that is conditional on the levels of covariates.

Interactive forms of conducting business and role games in dialogical training

NASA Astrophysics Data System (ADS)

Medvedeva, L.; Yushkov, E.; Yakovlev, D.; Bogatyreova, M.

2017-01-01

Mastering interactive technologies by teachers of higher educational institutions is the basis of enhancing the quality of education. The competent use of interactive forms of business and role-play games at seminars strengthens a pedagogical effect on the development of the culture of thinking, professional and personal qualities of students, as well as provides an in-depth study of the subject and acquisition of scientific cognition methods. Dialogical thinking creates a truly open mind for sharing opinions and freely discussing suggestions made by the participants, especially in situations of seeking effective task-solving methods. In order to train competitive graduates, ready to act efficiently in their future career, it is necessary to apply innovational interactive technologies in the educational process.

A biomimetic approach to enhancing interfacial interactions: polydopamine-coated clay as reinforcement for epoxy resin.

PubMed

Yang, Liping; Phua, Si Lei; Teo, Jun Kai Herman; Toh, Cher Ling; Lau, Soo Khim; Ma, Jan; Lu, Xuehong

2011-08-01

A facile biomimetic method was developed to enhance the interfacial interaction in polymer-layered silicate nanocomposites. By mimicking mussel adhesive proteins, a monolayer of polydopamine was constructed on clay surface by a controllable coating method. The modified clay (D-clay) was incorporated into an epoxy resin, it is found that the strong interfacial interactions brought by the polydopamine benefits not only the dispersion of the D-clay in the epoxy but also the effective interfacial stress transfer, leading to greatly improved thermomechanical properties at very low inorganic loadings. Rheological and infrared spectroscopic studies show that the interfacial interactions between the D-clay and epoxy are dominated by the hydrogen bonds between the catechol-enriched polydopamine and the epoxy.

Fighting detection using interaction energy force

NASA Astrophysics Data System (ADS)

Wateosot, Chonthisa; Suvonvorn, Nikom

2017-02-01

Fighting detection is an important issue in security aimed to prevent criminal or undesirable events in public places. Many researches on computer vision techniques have studied to detect the specific event in crowded scenes. In this paper we focus on fighting detection using social-based Interaction Energy Force (IEF). The method uses low level features without object extraction and tracking. The interaction force is modeled using the magnitude and direction of optical flows. A fighting factor is developed under this model to detect fighting events using thresholding method. An energy map of interaction force is also presented to identify the corresponding events. The evaluation is performed using NUSHGA and BEHAVE datasets. The results show the efficiency with high accuracy regardless of various conditions.

Molybdenum disulfide and water interaction parameters

NASA Astrophysics Data System (ADS)

Heiranian, Mohammad; Wu, Yanbin; Aluru, Narayana R.

2017-09-01

Understanding the interaction between water and molybdenum disulfide (MoS2) is of crucial importance to investigate the physics of various applications involving MoS2 and water interfaces. An accurate force field is required to describe water and MoS2 interactions. In this work, water-MoS2 force field parameters are derived using the high-accuracy random phase approximation (RPA) method and validated by comparing to experiments. The parameters obtained from the RPA method result in water-MoS2 interface properties (solid-liquid work of adhesion) in good comparison to the experimental measurements. An accurate description of MoS2-water interaction will facilitate the study of MoS2 in applications such as DNA sequencing, sea water desalination, and power generation.

Interweaving interactions in virtual worlds: a case study.

PubMed

Cantamesse, Matteo; Galimberti, Carlo; Giacoma, Gianandrea

2011-01-01

The aim of this study was to examine the effect of playing the online game World of Warcraft (WoW), both on adolescent's (effective) social interaction and on the competence they developed on it. Social interactions within the game environment have been investigated by integrating qualitative and quantitative methods: conversation analysis and social network analysis (SNA). From a psychosocial point of view, the in-game interactions, and in particular conversational exchanges, turn out to be a collaborative path of the joint definition of identities and social ties, with reflection on in-game processes and out-game relationship.

Improved Discovery of Molecular Interactions in Genome-Scale Data with Adaptive Model-Based Normalization

PubMed Central

Brown, Patrick O.

2013-01-01

Background High throughput molecular-interaction studies using immunoprecipitations (IP) or affinity purifications are powerful and widely used in biology research. One of many important applications of this method is to identify the set of RNAs that interact with a particular RNA-binding protein (RBP). Here, the unique statistical challenge presented is to delineate a specific set of RNAs that are enriched in one sample relative to another, typically a specific IP compared to a non-specific control to model background. The choice of normalization procedure critically impacts the number of RNAs that will be identified as interacting with an RBP at a given significance threshold – yet existing normalization methods make assumptions that are often fundamentally inaccurate when applied to IP enrichment data. Methods In this paper, we present a new normalization methodology that is specifically designed for identifying enriched RNA or DNA sequences in an IP. The normalization (called adaptive or AD normalization) uses a basic model of the IP experiment and is not a variant of mean, quantile, or other methodology previously proposed. The approach is evaluated statistically and tested with simulated and empirical data. Results and Conclusions The adaptive (AD) normalization method results in a greatly increased range in the number of enriched RNAs identified, fewer false positives, and overall better concordance with independent biological evidence, for the RBPs we analyzed, compared to median normalization. The approach is also applicable to the study of pairwise RNA, DNA and protein interactions such as the analysis of transcription factors via chromatin immunoprecipitation (ChIP) or any other experiments where samples from two conditions, one of which contains an enriched subset of the other, are studied. PMID:23349766

Power of data mining methods to detect genetic associations and interactions.

PubMed

Molinaro, Annette M; Carriero, Nicholas; Bjornson, Robert; Hartge, Patricia; Rothman, Nathaniel; Chatterjee, Nilanjan

2011-01-01

Genetic association studies, thus far, have focused on the analysis of individual main effects of SNP markers. Nonetheless, there is a clear need for modeling epistasis or gene-gene interactions to better understand the biologic basis of existing associations. Tree-based methods have been widely studied as tools for building prediction models based on complex variable interactions. An understanding of the power of such methods for the discovery of genetic associations in the presence of complex interactions is of great importance. Here, we systematically evaluate the power of three leading algorithms: random forests (RF), Monte Carlo logic regression (MCLR), and multifactor dimensionality reduction (MDR). We use the algorithm-specific variable importance measures (VIMs) as statistics and employ permutation-based resampling to generate the null distribution and associated p values. The power of the three is assessed via simulation studies. Additionally, in a data analysis, we evaluate the associations between individual SNPs in pro-inflammatory and immunoregulatory genes and the risk of non-Hodgkin lymphoma. The power of RF is highest in all simulation models, that of MCLR is similar to RF in half, and that of MDR is consistently the lowest. Our study indicates that the power of RF VIMs is most reliable. However, in addition to tuning parameters, the power of RF is notably influenced by the type of variable (continuous vs. categorical) and the chosen VIM. Copyright © 2011 S. Karger AG, Basel.

A method to assess how interactive water simulation tools influence transdisciplinary decision-making processes in water management

NASA Astrophysics Data System (ADS)

Leskens, Johannes

2015-04-01

In modern water management, often transdisciplinary work sessions are organized in which various stakeholders participate to jointly define problems, choose measures and divide responsibilities to take actions. Involved stakeholders are for example policy analysts or decision-makers from municipalities, water boards or provinces, representatives of pressure groups and researchers from knowledge institutes. Parallel to this increasing attention for transdisciplinary work sessions, we see a growing availability of interactive IT-tools that can be applied during these sessions. For example, dynamic flood risk maps have become recently available that allow users during a work sessions to instantaneously assess the impact of storm surges or dam breaches, displayed on digital maps. Other examples are serious games, realistic visualizations and participatory simulations. However, the question is if and how these interactive IT-tools contribute to better decision-making. To assess this, we take the process of knowledge construction during a work session as a measure for the quality of decision-making. Knowledge construction can be defined as the process in which ideas, perspectives and opinions of different stakeholders, all having their own expertise and experience, are confronted with each other and new shared meanings towards water management issues are created. We present an assessment method to monitor the process of knowledge construction during work sessions in water management in which interactive IT tools are being used. The assessment method is based on a literature review, focusing on studies in which knowledge construction was monitored in other contexts that water management. To test the applicability of the assessment method, we applied it during a multi-stakeholder work session in Westland, located in the southwest of the Netherlands. The discussions during the work session were observed by camera. All statements, expressed by the various members of a stakeholder session, were classified according to our assessment method. We can draw the following preliminary conclusions. First, the case study showed that the method was useful to show the knowledge construction process over time, in terms of content and cognitive level of statements and interaction, attention and response between stakeholders. It was observed that the various aspects of knowledge construction all were influenced by the use of the 3Di model. The model focused discussions on technical issues of flood risk management, non-flood specialists were able to participate in discussions and in suggesting solutions and more topics could be evaluated in respect to non-interactive flood maps. Second, the method is considered useful as a benchmark for different interactive IT tools. The method is also considered useful to gain insight in how to optimally set-up multi-stakeholder meetings in which interactive IT-tools are being used. Further, the method can provide model developers insight in how to better meet the technical requirements of interactive IT tools to support the knowledge construction process during multi-stakeholder meeting

Use of live interactive webcasting for an international postgraduate module in ehealth: case study evaluation.

PubMed

Jones, Ray B; Maramba, Inocencio; Boulos, Maged N Kamel; Alexander, Tara

2009-11-13

Producing "traditional" e-learning can be time consuming, and in a topic such as eHealth, it may have a short shelf-life. Students sometimes report feeling isolated and lacking in motivation. Synchronous methods can play an important part in any blended approach to learning. The aim was to develop, deliver, and evaluate an international postgraduate module in eHealth using live interactive webcasting. We developed a hybrid solution for live interactive webcasting using a scan converter, mixer, and digitizer, and video server to embed a presenter-controlled talking head or copy of the presenter's computer screen (normally a PowerPoint slide) in a student chat room. We recruited 16 students from six countries and ran weekly 2.5-hour live sessions for 10 weeks. The content included the use of computers by patients, patient access to records, different forms of e-learning for patients and professionals, research methods in eHealth, geographic information systems, and telehealth. All sessions were recorded-presentations as video files and the student interaction as text files. Students were sent an email questionnaire of mostly open questions seeking their views of this form of learning. Responses were collated and anonymized by a colleague who was not part of the teaching team. Sessions were generally very interactive, with most students participating actively in breakout or full-class discussions. In a typical 2.5-hour session, students posted about 50 messages each. Two students did not complete all sessions; one withdrew from the pressure of work after session 6, and one from illness after session 7. Fourteen of the 16 responded to the feedback questionnaire. Most students (12/14) found the module useful or very useful, and all would recommend the module to others. All liked the method of delivery, in particular the interactivity, the variety of students, and the "closeness" of the group. Most (11/14) felt "connected" with the other students on the course. Many students (11/14) had previous experience with asynchronous e-learning, two as teachers; 12/14 students suggested advantages of synchronous methods, mostly associated with the interaction and feedback from teachers and peers. This model of synchronous e-learning based on interactive live webcasting was a successful method of delivering an international postgraduate module. Students found it engaging over a 10-week course. Although this is a small study, given that synchronous methods such as interactive webcasting are a much easier transition for lecturers used to face-to-face teaching than are asynchronous methods, they should be considered as part of the blend of e-learning methods. Further research and development is needed on interfaces and methods that are robust and accessible, on the most appropriate blend of synchronous and asynchronous work for different student groups, and on learning outcomes and effectiveness.

Method of assessing parent-child grocery store purchasing interactions using a micro-camcorder.

PubMed

Calloway, Eric E; Roberts-Gray, Cindy; Ranjit, Nalini; Sweitzer, Sara J; McInnis, Katie A; Romo-Palafox, Maria J; Briley, Margaret E

2014-12-01

The purpose of this study was to assess the validity of using participant worn micro-camcorders (PWMC) to collect data on parent-child food and beverage purchasing interactions in the grocery store. Parent-child dyads (n = 32) were met at their usual grocery store and shopping time. Parents were mostly Caucasian (n = 27, 84.4%), mothers (n = 30, 93.8%). Children were 2-6 years old with 15 girls and 17 boys. A micro-camcorder was affixed to a baseball style hat worn by the child. The dyad proceeded to shop while being shadowed by an in-person observer. Video/audio data were coded for behavioral and environmental variables. The PWMC method was compared to in-person observation to assess sensitivity and relative validity for measuring parent-child interactions, and compared to receipt data to assess criterion validity for evaluating purchasing decisions. Inter-rater reliability for coding video/audio data collected using the PWMC method was also assessed. The PWMC method proved to be more sensitive than in-person observation revealing on average 1.4 (p < 0.01) more parent-child food and beverage purchasing interactions per shopping trip. Inter-rater reliability for coding PWMC data showed moderate to almost perfect agreement (Cohen's kappa = 0.461-0.937). The PWMC method was significantly correlated with in-person observation for measuring occurrences of parent-child food purchasing interactions (rho = 0.911, p < 0.01) and characteristics of those interactions (rho = 0.345-0.850, p < 0.01). Additionally, there was substantial agreement between the PWMC method and receipt data for measuring purchasing decisions (Cohen's kappa = 0.787). The PWMC method proved to be well suited to assess parent-child food and beverage purchasing interactions in the grocery store. Copyright © 2014 Elsevier Ltd. All rights reserved.

Correlation between safety assessments in the driver-car interaction design process.

PubMed

Broström, Robert; Bengtsson, Peter; Axelsson, Jakob

2011-05-01

With the functional revolution in modern cars, evaluation methods to be used in all phases of driver-car interaction design have gained importance. It is crucial for car manufacturers to discover and solve safety issues early in the interaction design process. A current problem is thus to find a correlation between the formative methods that are used during development and the summative methods that are used when the product has reached the customer. This paper investigates the correlation between efficiency metrics from summative and formative evaluations, where the results of two studies on sound and navigation system tasks are compared. The first, an analysis of the J.D. Power and Associates APEAL survey, consists of answers given by about two thousand customers. The second, an expert evaluation study, was done by six evaluators who assessed the layouts by task completion time, TLX and Nielsen heuristics. The results show a high degree of correlation between the studies in terms of task efficiency, i.e. between customer ratings and task completion time, and customer ratings and TLX. However, no correlation was observed between Nielsen heuristics and customer ratings, task completion time or TLX. The results of the studies introduce a possibility to develop a usability evaluation framework that includes both formative and summative approaches, as the results show a high degree of consistency between the different methodologies. Hence, combining a quantitative approach with the expert evaluation method, such as task completion time, should be more useful for driver-car interaction design. Copyright © 2010 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Predicting permanent and transient protein-protein interfaces.

PubMed

La, David; Kong, Misun; Hoffman, William; Choi, Youn Im; Kihara, Daisuke

2013-05-01

Protein-protein interactions (PPIs) are involved in diverse functions in a cell. To optimize functional roles of interactions, proteins interact with a spectrum of binding affinities. Interactions are conventionally classified into permanent and transient, where the former denotes tight binding between proteins that result in strong complexes, whereas the latter compose of relatively weak interactions that can dissociate after binding to regulate functional activity at specific time point. Knowing the type of interactions has significant implications for understanding the nature and function of PPIs. In this study, we constructed amino acid substitution models that capture mutation patterns at permanent and transient type of protein interfaces, which were found to be different with statistical significance. Using the substitution models, we developed a novel computational method that predicts permanent and transient protein binding interfaces (PBIs) in protein surfaces. Without knowledge of the interacting partner, the method uses a single query protein structure and a multiple sequence alignment of the sequence family. Using a large dataset of permanent and transient proteins, we show that our method, BindML+, performs very well in protein interface classification. A very high area under the curve (AUC) value of 0.957 was observed when predicted protein binding sites were classified. Remarkably, near prefect accuracy was achieved with an AUC of 0.991 when actual binding sites were classified. The developed method will be also useful for protein design of permanent and transient PBIs. Copyright © 2013 Wiley Periodicals, Inc.

Analysis and Identification of Aptamer-Compound Interactions with a Maximum Relevance Minimum Redundancy and Nearest Neighbor Algorithm

PubMed Central

Wang, ShaoPeng; Zhang, Yu-Hang; Lu, Jing; Cui, Weiren; Hu, Jerry; Cai, Yu-Dong

2016-01-01

The development of biochemistry and molecular biology has revealed an increasingly important role of compounds in several biological processes. Like the aptamer-protein interaction, aptamer-compound interaction attracts increasing attention. However, it is time-consuming to select proper aptamers against compounds using traditional methods, such as exponential enrichment. Thus, there is an urgent need to design effective computational methods for searching effective aptamers against compounds. This study attempted to extract important features for aptamer-compound interactions using feature selection methods, such as Maximum Relevance Minimum Redundancy, as well as incremental feature selection. Each aptamer-compound pair was represented by properties derived from the aptamer and compound, including frequencies of single nucleotides and dinucleotides for the aptamer, as well as the constitutional, electrostatic, quantum-chemical, and space conformational descriptors of the compounds. As a result, some important features were obtained. To confirm the importance of the obtained features, we further discussed the associations between them and aptamer-compound interactions. Simultaneously, an optimal prediction model based on the nearest neighbor algorithm was built to identify aptamer-compound interactions, which has the potential to be a useful tool for the identification of novel aptamer-compound interactions. The program is available upon the request. PMID:26955638

Analysis and Identification of Aptamer-Compound Interactions with a Maximum Relevance Minimum Redundancy and Nearest Neighbor Algorithm.

PubMed

Wang, ShaoPeng; Zhang, Yu-Hang; Lu, Jing; Cui, Weiren; Hu, Jerry; Cai, Yu-Dong

2016-01-01

The development of biochemistry and molecular biology has revealed an increasingly important role of compounds in several biological processes. Like the aptamer-protein interaction, aptamer-compound interaction attracts increasing attention. However, it is time-consuming to select proper aptamers against compounds using traditional methods, such as exponential enrichment. Thus, there is an urgent need to design effective computational methods for searching effective aptamers against compounds. This study attempted to extract important features for aptamer-compound interactions using feature selection methods, such as Maximum Relevance Minimum Redundancy, as well as incremental feature selection. Each aptamer-compound pair was represented by properties derived from the aptamer and compound, including frequencies of single nucleotides and dinucleotides for the aptamer, as well as the constitutional, electrostatic, quantum-chemical, and space conformational descriptors of the compounds. As a result, some important features were obtained. To confirm the importance of the obtained features, we further discussed the associations between them and aptamer-compound interactions. Simultaneously, an optimal prediction model based on the nearest neighbor algorithm was built to identify aptamer-compound interactions, which has the potential to be a useful tool for the identification of novel aptamer-compound interactions. The program is available upon the request.

Beyond the Flipped Classroom: A Highly Interactive Cloud-Classroom (HIC) Embedded into Basic Materials Science Courses

ERIC Educational Resources Information Center

Liou, Wei-Kai; Bhagat, Kaushal Kumar; Chang, Chun-Yen

2016-01-01

The present study compares the highly interactive cloud-classroom (HIC) system with traditional methods of teaching materials science that utilize crystal structure picture or real crystal structure model, in order to examine its learning effectiveness across three dimensions: knowledge, comprehension and application. The aim of this study was to…

Towards a Pedagogy of Humanizing Child Education in Terms of Teacher-Student Interaction

ERIC Educational Resources Information Center

Shih, Yi-Huang

2018-01-01

By reading and analyzing related studies, this article investigates methods for humanizing child education in terms of teacher-student interaction. It is hoped that this study will allow teachers to understand the essence of child education, to become better educators and humanizing child education, so that students can develop a healthy body and…

The Effect of Interactive Technology on Informal Learning and Performance in a Social Setting

ERIC Educational Resources Information Center

Boileau, Timothy

2011-01-01

This study is based on a qualitative multiple case study research design using a mixed methods approach to provide insight into the effect of interactive technology on informal learning and performance in a social business setting inhabited by knowledge workers. The central phenomenon examined is the variance in behavioral intention towards…

Quantitative Research Methods, Study Quality, and Outcomes: The Case of Interaction Research

ERIC Educational Resources Information Center

Plonsky, Luke; Gass, Susan

2011-01-01

This article constitutes the first empirical assessment of methodological quality in second language acquisition (SLA). We surveyed a corpus of 174 studies (N = 7,951) within the tradition of research on second-language interaction, one of the longest and most influential traditions of inquiry in SLA. Each report was coded for methodological…

Personality, Study Methods and Academic Performance

ERIC Educational Resources Information Center

Entwistle, N. J.; Wilson, J. D.

1970-01-01

A questionnaire measuring four student personality types--stable introvert, unstable introvert, stable extrovert and unstable extrovert--along with the Eysenck Personality Inventory (Form A) were give to 72 graduate students at Aberdeen University and the results showed recognizable interaction between study methods, motivation and personality…

Characterizing the topology of probabilistic biological networks.

PubMed

Todor, Andrei; Dobra, Alin; Kahveci, Tamer

2013-01-01

Biological interactions are often uncertain events, that may or may not take place with some probability. This uncertainty leads to a massive number of alternative interaction topologies for each such network. The existing studies analyze the degree distribution of biological networks by assuming that all the given interactions take place under all circumstances. This strong and often incorrect assumption can lead to misleading results. In this paper, we address this problem and develop a sound mathematical basis to characterize networks in the presence of uncertain interactions. Using our mathematical representation, we develop a method that can accurately describe the degree distribution of such networks. We also take one more step and extend our method to accurately compute the joint-degree distributions of node pairs connected by edges. The number of possible network topologies grows exponentially with the number of uncertain interactions. However, the mathematical model we develop allows us to compute these degree distributions in polynomial time in the number of interactions. Our method works quickly even for entire protein-protein interaction (PPI) networks. It also helps us find an adequate mathematical model using MLE. We perform a comparative study of node-degree and joint-degree distributions in two types of biological networks: the classical deterministic networks and the more flexible probabilistic networks. Our results confirm that power-law and log-normal models best describe degree distributions for both probabilistic and deterministic networks. Moreover, the inverse correlation of degrees of neighboring nodes shows that, in probabilistic networks, nodes with large number of interactions prefer to interact with those with small number of interactions more frequently than expected. We also show that probabilistic networks are more robust for node-degree distribution computation than the deterministic ones. all the data sets used, the software implemented and the alignments found in this paper are available at http://bioinformatics.cise.ufl.edu/projects/probNet/.

Mapping protein-RNA interactions by RCAP, RNA-cross-linking and peptide fingerprinting.

PubMed

Vaughan, Robert C; Kao, C Cheng

2015-01-01

RNA nanotechnology often feature protein RNA complexes. The interaction between proteins and large RNAs are difficult to study using traditional structure-based methods like NMR or X-ray crystallography. RCAP, an approach that uses reversible-cross-linking affinity purification method coupled with mass spectrometry, has been developed to map regions within proteins that contact RNA. This chapter details how RCAP is applied to map protein-RNA contacts within virions.

iLOCi: a SNP interaction prioritization technique for detecting epistasis in genome-wide association studies

PubMed Central

2012-01-01

Background Genome-wide association studies (GWAS) do not provide a full account of the heritability of genetic diseases since gene-gene interactions, also known as epistasis are not considered in single locus GWAS. To address this problem, a considerable number of methods have been developed for identifying disease-associated gene-gene interactions. However, these methods typically fail to identify interacting markers explaining more of the disease heritability over single locus GWAS, since many of the interactions significant for disease are obscured by uninformative marker interactions e.g., linkage disequilibrium (LD). Results In this study, we present a novel SNP interaction prioritization algorithm, named iLOCi (Interacting Loci). This algorithm accounts for marker dependencies separately in case and control groups. Disease-associated interactions are then prioritized according to a novel ranking score calculated from the difference in marker dependencies for every possible pair between case and control groups. The analysis of a typical GWAS dataset can be completed in less than a day on a standard workstation with parallel processing capability. The proposed framework was validated using simulated data and applied to real GWAS datasets using the Wellcome Trust Case Control Consortium (WTCCC) data. The results from simulated data showed the ability of iLOCi to identify various types of gene-gene interactions, especially for high-order interaction. From the WTCCC data, we found that among the top ranked interacting SNP pairs, several mapped to genes previously known to be associated with disease, and interestingly, other previously unreported genes with biologically related roles. Conclusion iLOCi is a powerful tool for uncovering true disease interacting markers and thus can provide a more complete understanding of the genetic basis underlying complex disease. The program is available for download at http://www4a.biotec.or.th/GI/tools/iloci. PMID:23281813

Combining multiple positive training sets to generate confidence scores for protein-protein interactions.

PubMed

Yu, Jingkai; Finley, Russell L

2009-01-01

High-throughput experimental and computational methods are generating a wealth of protein-protein interaction data for a variety of organisms. However, data produced by current state-of-the-art methods include many false positives, which can hinder the analyses needed to derive biological insights. One way to address this problem is to assign confidence scores that reflect the reliability and biological significance of each interaction. Most previously described scoring methods use a set of likely true positives to train a model to score all interactions in a dataset. A single positive training set, however, may be biased and not representative of true interaction space. We demonstrate a method to score protein interactions by utilizing multiple independent sets of training positives to reduce the potential bias inherent in using a single training set. We used a set of benchmark yeast protein interactions to show that our approach outperforms other scoring methods. Our approach can also score interactions across data types, which makes it more widely applicable than many previously proposed methods. We applied the method to protein interaction data from both Drosophila melanogaster and Homo sapiens. Independent evaluations show that the resulting confidence scores accurately reflect the biological significance of the interactions.

Evaluation of the binding interaction between bovine serum albumin and dimethyl fumarate, an anti-inflammatory drug by multispectroscopic methods

NASA Astrophysics Data System (ADS)

Jattinagoudar, Laxmi; Meti, Manjunath; Nandibewoor, Sharanappa; Chimatadar, Shivamurti

2016-03-01

The information of the quenching reaction of bovine serum albumin with dimethyl fumarate is obtained by multi-spectroscopic methods. The number of binding sites, n and binding constants, KA were determined at different temperatures. The effect of increasing temperature on Stern-Volmer quenching constants (KD) indicates that a dynamic quenching mechanism is involved in the interaction. The analysis of thermodynamic quantities namely, ∆H° and ∆S° suggested hydrophobic forces playing a major role in the interaction between dimethyl fumarate and bovine serum albumin. The binding site of dimethyl fumarate on bovine serum albumin was determined by displacement studies, using the site probes viz., warfarin, ibuprofen and digitoxin. The determination of magnitude of the distance of approach for molecular interactions between dimethyl fumarate and bovine serum albumin is calculated according to the theory of Förster energy transfer. The CD, 3D fluorescence spectra, synchronous fluorescence measurements and FT-IR spectral results were indicative of the change in secondary structure of the protein. The influence of some of the metal ions on the binding interaction was also studied.

Predicting microRNA-disease associations using label propagation based on linear neighborhood similarity.

PubMed

Li, Guanghui; Luo, Jiawei; Xiao, Qiu; Liang, Cheng; Ding, Pingjian

2018-05-12

Interactions between microRNAs (miRNAs) and diseases can yield important information for uncovering novel prognostic markers. Since experimental determination of disease-miRNA associations is time-consuming and costly, attention has been given to designing efficient and robust computational techniques for identifying undiscovered interactions. In this study, we present a label propagation model with linear neighborhood similarity, called LPLNS, to predict unobserved miRNA-disease associations. Additionally, a preprocessing step is performed to derive new interaction likelihood profiles that will contribute to the prediction since new miRNAs and diseases lack known associations. Our results demonstrate that the LPLNS model based on the known disease-miRNA associations could achieve impressive performance with an AUC of 0.9034. Furthermore, we observed that the LPLNS model based on new interaction likelihood profiles could improve the performance to an AUC of 0.9127. This was better than other comparable methods. In addition, case studies also demonstrated our method's outstanding performance for inferring undiscovered interactions between miRNAs and diseases, especially for novel diseases. Copyright © 2018. Published by Elsevier Inc.

Time-course, negative-stain electron microscopy–based analysis for investigating protein–protein interactions at the single-molecule level

PubMed Central

Nogal, Bartek; Bowman, Charles A.; Ward, Andrew B.

2017-01-01

Several biophysical approaches are available to study protein–protein interactions. Most approaches are conducted in bulk solution, and are therefore limited to an average measurement of the ensemble of molecular interactions. Here, we show how single-particle EM can enrich our understanding of protein–protein interactions at the single-molecule level and potentially capture states that are unobservable with ensemble methods because they are below the limit of detection or not conducted on an appropriate time scale. Using the HIV-1 envelope glycoprotein (Env) and its interaction with receptor CD4-binding site neutralizing antibodies as a model system, we both corroborate ensemble kinetics-derived parameters and demonstrate how time-course EM can further dissect stoichiometric states of complexes that are not readily observable with other methods. Visualization of the kinetics and stoichiometry of Env–antibody complexes demonstrated the applicability of our approach to qualitatively and semi-quantitatively differentiate two highly similar neutralizing antibodies. Furthermore, implementation of machine-learning techniques for sorting class averages of these complexes into discrete subclasses of particles helped reduce human bias. Our data provide proof of concept that single-particle EM can be used to generate a “visual” kinetic profile that should be amenable to studying many other protein–protein interactions, is relatively simple and complementary to well-established biophysical approaches. Moreover, our method provides critical insights into broadly neutralizing antibody recognition of Env, which may inform vaccine immunogen design and immunotherapeutic development. PMID:28972148

EPIBLASTER-fast exhaustive two-locus epistasis detection strategy using graphical processing units

PubMed Central

Kam-Thong, Tony; Czamara, Darina; Tsuda, Koji; Borgwardt, Karsten; Lewis, Cathryn M; Erhardt-Lehmann, Angelika; Hemmer, Bernhard; Rieckmann, Peter; Daake, Markus; Weber, Frank; Wolf, Christiane; Ziegler, Andreas; Pütz, Benno; Holsboer, Florian; Schölkopf, Bernhard; Müller-Myhsok, Bertram

2011-01-01

Detection of epistatic interaction between loci has been postulated to provide a more in-depth understanding of the complex biological and biochemical pathways underlying human diseases. Studying the interaction between two loci is the natural progression following traditional and well-established single locus analysis. However, the added costs and time duration required for the computation involved have thus far deterred researchers from pursuing a genome-wide analysis of epistasis. In this paper, we propose a method allowing such analysis to be conducted very rapidly. The method, dubbed EPIBLASTER, is applicable to case–control studies and consists of a two-step process in which the difference in Pearson's correlation coefficients is computed between controls and cases across all possible SNP pairs as an indication of significant interaction warranting further analysis. For the subset of interactions deemed potentially significant, a second-stage analysis is performed using the likelihood ratio test from the logistic regression to obtain the P-value for the estimated coefficients of the individual effects and the interaction term. The algorithm is implemented using the parallel computational capability of commercially available graphical processing units to greatly reduce the computation time involved. In the current setup and example data sets (211 cases, 222 controls, 299468 SNPs; and 601 cases, 825 controls, 291095 SNPs), this coefficient evaluation stage can be completed in roughly 1 day. Our method allows for exhaustive and rapid detection of significant SNP pair interactions without imposing significant marginal effects of the single loci involved in the pair. PMID:21150885

Investigation of interaction studies of cefpirome with ACE-inhibitors in various buffers

NASA Astrophysics Data System (ADS)

Nawaz, Muhammad; Arayne, Muhammad Saeed; Sultana, Najma; Abbas, Hira Fatima

2015-02-01

This work describes a RP-HPLC method for the determination and interaction studies of cefpirome with ACE-inhibitors (captopril, enalapril and lisinopril) in various buffers. The separation and interaction of cefpirome with ACE-inhibitors was achieved on a Purospher Star, C18 (5 μm, 250 × 4.6 mm) column. Mobile phase consisted of methanol: water (80:20, v/v, pH 3.3); however, for the separation of lisinopril, it was modified to methanol-water (40:60, v/v, pH 3.3) and pumped at a flow rate of 1 mL min-1. In all cases, UV detection was performed at 225 nm. Interactions were carried out in physiological pH i.e., pH 1 (simulated gastric juice), 4 (simulated full stomach), 7.4 (blood pH) and 9 (simulated GI), drug contents were analyzed by reverse phase high performance liquid chromatography. Method was found linear in the concentration range of 1.0-50.0 μg mL-1 with correlation coefficient (r2) of 0.999. Precision (RSD%) was less than 2.0%, indicating good precision of the method and accuracy was 98.0-100.0%. Furthermore, cefpirome-ACE-inhibitors' complexes were also synthesized and results were elucidated on the basis of FT-IR, and 1H NMR. The interaction results show that these interactions are pH dependent and for the co-administration of cefpirome and ACE-inhibitors, a proper interval should be given.

Using resonance light scattering and UV/vis absorption spectroscopy to study the interaction between gliclazide and bovine serum albumin.

PubMed

Zhang, Qiu-Ju; Liu, Bao-Sheng; Li, Gai-Xia; Han, Rong

2016-08-01

At different temperatures (298, 310 and 318 K), the interaction between gliclazide and bovine serum albumin (BSA) was investigated using fluorescence quenching spectroscopy, resonance light scattering spectroscopy and UV/vis absorption spectroscopy. The first method studied changes in the fluorescence of BSA on addition of gliclazide, and the latter two methods studied the spectral change in gliclazide while BSA was being added. The results indicated that the quenching mechanism between BSA and gliclazide was static. The binding constant (Ka ), number of binding sites (n), thermodynamic parameters, binding forces and Hill's coefficient were calculated at three temperatures. Values for the binding constant obtained using resonance light scattering and UV/vis absorption spectroscopy were much greater than those obtained from fluorescence quenching spectroscopy, indicating that methods monitoring gliclazide were more accurate and reasonable. In addition, the results suggest that other residues are involved in the reaction and the mode 'point to surface' existed in the interaction between BSA and gliclazide. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Using video-based observation research methods in primary care health encounters to evaluate complex interactions.

PubMed

Asan, Onur; Montague, Enid

2014-01-01

The purpose of this paper is to describe the use of video-based observation research methods in primary care environment and highlight important methodological considerations and provide practical guidance for primary care and human factors researchers conducting video studies to understand patient-clinician interaction in primary care settings. We reviewed studies in the literature which used video methods in health care research, and we also used our own experience based on the video studies we conducted in primary care settings. This paper highlighted the benefits of using video techniques, such as multi-channel recording and video coding, and compared "unmanned" video recording with the traditional observation method in primary care research. We proposed a list that can be followed step by step to conduct an effective video study in a primary care setting for a given problem. This paper also described obstacles, researchers should anticipate when using video recording methods in future studies. With the new technological improvements, video-based observation research is becoming a promising method in primary care and HFE research. Video recording has been under-utilised as a data collection tool because of confidentiality and privacy issues. However, it has many benefits as opposed to traditional observations, and recent studies using video recording methods have introduced new research areas and approaches.

A Comparative Study on Multifactor Dimensionality Reduction Methods for Detecting Gene-Gene Interactions with the Survival Phenotype

PubMed Central

Lee, Seungyeoun; Kim, Yongkang; Kwon, Min-Seok; Park, Taesung

2015-01-01

Genome-wide association studies (GWAS) have extensively analyzed single SNP effects on a wide variety of common and complex diseases and found many genetic variants associated with diseases. However, there is still a large portion of the genetic variants left unexplained. This missing heritability problem might be due to the analytical strategy that limits analyses to only single SNPs. One of possible approaches to the missing heritability problem is to consider identifying multi-SNP effects or gene-gene interactions. The multifactor dimensionality reduction method has been widely used to detect gene-gene interactions based on the constructive induction by classifying high-dimensional genotype combinations into one-dimensional variable with two attributes of high risk and low risk for the case-control study. Many modifications of MDR have been proposed and also extended to the survival phenotype. In this study, we propose several extensions of MDR for the survival phenotype and compare the proposed extensions with earlier MDR through comprehensive simulation studies. PMID:26339630

Analysis of Tire Tractive Performance on Deformable Terrain by Finite Element-Discrete Element Method

NASA Astrophysics Data System (ADS)

Nakashima, Hiroshi; Takatsu, Yuzuru

The goal of this study is to develop a practical and fast simulation tool for soil-tire interaction analysis, where finite element method (FEM) and discrete element method (DEM) are coupled together, and which can be realized on a desktop PC. We have extended our formerly proposed dynamic FE-DE method (FE-DEM) to include practical soil-tire system interaction, where not only the vertical sinkage of a tire, but also the travel of a driven tire was considered. Numerical simulation by FE-DEM is stable, and the relationships between variables, such as load-sinkage and sinkage-travel distance, and the gross tractive effort and running resistance characteristics, are obtained. Moreover, the simulation result is accurate enough to predict the maximum drawbar pull for a given tire, once the appropriate parameter values are provided. Therefore, the developed FE-DEM program can be applied with sufficient accuracy to interaction problems in soil-tire systems.

A cut-cell finite volume – finite element coupling approach for fluid–structure interaction in compressible flow

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

Pasquariello, Vito, E-mail: vito.pasquariello@tum.de; Hammerl, Georg; Örley, Felix

2016-02-15

We present a loosely coupled approach for the solution of fluid–structure interaction problems between a compressible flow and a deformable structure. The method is based on staggered Dirichlet–Neumann partitioning. The interface motion in the Eulerian frame is accounted for by a conservative cut-cell Immersed Boundary method. The present approach enables sub-cell resolution by considering individual cut-elements within a single fluid cell, which guarantees an accurate representation of the time-varying solid interface. The cut-cell procedure inevitably leads to non-matching interfaces, demanding for a special treatment. A Mortar method is chosen in order to obtain a conservative and consistent load transfer. Wemore » validate our method by investigating two-dimensional test cases comprising a shock-loaded rigid cylinder and a deformable panel. Moreover, the aeroelastic instability of a thin plate structure is studied with a focus on the prediction of flutter onset. Finally, we propose a three-dimensional fluid–structure interaction test case of a flexible inflated thin shell interacting with a shock wave involving large and complex structural deformations.« less

Functional connectivity analysis of the neural bases of emotion regulation: A comparison of independent component method with density-based k-means clustering method.

PubMed

Zou, Ling; Guo, Qian; Xu, Yi; Yang, Biao; Jiao, Zhuqing; Xiang, Jianbo

2016-04-29

Functional magnetic resonance imaging (fMRI) is an important tool in neuroscience for assessing connectivity and interactions between distant areas of the brain. To find and characterize the coherent patterns of brain activity as a means of identifying brain systems for the cognitive reappraisal of the emotion task, both density-based k-means clustering and independent component analysis (ICA) methods can be applied to characterize the interactions between brain regions involved in cognitive reappraisal of emotion. Our results reveal that compared with the ICA method, the density-based k-means clustering method provides a higher sensitivity of polymerization. In addition, it is more sensitive to those relatively weak functional connection regions. Thus, the study concludes that in the process of receiving emotional stimuli, the relatively obvious activation areas are mainly distributed in the frontal lobe, cingulum and near the hypothalamus. Furthermore, density-based k-means clustering method creates a more reliable method for follow-up studies of brain functional connectivity.

Multivariate generalized multifactor dimensionality reduction to detect gene-gene interactions

PubMed Central

2013-01-01

Background Recently, one of the greatest challenges in genome-wide association studies is to detect gene-gene and/or gene-environment interactions for common complex human diseases. Ritchie et al. (2001) proposed multifactor dimensionality reduction (MDR) method for interaction analysis. MDR is a combinatorial approach to reduce multi-locus genotypes into high-risk and low-risk groups. Although MDR has been widely used for case-control studies with binary phenotypes, several extensions have been proposed. One of these methods, a generalized MDR (GMDR) proposed by Lou et al. (2007), allows adjusting for covariates and applying to both dichotomous and continuous phenotypes. GMDR uses the residual score of a generalized linear model of phenotypes to assign either high-risk or low-risk group, while MDR uses the ratio of cases to controls. Methods In this study, we propose multivariate GMDR, an extension of GMDR for multivariate phenotypes. Jointly analysing correlated multivariate phenotypes may have more power to detect susceptible genes and gene-gene interactions. We construct generalized estimating equations (GEE) with multivariate phenotypes to extend generalized linear models. Using the score vectors from GEE we discriminate high-risk from low-risk groups. We applied the multivariate GMDR method to the blood pressure data of the 7,546 subjects from the Korean Association Resource study: systolic blood pressure (SBP) and diastolic blood pressure (DBP). We compare the results of multivariate GMDR for SBP and DBP to the results from separate univariate GMDR for SBP and DBP, respectively. We also applied the multivariate GMDR method to the repeatedly measured hypertension status from 5,466 subjects and compared its result with those of univariate GMDR at each time point. Results Results from the univariate GMDR and multivariate GMDR in two-locus model with both blood pressures and hypertension phenotypes indicate best combinations of SNPs whose interaction has significant association with risk for high blood pressures or hypertension. Although the test balanced accuracy (BA) of multivariate analysis was not always greater than that of univariate analysis, the multivariate BAs were more stable with smaller standard deviations. Conclusions In this study, we have developed multivariate GMDR method using GEE approach. It is useful to use multivariate GMDR with correlated multiple phenotypes of interests. PMID:24565370

Maternal Interactions with a Hearing and Hearing-Impaired Twin: Similarities and Differences in Speech Input, Interaction Quality, and Word Production

ERIC Educational Resources Information Center

Lam, Christa; Kitamura, Christine

2010-01-01

Purpose: This study examined a mother's speech style and interactive behaviors with her twin sons: 1 with bilateral hearing impairment (HI) and the other with normal hearing (NH). Method: The mother was video-recorded interacting with her twin sons when the boys were 12.5 and 22 months of age. Mean F0, F0 range, duration, and F1/F2 vowel space of…

Self-Regulated Learning in Virtual Communities

ERIC Educational Resources Information Center

Delfino, Manuela; Dettori, Giuliana; Persico, Donatella

2008-01-01

This paper investigates self-regulated learning (SRL) in a virtual learning community of adults interacting through asynchronous textual communication. The investigation method chosen is interaction analysis, a qualitative/quantitative approach allowing a systematic study of the contents of the messages exchanged within online communities. The…

Statistical methods for analysing responses of wildlife to human disturbance.

Treesearch

Haiganoush K. Preisler; Alan A. Ager; Michael J. Wisdom

2006-01-01

1. Off-road recreation is increasing rapidly in many areas of the world, and effects on wildlife can be highly detrimental. Consequently, we have developed methods for studying wildlife responses to off-road recreation with the use of new technologies that allow frequent and accurate monitoring of human-wildlife interactions. To illustrate these methods, we studied the...

Creative Interactive Teaching: Case Method & Other Techniques. Selected Papers of the International Conference on Case Methods Research & Application (16th, Caceres, Spain, 1999).

ERIC Educational Resources Information Center

Klein, Hans E., Ed.

This book presents a selection of papers from the international, interdisciplinary conference of the World Association for Case Method Research & Application. Papers are categorized into seven areas: (1) "International Case Studies" (e.g., event-based entrepreneurship, case studies on consumer complaints, and strategic quality…

A Molecular Dynamic Modeling of Hemoglobin-Hemoglobin Interactions

NASA Astrophysics Data System (ADS)

Wu, Tao; Yang, Ye; Sheldon Wang, X.; Cohen, Barry; Ge, Hongya

2010-05-01

In this paper, we present a study of hemoglobin-hemoglobin interaction with model reduction methods. We begin with a simple spring-mass system with given parameters (mass and stiffness). With this known system, we compare the mode superposition method with Singular Value Decomposition (SVD) based Principal Component Analysis (PCA). Through PCA we are able to recover the principal direction of this system, namely the model direction. This model direction will be matched with the eigenvector derived from mode superposition analysis. The same technique will be implemented in a much more complicated hemoglobin-hemoglobin molecule interaction model, in which thousands of atoms in hemoglobin molecules are coupled with tens of thousands of T3 water molecule models. In this model, complex inter-atomic and inter-molecular potentials are replaced by nonlinear springs. We employ the same method to get the most significant modes and their frequencies of this complex dynamical system. More complex physical phenomena can then be further studied by these coarse grained models.

Gauge invariance of excitonic linear and nonlinear optical response

NASA Astrophysics Data System (ADS)

Taghizadeh, Alireza; Pedersen, T. G.

2018-05-01

We study the equivalence of four different approaches to calculate the excitonic linear and nonlinear optical response of multiband semiconductors. These four methods derive from two choices of gauge, i.e., length and velocity gauges, and two ways of computing the current density, i.e., direct evaluation and evaluation via the time-derivative of the polarization density. The linear and quadratic response functions are obtained for all methods by employing a perturbative density-matrix approach within the mean-field approximation. The equivalence of all four methods is shown rigorously, when a correct interaction Hamiltonian is employed for the velocity gauge approaches. The correct interaction is written as a series of commutators containing the unperturbed Hamiltonian and position operators, which becomes equivalent to the conventional velocity gauge interaction in the limit of infinite Coulomb screening and infinitely many bands. As a case study, the theory is applied to hexagonal boron nitride monolayers, and the linear and nonlinear optical response found in different approaches are compared.

Reverse engineering of gene regulatory networks.

PubMed

Cho, K H; Choo, S M; Jung, S H; Kim, J R; Choi, H S; Kim, J

2007-05-01

Systems biology is a multi-disciplinary approach to the study of the interactions of various cellular mechanisms and cellular components. Owing to the development of new technologies that simultaneously measure the expression of genetic information, systems biological studies involving gene interactions are increasingly prominent. In this regard, reconstructing gene regulatory networks (GRNs) forms the basis for the dynamical analysis of gene interactions and related effects on cellular control pathways. Various approaches of inferring GRNs from gene expression profiles and biological information, including machine learning approaches, have been reviewed, with a brief introduction of DNA microarray experiments as typical tools for measuring levels of messenger ribonucleic acid (mRNA) expression. In particular, the inference methods are classified according to the required input information, and the main idea of each method is elucidated by comparing its advantages and disadvantages with respect to the other methods. In addition, recent developments in this field are introduced and discussions on the challenges and opportunities for future research are provided.

Interactive lung segmentation in abnormal human and animal chest CT scans

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

Kockelkorn, Thessa T. J. P., E-mail: thessa@isi.uu.nl; Viergever, Max A.; Schaefer-Prokop, Cornelia M.

2014-08-15

Purpose: Many medical image analysis systems require segmentation of the structures of interest as a first step. For scans with gross pathology, automatic segmentation methods may fail. The authors’ aim is to develop a versatile, fast, and reliable interactive system to segment anatomical structures. In this study, this system was used for segmenting lungs in challenging thoracic computed tomography (CT) scans. Methods: In volumetric thoracic CT scans, the chest is segmented and divided into 3D volumes of interest (VOIs), containing voxels with similar densities. These VOIs are automatically labeled as either lung tissue or nonlung tissue. The automatic labeling resultsmore » can be corrected using an interactive or a supervised interactive approach. When using the supervised interactive system, the user is shown the classification results per slice, whereupon he/she can adjust incorrect labels. The system is retrained continuously, taking the corrections and approvals of the user into account. In this way, the system learns to make a better distinction between lung tissue and nonlung tissue. When using the interactive framework without supervised learning, the user corrects all incorrectly labeled VOIs manually. Both interactive segmentation tools were tested on 32 volumetric CT scans of pigs, mice and humans, containing pulmonary abnormalities. Results: On average, supervised interactive lung segmentation took under 9 min of user interaction. Algorithm computing time was 2 min on average, but can easily be reduced. On average, 2.0% of all VOIs in a scan had to be relabeled. Lung segmentation using the interactive segmentation method took on average 13 min and involved relabeling 3.0% of all VOIs on average. The resulting segmentations correspond well to manual delineations of eight axial slices per scan, with an average Dice similarity coefficient of 0.933. Conclusions: The authors have developed two fast and reliable methods for interactive lung segmentation in challenging chest CT images. Both systems do not require prior knowledge of the scans under consideration and work on a variety of scans.« less

Evaluation of pedestrian safety at intersections: A theoretical framework based on pedestrian-vehicle interaction patterns.

PubMed

Ni, Ying; Wang, Menglong; Sun, Jian; Li, Keping

2016-11-01

Pedestrians are the most vulnerable road users, and pedestrian safety has become a major research focus in recent years. Regarding the quality and quantity issues with collision data, conflict analysis using surrogate safety measures has become a useful method to study pedestrian safety. However, given the inequality between pedestrians and vehicles in encounters and the multiple interactions between pedestrians and vehicles, it is insufficient to simply use the same indicator(s) or the same way to aggregate indicators for all conditions. In addition, behavioral factors cannot be neglected. To better use information extracted from trajectories for safety evaluation and pay more attention on effects of behavioral factors, this paper develops a more sophisticated framework for pedestrian conflict analysis that takes pedestrian-vehicle interactions into consideration. A concept of three interaction patterns has been proposed for the first time, namely "hard interaction," "no interaction," and "soft-interaction." Interactions have been categorized under one of these patterns by analyzing profiles of speed and conflict indicators during the whole interactive processes. In this paper, a support vector machine (SVM) approach has been adopted to classify severity levels for a dataset including 1144 events extracted from three intersections in Shanghai, China, followed by an analysis of variable importance. The results revealed that different conflict indicators have different contributions to indicating the severity level under various interaction patterns. Therefore, it is recommended either to use specific conflict indicators or to use weighted indicator aggregation for each interaction pattern when evaluating pedestrian safety. The implementation has been carried out at the fourth crosswalk, and the results indicate that the proposed method can achieve a higher accuracy and better robustness than conventional methods. Furthermore, the method is helpful for better understanding underlying levels of safety from the behavioral perspective, which can also provide evidence for targeted traffic education on proper behaviors. Copyright © 2016 Elsevier Ltd. All rights reserved.

On the tidal interaction between protoplanets and the primordial solar nebula. II - Self-consistent nonlinear interaction

NASA Technical Reports Server (NTRS)

Lin, D. N. C.; Papaloizou, J.

1986-01-01

A method to analyze the full nonlinear response and physical processes associated with the tidal interaction between a binary system and a thin disk in the steady state is presented. Using this approach, density wave propagation, induced by tidal interaction, may be studied for a wide range of sound speeds and viscosities. The effect of self-gravity may also be incorporated. The results of several calculations relevant to the tidal interaction between a protoplanet and the primordial solar nebula are also presented.

Detecting Coevolution in Mammalian Sperm–Egg Fusion Proteins

PubMed Central

CLAW, KATRINA G.; GEORGE, RENEE D.; SWANSON, WILLIE J.

2018-01-01

SUMMARY Interactions between sperm and egg proteins can occur physically between gamete surface-binding proteins, and genetically between gamete proteins that work in complementary pathways in which they may not physically interact. Physically interacting sperm–egg proteins have been functionally identified in only a few species, and none have been verified within mammals. Candidate genes on both the sperm and egg surfaces exist, but gene deletion studies do not support functional interactions between these sperm–egg proteins; interacting sperm–egg proteins thus remain elusive. Cooperative gamete proteins undergo rapid evolution, and it is predicted that these sperm–egg proteins will also have correlated evolutionary rates due to compensatory changes on both the sperm and egg. To explore potential physical and genetic interactions in sperm–egg proteins, we sequenced four candidate genes from diverse primate species, and used regression and likelihood methods to test for signatures of coevolution between sperm–egg gene pairs. With both methods, we found that the egg protein CD9 coevolves with the sperm protein IZUMO1, suggesting a physical or genetic interaction occurs between them. With regression analysis, we found that CD9 and CRISP2 have correlated rates of evolution, and with likelihood analysis, that CD9 and CRISP1 have correlated rates. This suggests that the different tests may reflect different levels of interaction, be it physical or genetic. Coevolution tests thus provide an exploratory method for detecting potentially interacting sperm–egg protein pairs. PMID:24644026

Detecting coevolution in mammalian sperm-egg fusion proteins.

PubMed

Claw, Katrina G; George, Renee D; Swanson, Willie J

2014-06-01

Interactions between sperm and egg proteins can occur physically between gamete surface-binding proteins, and genetically between gamete proteins that work in complementary pathways in which they may not physically interact. Physically interacting sperm-egg proteins have been functionally identified in only a few species, and none have been verified within mammals. Candidate genes on both the sperm and egg surfaces exist, but gene deletion studies do not support functional interactions between these sperm-egg proteins; interacting sperm-egg proteins thus remain elusive. Cooperative gamete proteins undergo rapid evolution, and it is predicted that these sperm-egg proteins will also have correlated evolutionary rates due to compensatory changes on both the sperm and egg. To explore potential physical and genetic interactions in sperm-egg proteins, we sequenced four candidate genes from diverse primate species, and used regression and likelihood methods to test for signatures of coevolution between sperm-egg gene pairs. With both methods, we found that the egg protein CD9 coevolves with the sperm protein IZUMO1, suggesting a physical or genetic interaction occurs between them. With regression analysis, we found that CD9 and CRISP2 have correlated rates of evolution, and with likelihood analysis, that CD9 and CRISP1 have correlated rates. This suggests that the different tests may reflect different levels of interaction, be it physical or genetic. Coevolution tests thus provide an exploratory method for detecting potentially interacting sperm-egg protein pairs. © 2014 Wiley Periodicals, Inc.

A method to quantify FRET stoichiometry with phasor plot analysis and acceptor lifetime ingrowth.

PubMed

Chen, WeiYue; Avezov, Edward; Schlachter, Simon C; Gielen, Fabrice; Laine, Romain F; Harding, Heather P; Hollfelder, Florian; Ron, David; Kaminski, Clemens F

2015-03-10

FRET is widely used for the study of protein-protein interactions in biological samples. However, it is difficult to quantify both the FRET efficiency (E) and the affinity (Kd) of the molecular interaction from intermolecular FRET signals in samples of unknown stoichiometry. Here, we present a method for the simultaneous quantification of the complete set of interaction parameters, including fractions of bound donors and acceptors, local protein concentrations, and dissociation constants, in each image pixel. The method makes use of fluorescence lifetime information from both donor and acceptor molecules and takes advantage of the linear properties of the phasor plot approach. We demonstrate the capability of our method in vitro in a microfluidic device and also in cells, via the determination of the binding affinity between tagged versions of glutathione and glutathione S-transferase, and via the determination of competitor concentration. The potential of the method is explored with simulations. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

rpiCOOL: A tool for In Silico RNA-protein interaction detection using random forest.

PubMed

Akbaripour-Elahabad, Mohammad; Zahiri, Javad; Rafeh, Reza; Eslami, Morteza; Azari, Mahboobeh

2016-08-07

Understanding the principle of RNA-protein interactions (RPIs) is of critical importance to provide insights into post-transcriptional gene regulation and is useful to guide studies about many complex diseases. The limitations and difficulties associated with experimental determination of RPIs, call an urgent need to computational methods for RPI prediction. In this paper, we proposed a machine learning method to detect RNA-protein interactions based on sequence information. We used motif information and repetitive patterns, which have been extracted from experimentally validated RNA-protein interactions, in combination with sequence composition as descriptors to build a model to RPI prediction via a random forest classifier. About 20% of the "sequence motifs" and "nucleotide composition" features have been selected as the informative features with the feature selection methods. These results suggest that these two feature types contribute effectively in RPI detection. Results of 10-fold cross-validation experiments on three non-redundant benchmark datasets show a better performance of the proposed method in comparison with the current state-of-the-art methods in terms of various performance measures. In addition, the results revealed that the accuracy of the RPI prediction methods could vary considerably across different organisms. We have implemented the proposed method, namely rpiCOOL, as a stand-alone tool with a user friendly graphical user interface (GUI) that enables the researchers to predict RNA-protein interaction. The rpiCOOL is freely available at http://biocool.ir/rpicool.html for non-commercial uses. Copyright © 2016 Elsevier Ltd. All rights reserved.

The interaction between cations and anionic groups inducing SHG enhancement in a series of apatite-like crystals: A first-principles study

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

Jing, Qun; University of Chinese Academy of Sciences, Beijing 100049; Department of Physics, School of Science, Shihezi University, Shihezi 832000

2014-11-15

It is an interesting topic to reveal the origin of the SHG intensity enhancement after substitution from alkali and alkali-earth metal atoms to cadmium in a series of apatite-like borates KSr{sub 4}(BO{sub 3}){sub 3}, Ca{sub 5}(BO{sub 3}){sub 3}F, Cd{sub 5}(BO{sub 3}){sub 3}F. Combined with the first-principles method, SHG-density method and real-space atom-cutting method, the electronic structure, the optical properties and the contribution of respective ion and ion groups have been investigated. Second harmonic generation (SHG) responses are mainly attributed to BO{sub 3} groups with π conjugated configuration and their alignment framework. The contributions of A site are more important inmore » CaBOF and CdBOF compounds than in KSrBO. It is also demonstrated that the strong covalent interactions between the boron–oxygen groups and the cadmium atoms contribute the enhancement of SHG responses after substitution from alkali and alkali-earth metal atoms. - graphical abstract: Combined with the first-principles method, SHG-density method and real-space atom-cutting method, the enhancement of SHG response are attributed to the interaction between cadmium and BO{sub 3} groups. - Highlights: • SHG response on a series of apatite-like borates was studied by a SHG-density method. • SHG responses are mainly attributed to BO{sub 3} groups and their alignment framework. • The contributions of A site are more important in CaBOF and CdBOF than in KSrBO. • Covalent interaction between BO and Cd is responsible for SHG of CdBOF.« less

“We Do Science Here”: Underrepresented Students’ Interactions with Faculty in Different College Contexts

PubMed Central

Hurtado, Sylvia; Eagan, M. Kevin; Tran, Minh C.; Newman, Christopher B.; Chang, Mitchell J.; Velasco, Paolo

2011-01-01

Faculty members play a key role in the identification and training of the next generation of scientific talent. In the face of the need to advance and diversify the scientific workforce, we examine whether and how specific institutional contexts shape student interactions with faculty. We conducted a mixed methods study to understand institutional contextual differences in the experiences of aspiring scientists. Data from a qualitative five-campus case study and a quantitative longitudinal study of students from over 117 higher education institutions were analyzed to determine how aspiring scientists interact with faculty and gain access to resources that will help them achieve their educational goals. Findings indicate that important structural differences exist between institutions in shaping students’ interactions with faculty. For example, students at more selective institutions typically have less frequent, less personal interactions with faculty whereas Black students at HBCUs report having more support and frequent interactions with faculty. PMID:23503924

Study of ultrasonic attenuation in f-electron systems in the paramagnetic limit of Coulomb interaction

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

Shadangi, Asit Ku., E-mail: asitshad@iopb.res.in; Rout, G. C., E-mail: gcr@iopb.res.in

2015-05-15

We report here a microscopic model study of ultrasonic attenuation in f-electron systems based on Periodic Anderson Model in which Coulomb interaction is considered within a mean-field approximation for a weak interaction. The Phonon is coupled to the conduction band and f-electrons. The phonon Green's function is calculated by Zubarev's technique of the Green's function method. The temperature dependent ultrasonic attenuation co-efficient is calculated from the imaginary part of the phonon self-energy in the dynamic and long wave length limit. The f-electron occupation number is calculated self-consistently in paramagnetic limit of Coulomb interaction. The effect of the Coulomb interaction onmore » ultrasonic attenuation is studied by varying the phonon coupling parameters to the conduction and f-electrons, hybridization strength, the position of f-level and the Coulomb interaction Strength. Results are discussed on the basis of experimental results.« less

Evolutionary dynamics of group interactions on structured populations: a review

PubMed Central

Perc, Matjaž; Gómez-Gardeñes, Jesús; Szolnoki, Attila; Floría, Luis M.; Moreno, Yamir

2013-01-01

Interactions among living organisms, from bacteria colonies to human societies, are inherently more complex than interactions among particles and non-living matter. Group interactions are a particularly important and widespread class, representative of which is the public goods game. In addition, methods of statistical physics have proved valuable for studying pattern formation, equilibrium selection and self-organization in evolutionary games. Here, we review recent advances in the study of evolutionary dynamics of group interactions on top of structured populations, including lattices, complex networks and coevolutionary models. We also compare these results with those obtained on well-mixed populations. The review particularly highlights that the study of the dynamics of group interactions, like several other important equilibrium and non-equilibrium dynamical processes in biological, economical and social sciences, benefits from the synergy between statistical physics, network science and evolutionary game theory. PMID:23303223

[Brownian dynamics simulations of protein-protein interactions in photosynthetic electron transport chain].

PubMed

Khruschev, S S; Abaturova, A M; Diakonova, A N; Fedorov, V A; Ustinin, D M; Kovalenko, I B; Riznichenko, G Yu; Rubin, A B

2015-01-01

The application of Brownian dynamics for simulation of transient protein-protein interactions is reviewed. The review focuses on theoretical basics of Brownian dynamics method, its particular implementations, advantages and drawbacks of the method. The outlook for future development of Brownian dynamics-based simulation techniques is discussed. Special attention is given to analysis of Brownian dynamics trajectories. The second part of the review is dedicated to the role of Brownian dynamics simulations in studying photosynthetic electron transport. Interactions of mobile electron carriers (plastocyanin, cytochrome c6, and ferredoxin) with their reaction partners (cytochrome b6f complex, photosystem I, ferredoxin:NADP-reductase, and hydrogenase) are considered.

Comparing High Definition Live Interactive and Store-and-Forward Consultations to In-Person Examinations.

PubMed

Marchell, Richard; Locatis, Craig; Burges, Gene; Maisiak, Richard; Liu, Wei-Li; Ackerman, Michael

2017-03-01

There is little teledermatology research directly comparing remote methods, even less research with two in-person dermatologist agreement providing a baseline for comparing remote methods, and no research using high definition video as a live interactive method. To compare in-person consultations with store-and-forward and live interactive methods, the latter having two levels of image quality. A controlled study was conducted where patients were examined in-person, by high definition video, and by store-and-forward methods. The order patients experienced methods and residents assigned methods rotated, although an attending always saw patients in-person. The type of high definition video employed, lower resolution compressed or higher resolution uncompressed, was alternated between clinics. Primary and differential diagnoses, biopsy recommendations, and diagnostic and biopsy confidence ratings were recorded. Concordance and confidence were significantly better for in-person versus remote methods and biopsy recommendations were lower. Store-and-forward and higher resolution uncompressed video results were similar and better than those for lower resolution compressed video. Dermatology residents took store-and-forward photos and their quality was likely superior to those normally taken in practice. There were variations in expertise between the attending and second and third year residents. The superiority of in-person consultations suggests the tendencies to order more biopsies or still see patients in-person are often justified in teledermatology and that high resolution uncompressed video can close the resolution gap between store-and-forward and live interactive methods.

The Socialization of Virtual Teams: Implications for ISD

NASA Astrophysics Data System (ADS)

Mullally, Brenda; Stapleton, Larry

Studies show that Information Systems Development (ISD) projects do not fulfil stakeholder expectations of completion time, quality and budget. (2005) study shows that development is more about social interaction and mutual understanding than following a prescribed method. Systems development is a social process where interactions help to make sense of the reality within which the system is developed (Hirschheirn et al., 1991). Research concentrates on methodology when in fact method may not be the primary problem. Authors have called for further research to investigate the true nature of the current systems development environment in real organisational situations (Fitzgerald, 2000).

Path-integral Monte Carlo method for Rényi entanglement entropies.

PubMed

Herdman, C M; Inglis, Stephen; Roy, P-N; Melko, R G; Del Maestro, A

2014-07-01

We introduce a quantum Monte Carlo algorithm to measure the Rényi entanglement entropies in systems of interacting bosons in the continuum. This approach is based on a path-integral ground state method that can be applied to interacting itinerant bosons in any spatial dimension with direct relevance to experimental systems of quantum fluids. We demonstrate how it may be used to compute spatial mode entanglement, particle partitioned entanglement, and the entanglement of particles, providing insights into quantum correlations generated by fluctuations, indistinguishability, and interactions. We present proof-of-principle calculations and benchmark against an exactly soluble model of interacting bosons in one spatial dimension. As this algorithm retains the fundamental polynomial scaling of quantum Monte Carlo when applied to sign-problem-free models, future applications should allow for the study of entanglement entropy in large-scale many-body systems of interacting bosons.

Van der Waals Interactions of Organic Molecules on Semiconductor and Metal Surfaces: a Comparative Study

NASA Astrophysics Data System (ADS)

Li, Guo; Cooper, Valentino; Cho, Jun-Hyung; Tamblyn, Isaac; Du, Shixuan; Neaton, Jeffrey; Gao, Hong-Jun; Zhang, Zhenyu

2012-02-01

We present a comparative investigation of vdW interactions of the organic molecules on semiconductor and metal surfaces using the DFT method implemented with vdW-DF. For styrene/H-Si(100), the vdW interactions reverse the effective intermolecular interaction from repulsive to attractive, ensuring preferred growth of long wires as observed experimentally. We further propose that an external E field and the selective creation of Si dangling bonds can drastically improve the ordered arrangement of the molecular nanowires [1]. For BDA/Au(111), the vdW interactions not only dramatically enhances the adsorption energies, but also significantly changes the molecular configurations. In the azobenzene/Ag(111) system, vdW-DF produces superior predictions for the adsorption energy than those obtained with other vdW corrected DFT approaches, providing evidence for the applicability of the vdW-DF method [2].

Final state interactions and the transverse structure of the pion using non-perturbative eikonal methods

DOE PAGES

Gamberg, Leonard; Schlegel, Marc

2010-01-18

In the factorized picture of semi-inclusive hadronic processes the naive time reversal-odd parton distributions exist by virtue of the gauge link which renders it color gauge invariant. The link characterizes the dynamical effect of initial/final-state interactions of the active parton due soft gluon exchanges with the target remnant. Though these interactions are non-perturbative, studies of final-state interaction have been approximated by perturbative one-gluon approximation in Abelian models. We include higher-order contributions by applying non-perturbative eikonal methods incorporating color degrees of freedom in a calculation of the Boer-Mulders function of the pion. Lastly, using this framework we explore under what conditionsmore » the Boer Mulders function can be described in terms of factorization of final state interactions and a spatial distribution in impact parameter space.« less

Drug-nutrient interactions in the intensive care unit: literature review and current recommendations

PubMed Central

Heldt, Tatiane; Loss, Sergio Henrique

2013-01-01

Objective To describe the interactions between drugs and nutrients and their frequency in the intensive care unit and to assess the professional team's awareness regarding this subject. Methods The keywords "drug interactions" and "nutrition therapy" were searched in the PubMed (specifically MeSH) electronic database. The studies were systematically reviewed for descriptions of the types of interactions between drugs and nutrients, including their frequency and consequences. Results Sixty-seven articles were found. Among these, 20 articles were appropriate for the methodology adopted and accomplished the objectives of the study. Of these 20 articles, 14 articles described interactions between drugs and enteral nutrition, three described interactions between drugs and parenteral nutrition, and three described the importance and care required to avoid such interactions. Conclusions The literature about drug and nutrient interactions is limited and suggests the inability of health care teams to recognize the potential for these interactions. Possibly, the elaboration of a protocol to evaluate drug-nutrient interactions will increase the safety and efficacy of therapeutics. PMID:23917982

In Vitro Interactions between Tacrolimus and Azoles against Candida albicans Determined by Different Methods▿

PubMed Central

Sun, Shujuan; Li, Yan; Guo, Qiongjie; Shi, Changwen; Yu, Jinlong; Ma, Lin

2008-01-01

Combination therapy could be of use for the treatment of fungal infections, especially those caused by drug-resistant fungi. However, the methods and approaches used for data generation and result interpretation need further optimizing. The fractional inhibitory concentration index (FICI) is the most commonly used method, but it has several drawbacks in characterizing antifungal drug interaction. Alternatively, some new methods can be used such as the ΔE model (difference between the predicted and measured fungal growth percentages) and the response surface approach, which uses the concentration-effect relationship over the whole concentration range instead of just the MIC. In the present study, in vitro interactions between tacrolimus (FK506) and three azoles—fluconazole (FLC), itraconazole (ITR), and voriconazole (VRC)-against Candida albicans were evaluated by the checkerboard microdilution method and time-killing test. The intensity of the interactions was determined by visual reading and the spectrophotometric method in a checkerboard assay, and the nature of the interactions was assessed by nonparametric models of FICI and ΔE. Colony counting and colorimetric viable detection methods (2,3-bis {2-methoxy-4-nitro-5-[(sulfenylamino) carbonyl]-2H-tetrazolium hydroxide} [XTT] reduction test) were used for evaluating the combination antifungal effects over time. Synergistic and indifferent effects were found for the combination of FK506 and azoles against azole-sensitive strains, while strong synergy was found against azole-resistant strains analyzed by FICI. The ΔE model gave more consistent results with FICI. The positive interactions were also confirmed by the time-killing test. Our findings suggest a potential role for combination therapy with calcineurin pathway inhibitors and azoles to augment activity against resistant C. albicans. PMID:18056277

A Framework for Spatial Interaction Analysis Based on Large-Scale Mobile Phone Data

PubMed Central

Li, Weifeng; Cheng, Xiaoyun; Guo, Gaohua

2014-01-01

The overall understanding of spatial interaction and the exact knowledge of its dynamic evolution are required in the urban planning and transportation planning. This study aimed to analyze the spatial interaction based on the large-scale mobile phone data. The newly arisen mass dataset required a new methodology which was compatible with its peculiar characteristics. A three-stage framework was proposed in this paper, including data preprocessing, critical activity identification, and spatial interaction measurement. The proposed framework introduced the frequent pattern mining and measured the spatial interaction by the obtained association. A case study of three communities in Shanghai was carried out as verification of proposed method and demonstration of its practical application. The spatial interaction patterns and the representative features proved the rationality of the proposed framework. PMID:25435865

Factors affecting quality of social interaction park in Jakarta

NASA Astrophysics Data System (ADS)

Mangunsong, N. I.

2018-01-01

The existence of social interactions park in Jakarta is an oasis in the middle of a concrete jungle. Parks is a response to the need for open space as a place of recreation and community interaction. Often the social interaction parks built by the government does not function as expected, but other functions such as a place to sell, trash, unsafe so be rarely visited by visitors. The purpose of this study was to analyze the factors that affect the quality of social interaction parks in Jakarta by conducting descriptive analysis and correlation analysis of the variables assessment. The results of the analysis can give an idea of social interactions park based on community needs and propose the development of social interactioncity park. The object of study are 25 social interaction parks in 5 municipalities of Jakarta. The method used is descriptive analysis method, correlation analysis using SPSS 19 and using crosstab, chi-square tests. The variables are 5 aspects of Design, Plants composition: Selection type of plant (D); the beauty and harmony (Ind); Maintenance and fertility (P); Cleanliness and Environmental Health (BS); Specificity (Drainage, Multi Function garden, Means, Concern/Mutual cooperation, in dense settlements) (K). The results of analysis show that beauty is the most significant correlation with the value of the park followed by specificity, cleanliness and maintenance. Design was not the most significant variable affecting the quality of the park. The results of this study can be used by the Department of Parks and Cemeteries as input in managing park existing or to be developed and to improve the quality of social interaction park in Jakarta.

Visualizing Active Enzyme Complexes Using a Photoreactive Inhibitor for Proximity Ligation – Application on γ-Secretase

PubMed Central

Schedin-Weiss, Sophia; Inoue, Mitsuhiro; Teranishi, Yasuhiro; Yamamoto, Natsuko Goto; Karlström, Helena; Winblad, Bengt; Tjernberg, Lars O.

2013-01-01

Here, we present a highly sensitive method to study protein-protein interactions and subcellular location selectively for active multicomponent enzymes. We apply the method on γ-secretase, the enzyme complex that catalyzes the cleavage of the amyloid precursor protein (APP) to generate amyloid β-peptide (Aβ), the major causative agent in Alzheimer disease (AD). The novel assay is based on proximity ligation, which can be used to study protein interactions in situ with very high sensitivity. In traditional proximity ligation assay (PLA), primary antibody recognition is typically accompanied by oligonucleotide-conjugated secondary antibodies as detection probes. Here, we first performed PLA experiments using antibodies against the γ-secretase components presenilin 1 (PS1), containing the catalytic site residues, and nicastrin, suggested to be involved in substrate recognition. To selectively study the interactions of active γ-secretase, we replaced one of the primary antibodies with a photoreactive γ-secretase inhibitor containing a PEG linker and a biotin group (GTB), and used oligonucleotide-conjugated streptavidin as a probe. Interestingly, significantly fewer interactions were detected with the latter, novel, assay, which is a reasonable finding considering that a substantial portion of PS1 is inactive. In addition, the PLA signals were located more peripherally when GTB was used instead of a PS1 antibody, suggesting that γ-secretase matures distal from the perinuclear ER region. This novel technique thus enables highly sensitive protein interaction studies, determines the subcellular location of the interactions, and differentiates between active and inactive γ-secretase in intact cells. We suggest that similar PLA assays using enzyme inhibitors could be useful also for other enzyme interaction studies. PMID:23717518

Exploring the roles of interaction and flow in explaining nurses' e-learning acceptance.

PubMed

Cheng, Yung-Ming

2013-01-01

To provide safe and competent patient care, it is very important that medical institutions should provide nurses with continuing education by using appropriate learning methods. As compared to traditional learning, electronic learning (e-learning) is a more flexible method for nurses' in-service learning. Hence, e-learning is expected to play a pivotal role in providing continuing education for nurses. This study's purpose was to explore the role and relevance of interaction factors, intrinsic motivator (i.e., flow), and extrinsic motivators (i.e., perceived usefulness (PU) and perceived ease of use (PEOU)) in explaining nurses' intention to use the e-learning system. Based on the technology acceptance model (TAM) with the flow theory, this study's research model presents three types of interaction factors, learner-system interaction, instructor-learner interaction, and learner-learner interaction to construct an extended TAM to explore nurses' intention to use the e-learning system. Sample data were gathered from nurses at two regional hospitals in Taiwan. A total of 320 questionnaires were distributed, 254 (79.375%) questionnaires were returned. Consequently, 218 usable questionnaires were analyzed in this study, with a usable response rate of 68.125%. First, confirmatory factor analysis was used to develop the measurement model. Second, to explore the causal relationships among all constructs, the structural model for the research model was tested by using structural equation modeling. First, learner-system interaction, instructor-learner interaction, and learner-learner interaction respectively had significant effects on PU, PEOU, and flow. Next, flow had significant effects on PU and PEOU, and PEOU had a significant effect on PU. Finally, the effects of flow, PU, and PEOU on intention to use were significant. Synthetically speaking, learner-system interaction, instructor-learner interaction, and learner-learner interaction can indirectly make significant impacts on nurses' usage intention of the e-learning system via their extrinsic motivators (i.e., PU and PEOU) and intrinsic motivator (i.e., flow). Copyright © 2012 Elsevier Ltd. All rights reserved.

Comparison of gesture and conventional interaction techniques for interventional neuroradiology.

PubMed

Hettig, Julian; Saalfeld, Patrick; Luz, Maria; Becker, Mathias; Skalej, Martin; Hansen, Christian

2017-09-01

Interaction with radiological image data and volume renderings within a sterile environment is a challenging task. Clinically established methods such as joystick control and task delegation can be time-consuming and error-prone and interrupt the workflow. New touchless input modalities may have the potential to overcome these limitations, but their value compared to established methods is unclear. We present a comparative evaluation to analyze the value of two gesture input modalities (Myo Gesture Control Armband and Leap Motion Controller) versus two clinically established methods (task delegation and joystick control). A user study was conducted with ten experienced radiologists by simulating a diagnostic neuroradiological vascular treatment with two frequently used interaction tasks in an experimental operating room. The input modalities were assessed using task completion time, perceived task difficulty, and subjective workload. Overall, the clinically established method of task delegation performed best under the study conditions. In general, gesture control failed to exceed the clinical input approach. However, the Myo Gesture Control Armband showed a potential for simple image selection task. Novel input modalities have the potential to take over single tasks more efficiently than clinically established methods. The results of our user study show the relevance of task characteristics such as task complexity on performance with specific input modalities. Accordingly, future work should consider task characteristics to provide a useful gesture interface for a specific use case instead of an all-in-one solution.

Contribution to the Study of Nuclear Interactions at Several Tens of Bev by Means of Cosmic Radiations (thesis); CONTRIBUTION A L'ETUDE DES INTERACTIONS NUCLEAIRES DE PLUSIEURS DIZAINES DE Gev., AU MOYEN DES RAYONS COSMIQUES (THESES)

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

Pelletier, C.

1960-01-01

The secondaries produced by the interaction of highenergy cosmic radiation with aluminum were studied with Wilson chambers placed in a magnetic field. From 9600 photographs made, 117 interactions of charged particles with energy higher than 10 Bev in aluminum were selected. These photographs were obtained with the apparatus installed at the Observatory of the Pic du Midi de Bigorre. This apparatus is described. The quantities of motion and the emission direction of charged secondaries of each interaction were determined. The measurements and the methods of calculation are described. The results obtained on charged secondaries and unstable particles are reported. Themore » selection of the interactions which occurred with only one nucleon of the aluminum nucleus is discussed. These interactions were studied in the center-of-mass system of the interacting particles. The results obtained are compared with the predictions of the principal theoreticat models of nucleon-nucleon interactions. (trauth)« less

Monte Carlo studies on neutron interactions in radiobiological experiments

PubMed Central

Shahmohammadi Beni, Mehrdad; Hau, Tak Cheong; Krstic, D.; Nikezic, D.

2017-01-01

Monte Carlo method was used to study the characteristics of neutron interactions with cells underneath a water medium layer with varying thickness. The following results were obtained. (1) The fractions of neutron interaction with 1H, 12C, 14N and 16O nuclei in the cell layer were studied. The fraction with 1H increased with increasing medium thickness, while decreased for 12C, 14N and 16O nuclei. The bulges in the interaction fractions with 12C, 14N and 16O nuclei were explained by the resonance spikes in the interaction cross-section data. The interaction fraction decreased in the order: 1H > 16O > 12C > 14N. (2) In general, as the medium thickness increased, the number of “interacting neutrons” which exited the medium and then further interacted with the cell layer increased. (3) The area under the angular distributions for “interacting neutrons” decreased with increasing incident neutron energy. Such results would be useful for deciphering the reasons behind discrepancies among existing results in the literature. PMID:28704557

Interactive Story Development for the Unit of Turks on the Silk Road in Social Sciences Course

ERIC Educational Resources Information Center

Karamete, Aysen; Topraklioglu, Kivanç

2017-01-01

With this study, creating interactive story that includes interaction factors was purposed in order to support teaching of the unit of Turks on the Silk Road in Social Sciences course of 6th grades. The research method was defined as Design and Development Research and ADDIE pattern that is one of the teaching design pattern was based while…

Yakima River Species Interactions Studies, Annual Report 1993.

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

Pearsons, Todd N.

Species interactions research was initiated in 1989 to investigate ecological interactions among fish in response to proposed supplementation of salmon and steelhead in the upper Yakima River basin. Data have been collected prior to supplementation to characterize the rainbow trout population, predict the potential interactions that may occur as a result of supplementation, and develop methods to monitor interactions. Major topics of this report are associated with the life history of rainbow trout, interactions experimentation, and methods for sampling. This report is organized into nine chapters with a general introduction preceding the first chapter and a general discussion following themore » last chapter. This annual report summarizes data collected primarily by the Washington Department of Fish and Wildlife (WDFW) between January 1 and December 31, 1993 in the upper Yakima basin above Roza Dam, however these data were compared to data from previous years to identify preliminary trends and patterns. Major preliminary findings from each of the chapters included in this report are described.« less

Discovering mutated driver genes through a robust and sparse co-regularized matrix factorization framework with prior information from mRNA expression patterns and interaction network.

PubMed

Xi, Jianing; Wang, Minghui; Li, Ao

2018-06-05

Discovery of mutated driver genes is one of the primary objective for studying tumorigenesis. To discover some relatively low frequently mutated driver genes from somatic mutation data, many existing methods incorporate interaction network as prior information. However, the prior information of mRNA expression patterns are not exploited by these existing network-based methods, which is also proven to be highly informative of cancer progressions. To incorporate prior information from both interaction network and mRNA expressions, we propose a robust and sparse co-regularized nonnegative matrix factorization to discover driver genes from mutation data. Furthermore, our framework also conducts Frobenius norm regularization to overcome overfitting issue. Sparsity-inducing penalty is employed to obtain sparse scores in gene representations, of which the top scored genes are selected as driver candidates. Evaluation experiments by known benchmarking genes indicate that the performance of our method benefits from the two type of prior information. Our method also outperforms the existing network-based methods, and detect some driver genes that are not predicted by the competing methods. In summary, our proposed method can improve the performance of driver gene discovery by effectively incorporating prior information from interaction network and mRNA expression patterns into a robust and sparse co-regularized matrix factorization framework.

Interactive Reading on the Secondary Level.

ERIC Educational Resources Information Center

Gross, Patricia A.

A study of two teachers and four secondary level English classes examined how traditional methods of teaching literature were replaced by more interactive and integrated approaches to text, based primarily upon a whole language philosophy. Intervention aspects purposely remained open-ended to accommodate each teacher's understandings and…

Influence of Food on Paediatric Gastrointestinal Drug Absorption Following Oral Administration: A Review

PubMed Central

Batchelor, Hannah K.

2015-01-01

The objective of this paper was to review existing information regarding food effects on drug absorption within paediatric populations. Mechanisms that underpin food–drug interactions were examined to consider potential differences between adult and paediatric populations, to provide insights into how this may alter the pharmacokinetic profile in a child. Relevant literature was searched to retrieve information on food–drug interaction studies undertaken on: (i) paediatric oral drug formulations; and (ii) within paediatric populations. The applicability of existing methodology to predict food effects in adult populations was evaluated with respect to paediatric populations where clinical data was available. Several differences in physiology, anatomy and the composition of food consumed within a paediatric population are likely to lead to food–drug interactions that cannot be predicted based on adult studies. Existing methods to predict food effects cannot be directly extrapolated to allow predictions within paediatric populations. Development of systematic methods and guidelines is needed to address the general lack of information on examining food–drug interactions within paediatric populations. PMID:27417362

Dissecting gene-environment interactions: A penalized robust approach accounting for hierarchical structures.

PubMed

Wu, Cen; Jiang, Yu; Ren, Jie; Cui, Yuehua; Ma, Shuangge

2018-02-10

Identification of gene-environment (G × E) interactions associated with disease phenotypes has posed a great challenge in high-throughput cancer studies. The existing marginal identification methods have suffered from not being able to accommodate the joint effects of a large number of genetic variants, while some of the joint-effect methods have been limited by failing to respect the "main effects, interactions" hierarchy, by ignoring data contamination, and by using inefficient selection techniques under complex structural sparsity. In this article, we develop an effective penalization approach to identify important G × E interactions and main effects, which can account for the hierarchical structures of the 2 types of effects. Possible data contamination is accommodated by adopting the least absolute deviation loss function. The advantage of the proposed approach over the alternatives is convincingly demonstrated in both simulation and a case study on lung cancer prognosis with gene expression measurements and clinical covariates under the accelerated failure time model. Copyright © 2017 John Wiley & Sons, Ltd.

A novel ultrasonication method in the preparation of zirconium impregnated cellulose for effective fluoride adsorption.

PubMed

Barathi, M; Kumar, A Santhana Krishna; Rajesh, N

2014-05-01

In the present work, we propose for the first time a novel ultrasound assisted methodology involving the impregnation of zirconium in a cellulose matrix. Fluoride from aqueous solution interacts with the cellulose hydroxyl groups and the cationic zirconium hydroxide. Ultrasonication ensures a green and quick alternative to the conventional time intensive method of preparation. The effectiveness of this process was confirmed by comprehensive characterization of zirconium impregnated cellulose (ZrIC) adsorbent using Fourier transform infrared spectroscopy (FT-IR), energy dispersive X-ray spectrometry (EDX) and X-ray diffraction (XRD) studies. The study of various adsorption isotherm models, kinetics and thermodynamics of the interaction validated the method. Copyright © 2013 Elsevier B.V. All rights reserved.

Using video-based observation research methods in primary care health encounters to evaluate complex interactions

PubMed Central

Asan, Onur; Montague, Enid

2015-01-01

Objective The purpose of this paper is to describe the use of video-based observation research methods in primary care environment and highlight important methodological considerations and provide practical guidance for primary care and human factors researchers conducting video studies to understand patient-clinician interaction in primary care settings. Methods We reviewed studies in the literature which used video methods in health care research and, we also used our own experience based on the video studies we conducted in primary care settings. Results This paper highlighted the benefits of using video techniques such as multi-channel recording and video coding and compared “unmanned” video recording with the traditional observation method in primary care research. We proposed a list, which can be followed step by step to conduct an effective video study in a primary care setting for a given problem. This paper also described obstacles researchers should anticipate when using video recording methods in future studies. Conclusion With the new technological improvements, video-based observation research is becoming a promising method in primary care and HFE research. Video recording has been under-utilized as a data collection tool because of confidentiality and privacy issues. However, it has many benefits as opposed to traditional observations, and recent studies using video recording methods have introduced new research areas and approaches. PMID:25479346

A Multi-Method Approach for Proteomic Network Inference in 11 Human Cancers.

PubMed

Şenbabaoğlu, Yasin; Sümer, Selçuk Onur; Sánchez-Vega, Francisco; Bemis, Debra; Ciriello, Giovanni; Schultz, Nikolaus; Sander, Chris

2016-02-01

Protein expression and post-translational modification levels are tightly regulated in neoplastic cells to maintain cellular processes known as 'cancer hallmarks'. The first Pan-Cancer initiative of The Cancer Genome Atlas (TCGA) Research Network has aggregated protein expression profiles for 3,467 patient samples from 11 tumor types using the antibody based reverse phase protein array (RPPA) technology. The resultant proteomic data can be utilized to computationally infer protein-protein interaction (PPI) networks and to study the commonalities and differences across tumor types. In this study, we compare the performance of 13 established network inference methods in their capacity to retrieve the curated Pathway Commons interactions from RPPA data. We observe that no single method has the best performance in all tumor types, but a group of six methods, including diverse techniques such as correlation, mutual information, and regression, consistently rank highly among the tested methods. We utilize the high performing methods to obtain a consensus network; and identify four robust and densely connected modules that reveal biological processes as well as suggest antibody-related technical biases. Mapping the consensus network interactions to Reactome gene lists confirms the pan-cancer importance of signal transduction pathways, innate and adaptive immune signaling, cell cycle, metabolism, and DNA repair; and also suggests several biological processes that may be specific to a subset of tumor types. Our results illustrate the utility of the RPPA platform as a tool to study proteomic networks in cancer.

A fast and accurate method to predict 2D and 3D aerodynamic boundary layer flows

NASA Astrophysics Data System (ADS)

Bijleveld, H. A.; Veldman, A. E. P.

2014-12-01

A quasi-simultaneous interaction method is applied to predict 2D and 3D aerodynamic flows. This method is suitable for offshore wind turbine design software as it is a very accurate and computationally reasonably cheap method. This study shows the results for a NACA 0012 airfoil. The two applied solvers converge to the experimental values when the grid is refined. We also show that in separation the eigenvalues remain positive thus avoiding the Goldstein singularity at separation. In 3D we show a flow over a dent in which separation occurs. A rotating flat plat is used to show the applicability of the method for rotating flows. The shown capabilities of the method indicate that the quasi-simultaneous interaction method is suitable for design methods for offshore wind turbine blades.

A robust multifactor dimensionality reduction method for detecting gene-gene interactions with application to the genetic analysis of bladder cancer susceptibility

PubMed Central

Gui, Jiang; Andrew, Angeline S.; Andrews, Peter; Nelson, Heather M.; Kelsey, Karl T.; Karagas, Margaret R.; Moore, Jason H.

2010-01-01

A central goal of human genetics is to identify and characterize susceptibility genes for common complex human diseases. An important challenge in this endeavor is the modeling of gene-gene interaction or epistasis that can result in non-additivity of genetic effects. The multifactor dimensionality reduction (MDR) method was developed as machine learning alternative to parametric logistic regression for detecting interactions in absence of significant marginal effects. The goal of MDR is to reduce the dimensionality inherent in modeling combinations of polymorphisms using a computational approach called constructive induction. Here, we propose a Robust Multifactor Dimensionality Reduction (RMDR) method that performs constructive induction using a Fisher’s Exact Test rather than a predetermined threshold. The advantage of this approach is that only those genotype combinations that are determined to be statistically significant are considered in the MDR analysis. We use two simulation studies to demonstrate that this approach will increase the success rate of MDR when there are only a few genotype combinations that are significantly associated with case-control status. We show that there is no loss of success rate when this is not the case. We then apply the RMDR method to the detection of gene-gene interactions in genotype data from a population-based study of bladder cancer in New Hampshire. PMID:21091664

The Effect of Experiences with Animals on the Reading Comprehension Skills of Students in the Seventh Grade

ERIC Educational Resources Information Center

Petersen, Annie

2008-01-01

The Problem: The study examined the difference that animal interactions had on the reading comprehension growth skills of students in the seventh grade. Method: A quasiexperimental study was conducted with two seventh-grade classes at William Howard Taft Middle School. One class received daily 20-minute animal interaction experiences for 5 days.…

A Meta-Ethnography of Two Studies on Interactions in Schools: Reflections on the Process of Translation

ERIC Educational Resources Information Center

Kakos, Michalis; Fritzsche, Bettina

2017-01-01

This paper reflects upon our experience gained from engagement in a meta-ethnography of two studies on interactions between teachers and students in schools situated in England and Germany. Starting with a short overview of Noblit and Hare's (1988) conceptualisation of the method, the paper outlines the meta-ethnography we undertook especially…

Interaction Between Society and Education in Chicago. Final Report.

ERIC Educational Resources Information Center

Havighurst, Robert J.; And Others

This study of social systems in Chicago has three objectives: (1) To explore the interaction of the educational system with the social structure and social forces in a modern metropolitan area, (2) to make a historical study of the development of education in a city evolving during the 20th century, and (3) to develop a method for a…

The Effect of WhatsApp Chat Group in Enhancing EFL Learners' Verbal Interaction outside Classroom Contexts

ERIC Educational Resources Information Center

Minalla, Amir Abdalla

2018-01-01

This study was mainly conducted to examine the possibility of utilizing "WhatsApp Group" in enhancing EFL learners' verbal interaction. To do this experimental and descriptive methods were used to achieve the objective of this study. A questionnaire and pre- and post-test were adopted as tools for data collection. Samples of two groups…

"Don't Ruin My Pretend": Kids Sustaining Play Interactions in Out-of-School Settings

ERIC Educational Resources Information Center

Eyerman, Suzanne

2011-01-01

As much as play is researched and discussed by people interested in children and childhood, studies often fail to examine closely the ways that kids accomplish their play. This study sought to answer the question of how children sustain their play interactions. By making use of qualitative methods to collect and analyze data, the play of…

Web 2.0, Pedagogical Support for Reflexive and Emotional Social Interaction among Swedish Students

ERIC Educational Resources Information Center

Augustsson, Gunnar

2010-01-01

Collaborative social interaction when using Web 2.0 in terms of VoiceThread is investigated in a case study of a Swedish university course in social psychology. The case study method was chosen because of the desire not to manipulate the students' behaviour, and data was collected in parallel with course implementation. Two particular…

Multiple Linear Regression for Reconstruction of Gene Regulatory Networks in Solving Cascade Error Problems

PubMed Central

Zainudin, Suhaila; Arif, Shereena M.

2017-01-01

Gene regulatory network (GRN) reconstruction is the process of identifying regulatory gene interactions from experimental data through computational analysis. One of the main reasons for the reduced performance of previous GRN methods had been inaccurate prediction of cascade motifs. Cascade error is defined as the wrong prediction of cascade motifs, where an indirect interaction is misinterpreted as a direct interaction. Despite the active research on various GRN prediction methods, the discussion on specific methods to solve problems related to cascade errors is still lacking. In fact, the experiments conducted by the past studies were not specifically geared towards proving the ability of GRN prediction methods in avoiding the occurrences of cascade errors. Hence, this research aims to propose Multiple Linear Regression (MLR) to infer GRN from gene expression data and to avoid wrongly inferring of an indirect interaction (A → B → C) as a direct interaction (A → C). Since the number of observations of the real experiment datasets was far less than the number of predictors, some predictors were eliminated by extracting the random subnetworks from global interaction networks via an established extraction method. In addition, the experiment was extended to assess the effectiveness of MLR in dealing with cascade error by using a novel experimental procedure that had been proposed in this work. The experiment revealed that the number of cascade errors had been very minimal. Apart from that, the Belsley collinearity test proved that multicollinearity did affect the datasets used in this experiment greatly. All the tested subnetworks obtained satisfactory results, with AUROC values above 0.5. PMID:28250767

Interaction betwen Lead and Bone Protein to Affect Bone Calcium Level Using UV-Vis Spectroscopy

NASA Astrophysics Data System (ADS)

Noor, Z.; Azharuddin, A.; Aflanie, I.; Kania, N.; Suhartono, E.

2018-05-01

This present study aim to evaluate the interactions between lead (Pb) and with bone protein by UV-Vis approach. In addition, this prsent study also aim to investigate the effect of Pb on bone calcium (Ca) level. The present study was a true experimental study design to examine the impact of Pb exposure in bone of male rats (Rattus novergicus). The study involved 5 groups, P1 was the control group, while the other (P2-P5) were the case group with exposure of Pb in different concentration within 4 weeks. At the end of the exposure, the interaction between Pb and protein was determined using UV-Vis spectrophotometric method, and the Ca level was determined using permanganometric method. The results shows that that there is an interaction between Pb and bone protein. The result also shows that the value of the binding constant of Protein-Pb is 32.71. It means Pb have an high affinity to bind with bone protein, which promote a further reaction to induced the release of bone Ca from the bone protein. In conclusion, this present study found an obvious relationship between Pb and bone protein which promote a further reaction to increase the releasing of bone calcium.

Detecting Genetic Interactions for Quantitative Traits Using m-Spacing Entropy Measure

PubMed Central

Yee, Jaeyong; Kwon, Min-Seok; Park, Taesung; Park, Mira

2015-01-01

A number of statistical methods for detecting gene-gene interactions have been developed in genetic association studies with binary traits. However, many phenotype measures are intrinsically quantitative and categorizing continuous traits may not always be straightforward and meaningful. Association of gene-gene interactions with an observed distribution of such phenotypes needs to be investigated directly without categorization. Information gain based on entropy measure has previously been successful in identifying genetic associations with binary traits. We extend the usefulness of this information gain by proposing a nonparametric evaluation method of conditional entropy of a quantitative phenotype associated with a given genotype. Hence, the information gain can be obtained for any phenotype distribution. Because any functional form, such as Gaussian, is not assumed for the entire distribution of a trait or a given genotype, this method is expected to be robust enough to be applied to any phenotypic association data. Here, we show its use to successfully identify the main effect, as well as the genetic interactions, associated with a quantitative trait. PMID:26339620

Investigation of sorption interactions between oil shale principal mineral phases and organic compounds

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

Bowen, J.M.

1988-09-01

The interactions between minerals representative of the bulk composition of oil shales and organic compounds that have been found in oil shale leachates were investigated. The method used to directly determine the type of interactions that could take place between organic compounds and oil shale mineral phases was Fourier transform infrared spectroscopy (FTIR) using several advanced detection methods, including diffuse reflectance (DRIFT) and photoacoustics (PAS). The minerals that were investigated include quartz, calcite, and dolomite, which are known to figure significantly in the composition of processed oil shales. The organic chemical compounds used were chosen from a list of compoundsmore » identified in spent oil shale leachates, and they include pyridine, phenol, p-cresol, and acetone. The sorption interactions for the study were prepared by exposing each of the minerals to the organic compounds by three different methods. These were vapor deposition, direct application, and immersion in an aqueous solution at pH 12. 41 refs., 3 figs., 4 tabs.« less

Studying generalised dark matter interactions with extended halo-independent methods

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

Kahlhoefer, Felix; Wild, Sebastian

2016-10-20

The interpretation of dark matter direct detection experiments is complicated by the fact that neither the astrophysical distribution of dark matter nor the properties of its particle physics interactions with nuclei are known in detail. To address both of these issues in a very general way we develop a new framework that combines the full formalism of non-relativistic effective interactions with state-of-the-art halo-independent methods. This approach makes it possible to analyse direct detection experiments for arbitrary dark matter interactions and quantify the goodness-of-fit independent of astrophysical uncertainties. We employ this method in order to demonstrate that the degeneracy between astrophysicalmore » uncertainties and particle physics unknowns is not complete. Certain models can be distinguished in a halo-independent way using a single ton-scale experiment based on liquid xenon, while other models are indistinguishable with a single experiment but can be separated using combined information from several target elements.« less

Conservation of hot regions in protein-protein interaction in evolution.

PubMed

Hu, Jing; Li, Jiarui; Chen, Nansheng; Zhang, Xiaolong

2016-11-01

The hot regions of protein-protein interactions refer to the active area which formed by those most important residues to protein combination process. With the research development on protein interactions, lots of predicted hot regions can be discovered efficiently by intelligent computing methods, while performing biology experiments to verify each every prediction is hardly to be done due to the time-cost and the complexity of the experiment. This study based on the research of hot spot residue conservations, the proposed method is used to verify authenticity of predicted hot regions that using machine learning algorithm combined with protein's biological features and sequence conservation, though multiple sequence alignment, module substitute matrix and sequence similarity to create conservation scoring algorithm, and then using threshold module to verify the conservation tendency of hot regions in evolution. This research work gives an effective method to verify predicted hot regions in protein-protein interactions, which also provides a useful way to deeply investigate the functional activities of protein hot regions. Copyright © 2016. Published by Elsevier Inc.

Real-Time Analysis of Specific Protein-DNA Interactions with Surface Plasmon Resonance

PubMed Central

Ritzefeld, Markus; Sewald, Norbert

2012-01-01

Several proteins, like transcription factors, bind to certain DNA sequences, thereby regulating biochemical pathways that determine the fate of the corresponding cell. Due to these key positions, it is indispensable to analyze protein-DNA interactions and to identify their mode of action. Surface plasmon resonance is a label-free method that facilitates the elucidation of real-time kinetics of biomolecular interactions. In this article, we focus on this biosensor-based method and provide a detailed guide how SPR can be utilized to study binding of proteins to oligonucleotides. After a description of the physical phenomenon and the instrumental realization including fiber-optic-based SPR and SPR imaging, we will continue with a survey of immobilization methods. Subsequently, we will focus on the optimization of the experiment, expose pitfalls, and introduce how data should be analyzed and published. Finally, we summarize several interesting publications of the last decades dealing with protein-DNA and RNA interaction analysis by SPR. PMID:22500214

Introducing dyadic interviews as a method for collecting qualitative data.

PubMed

Morgan, David L; Ataie, Jutta; Carder, Paula; Hoffman, Kim

2013-09-01

In dyadic interviews, two participants interact in response to open-ended research questions. There are few precedents for using dyadic interviews as a technique for qualitative research. We introduce this method largely in comparison to focus groups, because both represent forms of interactive interviewing. We do not, however, view dyadic interviews as miniature focus groups, and treat them as generating their own opportunities and issues. To illustrate the nature of dyadic interviewing, we present summaries of three studies using this method. In the first study, we used dyadic interviews and photovoice techniques to examine experiences of people with early-stage dementia. In the second study, we explored the experiences of staff who provided services to elderly housing residents. In the third study, we examined barriers and facilitators to substance abuse treatment among Asian Americans and Pacific Islanders in Hawaii. We conclude with a discussion of directions for future research using dyadic interviews.

Methods to Assess the Direct Interaction of C. jejuni with Mucins.

PubMed

Clyne, Marguerite; Duggan, Gina; Naughton, Julie; Bourke, Billy

2017-01-01

Studies of the interaction of bacteria with mucus-secreting cells can be complemented at a more mechanistic level by exploring the interaction of bacteria with purified mucins. Here we describe a far Western blotting approach to show how C. jejuni proteins separated by SDS PAGE and transferred to a membrane or slot blotted directly onto a membrane can be probed using biotinylated mucin. In addition we describe the use of novel mucin microarrays to assess bacterial interactions with mucins in a high-throughput manner.

Considering social ergonomics: the effects of HIT on interpersonal relationships between patients and clinicians.

PubMed

Montague, Enid; Asan, Onur

2012-01-01

This study explored physicians' interactions with EHRs to understand the qualities that contribute to patient satisfaction with their use of the technologies and patient satisfaction with physician. Video-taped observations of 100 medical consultations were used to distinguish interaction patterns between physicians and EHRs. Quantified observational methods were used to contribute to ecological validity. Ten primary care physicians and 100 patients from five clinics participated in the study. Visits were videotaped and coded using an objective coding methodology to understand how physicians interacted with electronic health records. Results indicate, a variety of EHR interaction styles may be effective in providing patient-centered care.

Direct chill casting of aluminium alloys under electromagnetic interaction by permanent magnet assembly

NASA Astrophysics Data System (ADS)

Bojarevičs, Andris; Kaldre, Imants; Milgrāvis, Mikus; Beinerts, Toms

2018-05-01

Direct chill casting is one of the methods used in industry to obtain good microstructure and properties of aluminium alloys. Nevertheless, for some alloys grain structure is not optimal. In this study, we offer the use of electromagnetic interaction to modify melt convection near the solidification interface. Solidification under various electromagnetic interactions has been widely studied, but usually at low solidification velocity and high thermal gradient. This type of interaction may succeed fragmentation of dendrite arms and transport of solidification nuclei thus leading to improved material structure and properties. Realization of experimental small-scale crystallizer and electromagnetic system has been described in this article.

Regimen Difficulty and Medication Non-Adherence and the Interaction Effects of Gender and Age.

PubMed

Dalvi, Vidya; Mekoth, Nandakumar

2017-12-08

Medication non-adherence is a global health issue. Numerous factors predict it. This study is aimed to identify the association between regimen difficulty and medication non-adherence among patients with chronic conditions and testing the interaction effects of gender and age on the same. It was a cross-sectional study conducted among 479 outpatients from India. Convenience sampling method was used. Multiple regression analyses were performed to find the predictors of non-adherence and to test interaction effects. Regimen difficulty predicted medication non-adherence. The patient's gender and age have interaction effects on the relationship between regimen difficulty and medication non-adherence.

The effectiveness of hydrotherapy in the treatment of social and behavioral aspects of children with autism spectrum disorders: a systematic review.

PubMed

Mortimer, Rachel; Privopoulos, Melinda; Kumar, Saravana

2014-01-01

Autism spectrum disorders (ASDs) are increasing in prevalence. Children with ASDs present with impairments in social interactions; communication; restricted, repetitive, and stereotyped patterns of behavior, interests, or activities; as well as motor delays. Hydrotherapy is used as a treatment for children with disabilities and motor delays. There have been no systematic reviews conducted on the effectiveness of hydrotherapy in children with ASDs. We aimed to examine the effectiveness of hydrotherapy on social interactions and behaviors in the treatment of children with ASDs. A systematic search of Cochrane, CINAHL, PsycINFO, Embase, MEDLINE®, and Academic Search Premier was conducted. Studies of participants, aged 3-18 years, with ASDs at a high-functioning level were included if they utilized outcome measures assessing social interactions and behaviors through questionnaire or observation. A critical appraisal, using the McMaster Critical Review Form for Quantitative Studies, was performed to assess methodological quality. Four studies of varying research design and quality met the inclusion criteria. The participants in these studies were aged between 3-12 years of age. The duration of the intervention ranged from 10-14 weeks, and each study used varied measures of outcome. Overall, all the studies showed some improvements in social interactions or behaviors following a Halliwick-based hydrotherapy intervention. Few studies have investigated the effect of hydrotherapy on the social interactions and behaviors of children with ASDs. While there is an increasing body of evidence for hydrotherapy for children with ASDs, this is constrained by small sample size, lack of comparator, crude sampling methods, and the lack of standardized outcome measures. Hydrotherapy shows potential as a treatment method for social interactions and behaviors in children with ASDs.

Evaluation of three methods of different levels of complexity to represent the interactions between the Greenland ice sheet and the atmosphere at the century time scale.

NASA Astrophysics Data System (ADS)

Le clec'h, Sébastien; Fettweis, Xavier; Quiquet, Aurelien; Dumas, Christophe; Kageyama, Masa; Charbit, Sylvie; Ritz, Catherine

2017-04-01

Based on numerous studies showing implications of polar ice sheets on the climate system, the climate community recommended the development of methods to account for feedbacks between polar ice sheets and the other climate components. In this study we used three methods of different levels of complexity to represent the interactions between a Greenland ice sheet model (GRISLI) and a regional atmospheric model (MAR) under the RCP8.5 scenario. The simplest method, i.e. uncoupled, does not account for interactions between both models. In this method MAR computes varying atmospheric conditions using the same present-day observed Greenland ice sheet topography and extent. The outputs are then used to force GRISLI. The second method is a one-way coupling method in which the MAR outputs are corrected to account for topography changes before their transfer to GRISLI. The third method is a fully coupled method allowing the full representation of interactions between MAR and GRISLI. In this case, the ice sheet topography and its extent as seen by the atmospheric model is updated for each ice sheet model time step. The three methods are evaluated regarding the Greenland ice sheet response from 2000 to 2150. As expected, the uncoupled method shows a coastal thinning of the ice sheet due to a decreasing surface mass balance for coastal regions related to increased mean surface temperature. The one-way coupling and the full coupling methods tend to amplify the surface mass balance due to surface elevation feedback. The uncoupled method tends to underestimate the Greenland ice sheet volume reduction compared to both coupling methods over 150 years. This underestimation is of the same order of magnitude of the ice loss from the Greenland peripheral glaciers at the end of the 21st century. As for the uncoupled method, the thinning of the ice sheet occurs in coastal regions for both coupling methods. However compared to the one-way coupling method, the fully coupled method tends to increase the spatial variability of the surface mass balance changes through time. Our results also indicate that differences between the two coupling methods increase with time, which suggests that the choice of the method should depend on the timescale considered. Beyond century scale projections the fully coupled method is necessary in order to avoid underestimation of the ice sheet volume reduction, whilst the one-way method seems to be sufficient to represent the interactions between the atmosphere and the GrIS for projections by the end of the century.

Toward an Enhanced Sampling Molecular Dynamics Method for Studying Ligand-Induced Conformational Changes in Proteins.

PubMed

Andersen, Ole Juul; Grouleff, Julie; Needham, Perri; Walker, Ross C; Jensen, Frank

2015-11-19

Current enhanced sampling molecular dynamics methods for studying large conformational changes in proteins suffer from certain limitations. These include, among others, the need for user defined collective variables, the prerequisite of both start and end point structures of the conformational change, and the need for a priori knowledge of the amount by which to boost specific parts of the potential. In this paper, a framework is proposed for a molecular dynamics method for studying ligand-induced conformational changes, in which the nonbonded interactions between the ligand and the protein are used to calculate a biasing force. The method requires only a single input structure, and does not entail the use of collective variables. We provide a proof-of-concept for accelerating conformational changes in three simple test molecules, as well as promising results for two proteins known to undergo domain closure upon ligand binding. For the ribose-binding protein, backbone root-mean-square deviations as low as 0.75 Å compared to the crystal structure of the closed conformation are obtained within 50 ns simulations, whereas no domain closures are observed in unbiased simulations. A skewed closed structure is obtained for the glutamine-binding protein at high bias values, indicating that specific protein-ligand interactions might suppress important protein-protein interactions.

Human patient simulators and interactive case studies: a comparative analysis of learning outcomes and student perceptions.

PubMed

Howard, Valerie Michele; Ross, Carl; Mitchell, Ann M; Nelson, Glenn M

2010-01-01

Although human patient simulators provide an innovative teaching method for nursing students, they are quite expensive. To investigate the value of this expenditure, a quantitative, quasi-experimental, two-group pretest and posttest design was used to compare two educational interventions: human patient simulators and interactive case studies. The sample (N = 49) consisted of students from baccalaureate, accelerated baccalaureate, and diploma nursing programs. Custom-designed Health Education Systems, Inc examinations were used to measure knowledge before and after the implementation of the two educational interventions. Students in the human patient simulation group scored significantly higher than did those in the interactive case study group on the posttest Health Education Systems, Inc examination, and no significant difference was found in student scores among the three types of nursing programs that participated in the study. Data obtained from a questionnaire administered to participants indicated that students responded favorably to the use of human patient simulators as a teaching method.

Studies of aerothermal loads generated in regions of shock/shock interaction in hypersonic flow

NASA Technical Reports Server (NTRS)

Holden, Michael S.; Moselle, John R.; Lee, Jinho

1991-01-01

Experimental studies were conducted to examine the aerothermal characteristics of shock/shock/boundary layer interaction regions generated by single and multiple incident shocks. The presented experimental studies were conducted over a Mach number range from 6 to 19 for a range of Reynolds numbers to obtain both laminar and turbulent interaction regions. Detailed heat transfer and pressure measurements were made for a range of interaction types and incident shock strengths over a transverse cylinder, with emphasis on the 3 and 4 type interaction regions. The measurements were compared with the simple Edney, Keyes, and Hains models for a range of interaction configurations and freestream conditions. The complex flowfields and aerothermal loads generated by multiple-shock impingement, while not generating as large peak loads, provide important test cases for code prediction. The detailed heat transfer and pressure measurements proved a good basis for evaluating the accuracy of simple prediction methods and detailed numerical solutions for laminar and transitional regions or shock/shock interactions.

Learning and cognitive styles in web-based learning: theory, evidence, and application.

PubMed

Cook, David A

2005-03-01

Cognitive and learning styles (CLS) have long been investigated as a basis to adapt instruction and enhance learning. Web-based learning (WBL) can reach large, heterogenous audiences, and adaptation to CLS may increase its effectiveness. Adaptation is only useful if some learners (with a defined trait) do better with one method and other learners (with a complementary trait) do better with another method (aptitude-treatment interaction). A comprehensive search of health professions education literature found 12 articles on CLS in computer-assisted learning and WBL. Because so few reports were found, research from non-medical education was also included. Among all the reports, four CLS predominated. Each CLS construct was used to predict relationships between CLS and WBL. Evidence was then reviewed to support or refute these predictions. The wholist-analytic construct shows consistent aptitude-treatment interactions consonant with predictions (wholists need structure, a broad-before-deep approach, and social interaction, while analytics need less structure and a deep-before-broad approach). Limited evidence for the active-reflective construct suggests aptitude-treatment interaction, with active learners doing better with interactive learning and reflective learners doing better with methods to promote reflection. As predicted, no consistent interaction between the concrete-abstract construct and computer format was found, but one study suggests that there is interaction with instructional method. Contrary to predictions, no interaction was found for the verbal-imager construct. Teachers developing WBL activities should consider assessing and adapting to accommodate learners defined by the wholist-analytic and active-reflective constructs. Other adaptations should be considered experimental. Further WBL research could clarify the feasibility and effectiveness of assessing and adapting to CLS.

The Role of Clinical Pharmacists in Educating Nurses to Reduce Drug-Food Interactions (Absorption Phase) in Hospitalized Patients

PubMed Central

Abbasi Nazari, Mohammad; Salamzadeh, Jamshid; Hajebi, Giti; Gilbert, Benjamin

2011-01-01

Drug-food interactions can increase or decrease drug effects, resulting in therapeutic failure or toxicity. Activities that reduce these interactions play an important role for clinical pharmacists. This study was planned and performed in order to determine the role of clinical pharmacist in the prevention of absorption drug-food interactions through educating the nurses in a teaching hospital affiliated to Shahid Beheshti University of Medical Sciences, Tehran, Iran. The rate of interactions was determined using direct observation methods before and after the nurse training courses in four wards including gastrointestinal-liver, endocrine, vascular surgery and nephrology. Training courses consisted of the nurse attendance lecture delivered by a clinical pharmacist which included receiving information pamphlets. Total incorrect drug administration fell down from 44.6% to 31.5%. The analysis showed that the rate of absorption drug-food interactions significantly decreased after the nurse training courses (p < 0.001). Clinical pharmacist can play an important role in nurse training as an effective method to reduce drug-food interactions in hospitals. PMID:24363698

Inferring Mechanisms of Compensation from E-MAP and SGA Data Using Local Search Algorithms for Max Cut

NASA Astrophysics Data System (ADS)

Leiserson, Mark D. M.; Tatar, Diana; Cowen, Lenore J.; Hescott, Benjamin J.

A new method based on a mathematically natural local search framework for max cut is developed to uncover functionally coherent module and BPM motifs in high-throughput genetic interaction data. Unlike previous methods which also consider physical protein-protein interaction data, our method utilizes genetic interaction data only; this becomes increasingly important as high-throughput genetic interaction data is becoming available in settings where less is known about physical interaction data. We compare modules and BPMs obtained to previous methods and across different datasets. Despite needing no physical interaction information, the BPMs produced by our method are competitive with previous methods. Biological findings include a suggested global role for the prefoldin complex and a SWR subcomplex in pathway buffering in the budding yeast interactome.

Inferring mechanisms of compensation from E-MAP and SGA data using local search algorithms for max cut.

PubMed

Leiserson, Mark D M; Tatar, Diana; Cowen, Lenore J; Hescott, Benjamin J

2011-11-01

A new method based on a mathematically natural local search framework for max cut is developed to uncover functionally coherent module and BPM motifs in high-throughput genetic interaction data. Unlike previous methods, which also consider physical protein-protein interaction data, our method utilizes genetic interaction data only; this becomes increasingly important as high-throughput genetic interaction data is becoming available in settings where less is known about physical interaction data. We compare modules and BPMs obtained to previous methods and across different datasets. Despite needing no physical interaction information, the BPMs produced by our method are competitive with previous methods. Biological findings include a suggested global role for the prefoldin complex and a SWR subcomplex in pathway buffering in the budding yeast interactome.

Prediction and Reduction of Noise in Pneumatic Bleed Valves

NASA Astrophysics Data System (ADS)

Taghavi Nezhad, Shervin

This study investigates numerically the fluid mechanics and acoustics of pneumatic bleed valves used in turbofan engines. The goal is to characterized the fundamental processes of noise generation and devise strategies for noise reduction. Three different methods are employed for both analysis and redesign of the bleed valve to reduce noise. The bleed valve noise problem is carefully divided into multiple smaller problems. For large separations and tonal noises, the unsteady Reynolds-Averaged Navier-Stokes (URANS) method is utilized. This method is also applied in the re-designing of the bleed valve geometry. For the bleed valve muffler, which is comprised of perforated plates and a honeycomb, a Reynolds-Averaged Navier-Stokes (RANS) method combined with a simplified acoustic analogy is used. The original muffler design is modified to improve noise attenuation. Finally, for sound scattering through perforated plates, a fully implicit linearized Euler solver is developed. The problem of sound interaction with perforated plates is studied from two perspectives. In the first study the effect of high--speed mean flow is considered and it is shown that at Strouhal numbers of around 0.2-0.25 there is an increase in transmitted incident sound. In the second part, the interaction of holes in two--dimensional perforated plates is investigated using three different configurations. The study demonstrates that the hole interaction has a significant impact on sound attenuation, especially at high frequencies.

Gene function prediction with gene interaction networks: a context graph kernel approach.

PubMed

Li, Xin; Chen, Hsinchun; Li, Jiexun; Zhang, Zhu

2010-01-01

Predicting gene functions is a challenge for biologists in the postgenomic era. Interactions among genes and their products compose networks that can be used to infer gene functions. Most previous studies adopt a linkage assumption, i.e., they assume that gene interactions indicate functional similarities between connected genes. In this study, we propose to use a gene's context graph, i.e., the gene interaction network associated with the focal gene, to infer its functions. In a kernel-based machine-learning framework, we design a context graph kernel to capture the information in context graphs. Our experimental study on a testbed of p53-related genes demonstrates the advantage of using indirect gene interactions and shows the empirical superiority of the proposed approach over linkage-assumption-based methods, such as the algorithm to minimize inconsistent connected genes and diffusion kernels.

Effectiveness of Parent-Child Interaction Therapy (PCIT) among Chinese Families

ERIC Educational Resources Information Center

Leung, Cynthia; Tsang, Sandra; Heung, Kitty; Yiu, Ivan

2009-01-01

Objective: This study examined the effectiveness of Parent-Child Interaction Therapy (PCIT) among Chinese parents and children in Hong Kong with significant behavior problems. Method: The participants (intervention group, 48; comparison group, 62) completed questionnaires on child behavior problems and parenting stress before and after…

An Exploration of Interactions between Virtual Mentors and Preservice Teachers

ERIC Educational Resources Information Center

Reese, Jill

2017-01-01

This study describes interactions between preservice music teachers and experienced teachers during virtual mentoring sessions embedded in field experiences for an elementary general music methods course. Participants were preservice music teachers (mentees) and experienced teachers (mentors). Videos of six mentoring sessions were transcribed,…

Recent Empirical Studies of the Pedagogical Effects of Interactive Video Instruction in "Soft Skill" Areas.

ERIC Educational Resources Information Center

Cronin, Michael W.; Cronin, Karen A.

1992-01-01

Recent empirical research has identified significant advantages for interactive video instruction over traditional teaching methods in "soft skill" (humanities and social sciences) areas, including cognitive achievement, transfer of learning to performance, learning motivation, student achievement across uncontrolled student characteristics, user…

An Investigation of Technological Innovation: Interactive Television.

ERIC Educational Resources Information Center

Robinson, Rhonda S.

A 5-year case study was implemented to evaluate the two-way Carroll Instructional Television Consortium, which utilizes a cable television network serving four school districts in Illinois. This network permits simultaneous video and audio interactive communication among four high schools. The naturalistic inquiry method employed included…

Cautions: Implementing Interpersonal Interaction in Workplace E-Learning

ERIC Educational Resources Information Center

Githens, Rod P.

2006-01-01

E-learning programs in workplaces have been slow to incorporate social and collaborative methods. Although these programs provide flexibility and cost savings, poor learning outcomes and low completion rates have caused some organizations to transition to approaches that include interpersonal interaction. In reviewing studies of e-learning…

Progress on first-principles-based materials design for hydrogen storage.

PubMed

Park, Noejung; Choi, Keunsu; Hwang, Jeongwoon; Kim, Dong Wook; Kim, Dong Ok; Ihm, Jisoon

2012-12-04

This article briefly summarizes the research activities in the field of hydrogen storage in sorbent materials and reports our recent works and future directions for the design of such materials. Distinct features of sorption-based hydrogen storage methods are described compared with metal hydrides and complex chemical hydrides. We classify the studies of hydrogen sorbent materials in terms of two key technical issues: (i) constructing stable framework structures with high porosity, and (ii) increasing the binding affinity of hydrogen molecules to surfaces beyond the usual van der Waals interaction. The recent development of reticular chemistry is summarized as a means for addressing the first issue. Theoretical studies focus mainly on the second issue and can be grouped into three classes according to the underlying interaction mechanism: electrostatic interactions based on alkaline cations, Kubas interactions with open transition metals, and orbital interactions involving Ca and other nontransitional metals. Hierarchical computational methods to enable the theoretical predictions are explained, from ab initio studies to molecular dynamics simulations using force field parameters. We also discuss the actual delivery amount of stored hydrogen, which depends on the charging and discharging conditions. The usefulness and practical significance of the hydrogen spillover mechanism in increasing the storage capacity are presented as well.

Progress on first-principles-based materials design for hydrogen storage

PubMed Central

Park, Noejung; Choi, Keunsu; Hwang, Jeongwoon; Kim, Dong Wook; Kim, Dong Ok; Ihm, Jisoon

2012-01-01

This article briefly summarizes the research activities in the field of hydrogen storage in sorbent materials and reports our recent works and future directions for the design of such materials. Distinct features of sorption-based hydrogen storage methods are described compared with metal hydrides and complex chemical hydrides. We classify the studies of hydrogen sorbent materials in terms of two key technical issues: (i) constructing stable framework structures with high porosity, and (ii) increasing the binding affinity of hydrogen molecules to surfaces beyond the usual van der Waals interaction. The recent development of reticular chemistry is summarized as a means for addressing the first issue. Theoretical studies focus mainly on the second issue and can be grouped into three classes according to the underlying interaction mechanism: electrostatic interactions based on alkaline cations, Kubas interactions with open transition metals, and orbital interactions involving Ca and other nontransitional metals. Hierarchical computational methods to enable the theoretical predictions are explained, from ab initio studies to molecular dynamics simulations using force field parameters. We also discuss the actual delivery amount of stored hydrogen, which depends on the charging and discharging conditions. The usefulness and practical significance of the hydrogen spillover mechanism in increasing the storage capacity are presented as well. PMID:23161910

Kinetic and thermodynamic study of bovine serum albumin interaction with rifampicin using surface plasmon resonance and molecular docking methods

NASA Astrophysics Data System (ADS)

Sharifi, Maryam; Dolatabadi, Jafar Ezzati Nazhad; Fathi, Farzaneh; Rashidi, Mohammad; Jafari, Behzad; Tajalli, Habib; Rashidi, Mohammad-Reza

2017-03-01

The interaction of bovine serum albumin (BSA) with various drugs, such as antibiotics, due to the importance of BSA in drug delivery has attracted increasing research attention at present. Therefore, the aim of this study was investigation of BSA interaction with rifampicin using surface plasmon resonance (SPR) and molecular docking methods under the imitated physiological conditions (pH=7.4). BSA immobilization on carboxymethyl dextran hydrogel chip has been carried out after activation with N-hydroxysuccinimide/N-ethyl-N-(3-diethylaminopropyl) carbodiimide. The dose-response sensorgrams of BSA upon increasing concentration of refampicin were attained in SPR analysis. The high affinity of rifampicin to BSA was demonstrated by a low equilibrium constants (KD) value (3.46×10-5 at 40°C). The process of kinetic values changing shows that affinity of BSA to rifampicin decreased with rising temperature. The positive value of both enthalpy change (ΔH) and entropy change (ΔS) showed that hydrophobic force plays major role in the BSA interaction with rifampicin. The positive value of ΔG was indicative of nonspontaneous and enthalpy-driven binding process. In addition, according to the molecular docking study, hydrogen binding has some contributions in the interaction of rifampicin with BSA.

Comparing High Definition Live Interactive and Store-and-Forward Consultations to In-Person Examinations

PubMed Central

Locatis, Craig; Burges, Gene; Maisiak, Richard; Liu, Wei-Li; Ackerman, Michael

2017-01-01

Abstract Background: There is little teledermatology research directly comparing remote methods, even less research with two in-person dermatologist agreement providing a baseline for comparing remote methods, and no research using high definition video as a live interactive method. Objective: To compare in-person consultations with store-and-forward and live interactive methods, the latter having two levels of image quality. Methods: A controlled study was conducted where patients were examined in-person, by high definition video, and by store-and-forward methods. The order patients experienced methods and residents assigned methods rotated, although an attending always saw patients in-person. The type of high definition video employed, lower resolution compressed or higher resolution uncompressed, was alternated between clinics. Primary and differential diagnoses, biopsy recommendations, and diagnostic and biopsy confidence ratings were recorded. Results: Concordance and confidence were significantly better for in-person versus remote methods and biopsy recommendations were lower. Store-and-forward and higher resolution uncompressed video results were similar and better than those for lower resolution compressed video. Limitations: Dermatology residents took store-and-forward photos and their quality was likely superior to those normally taken in practice. There were variations in expertise between the attending and second and third year residents. Conclusion: The superiority of in-person consultations suggests the tendencies to order more biopsies or still see patients in-person are often justified in teledermatology and that high resolution uncompressed video can close the resolution gap between store-and-forward and live interactive methods. PMID:27705083

[Framework on drug interactions between herbal medicine and western medicine: building Ⅰ/Ⅱ/Ⅲ class pathways of interactions].

PubMed

Jin, Rui; Huang, Jian-Mei; Wang, Yu-Guang; Zhang, Bing

2016-02-01

Combined use of Chinese medicine and western medicine is one of the hot spots in the domestic medical and academic fields for many years. There are lots of involved reports and studies on interaction problems due to combined used of Chinese medicine and western medicine, however, framework understanding is still rarely seen, affecting the clinical rationality of drug combinations. Actually, the inference ideas of drug interactions in clinical practice are more extensive and practical, and the overall viewpoint and pragmatic idea are the important factors in evaluating the rationality of clinical drug combinations. Based on above points, this paper systemically analyzed the existing information and examples, deeply discuss the embryology background (environment and action mechanism of interactions), and principally divided the interactions into three important and independent categories. Among the three categories, the first category (Ⅰapproach) was defined as the physical/chemical reactions after direct contact in vivo or in vitro, such as the combination of Chinese medicine injections and western medicine injections (in vitro), combination of bromide and Chinese medicines containing cinnabar (in vivo). The evaluation method for such interactions may be generalized theory of Acid-Base reaction. The second category (Ⅱ approach) was defined as the interactions through the pharmacokinetic process including absorption (such as the combination of aspirin and Huowei capsule), distribution (such as the combination of artosin and medicinal herbs containing coumarin), metabolism (such as the combination of phenobarbital and glycyrrhiza) and excretion (such as the combination of furadantin and Crataegi Fructus). The existing pharmacokinetic theory can act as the evaluation method for this type of interaction. The third category (Ⅲ approach) was defined as the synergy/antagonism interactions by pharmacological effects or biological pathways. The combination of warfarin and Salvia miltiorrhiza is an example for synergy interaction, while the combination of guanethidine and ephedra is an example for anatagonism interaction. The repeated application of Chinese and western medicine compound preparations and same type of western medicine also belongs to this approach. The receptor competition theory under the view of the overall pathways might act as the evaluation method for this type of interactions. Above all, the research framework on interactions between Chinese medicine and western medicine was proposed, providing overall thinking and support for the essential study on combined application of Chinese medicine and western medicine. Copyright© by the Chinese Pharmaceutical Association.

Interactive Multimedia Training in Osteoporosis Prevention of Female High School Students: An Interventional Study.

PubMed

Zarshenas, Ladan; Keshavarz, Tala; Momennasab, Marzieh; Zarifsanaiey, Nahid

2017-08-01

Given the limitations of traditional teaching methods in the learning process of adolescents, this study was designed to investigate the effects of osteoporosis prevention training through interactive multimedia method on the degree of knowledge and self-efficacy of female high school students. In this interventional study which was conducted in 2016 in Fars province, Iran, 120 high school students were selected through proportional stratified sampling from schools and different classes at first, second, third, and pre-university grades. The participants were randomly divided into two groups, each containing 60 students. Educational interventions for the test group included an interactive multimedia CD, and for the control group was an educational booklet. Before and one month after the intervention the students' level of knowledge and self-efficacy was measured. The spss 19 statistical software was used, and descriptive and analytical tests were performed to analyze the data. Results showed a significant difference in self-efficacy scores after the intervention (P=0.012) with the test group obtained a higher self-efficacy score than the control group. Also, a significant increase was observed in the knowledge score of both groups after the training (P<0.001), but the knowledge score between the two groups was not statistically significant (P=0.38) after the intervention. The use of new training methods like interactive multimedia CD for public education, particular adolescents about health and hygiene is recommended.

Boosting for detection of gene-environment interactions.

PubMed

Pashova, H; LeBlanc, M; Kooperberg, C

2013-01-30

In genetic association studies, it is typically thought that genetic variants and environmental variables jointly will explain more of the inheritance of a phenotype than either of these two components separately. Traditional methods to identify gene-environment interactions typically consider only one measured environmental variable at a time. However, in practice, multiple environmental factors may each be imprecise surrogates for the underlying physiological process that actually interacts with the genetic factors. In this paper, we develop a variant of L(2) boosting that is specifically designed to identify combinations of environmental variables that jointly modify the effect of a gene on a phenotype. Because the effect modifiers might have a small signal compared with the main effects, working in a space that is orthogonal to the main predictors allows us to focus on the interaction space. In a simulation study that investigates some plausible underlying model assumptions, our method outperforms the least absolute shrinkage and selection and Akaike Information Criterion and Bayesian Information Criterion model selection procedures as having the lowest test error. In an example for the Women's Health Initiative-Population Architecture using Genomics and Epidemiology study, the dedicated boosting method was able to pick out two single-nucleotide polymorphisms for which effect modification appears present. The performance was evaluated on an independent test set, and the results are promising. Copyright © 2012 John Wiley & Sons, Ltd.

Competing interactions in semiconductor quantum dots

DOE PAGES

van den Berg, R.; Brandino, G. P.; El Araby, O.; ...

2014-10-14

In this study, we introduce an integrability-based method enabling the study of semiconductor quantum dot models incorporating both the full hyperfine interaction as well as a mean-field treatment of dipole-dipole interactions in the nuclear spin bath. By performing free induction decay and spin echo simulations we characterize the combined effect of both types of interactions on the decoherence of the electron spin, for external fields ranging from low to high values. We show that for spin echo simulations the hyperfine interaction is the dominant source of decoherence at short times for low fields, and competes with the dipole-dipole interactions atmore » longer times. On the contrary, at high fields the main source of decay is due to the dipole-dipole interactions. In the latter regime an asymmetry in the echo is observed. Furthermore, the non-decaying fraction previously observed for zero field free induction decay simulations in quantum dots with only hyperfine interactions, is destroyed for longer times by the mean-field treatment of the dipolar interactions.« less

Interaction of Benzimidazoles and Benzotriazole: Its Corrosion Protection Properties on Mild Steel in Hydrochloric Acid

NASA Astrophysics Data System (ADS)

Ramya, K.; Mohan, Revathi; Joseph, Abraham

2014-11-01

Synergistic hydrogen-bonded interaction of alkyl benzimidazoles and 1,2,3-benzotrizole and its corrosion protection properties on mild steel in hydrochloric acid at different temperatures have been studied using polarization, EIS, adsorption, surface studies, and computational methods. The extent of synergistic interaction increases with temperature. Quantum chemical approach is used to calculate some electronic properties of the molecules and to ascertain the synergistic interaction, inhibitive effect, and molecular structures. The corrosion inhibition efficiencies and the global chemical reactivity relate to some parameters, such as total energy, E HOMO, E LUMO, and gap energy (Δ E). 1,2,3-Benzotrizole interacts with benzimidazoles derivatives up to a bond length of approximately 1.99 Å. This interaction represents the formation of a hydrogen bond between the 1,2,3-benzotrizole and benzimidazoles. This synergistic interaction of 1,2,3-benzotrizole and benzimidazole derivatives offers extended inhibition efficiency toward mild steel in hydrochloric acid.

Krylov subspace methods for computing hydrodynamic interactions in Brownian dynamics simulations

PubMed Central

Ando, Tadashi; Chow, Edmond; Saad, Yousef; Skolnick, Jeffrey

2012-01-01

Hydrodynamic interactions play an important role in the dynamics of macromolecules. The most common way to take into account hydrodynamic effects in molecular simulations is in the context of a Brownian dynamics simulation. However, the calculation of correlated Brownian noise vectors in these simulations is computationally very demanding and alternative methods are desirable. This paper studies methods based on Krylov subspaces for computing Brownian noise vectors. These methods are related to Chebyshev polynomial approximations, but do not require eigenvalue estimates. We show that only low accuracy is required in the Brownian noise vectors to accurately compute values of dynamic and static properties of polymer and monodisperse suspension models. With this level of accuracy, the computational time of Krylov subspace methods scales very nearly as O(N2) for the number of particles N up to 10 000, which was the limit tested. The performance of the Krylov subspace methods, especially the “block” version, is slightly better than that of the Chebyshev method, even without taking into account the additional cost of eigenvalue estimates required by the latter. Furthermore, at N = 10 000, the Krylov subspace method is 13 times faster than the exact Cholesky method. Thus, Krylov subspace methods are recommended for performing large-scale Brownian dynamics simulations with hydrodynamic interactions. PMID:22897254

Ab-initio adsorption study of chitosan on functionalized graphene: critical role of van der Waals interactions.

PubMed

Rahman, R; Mazumdar, D

2012-03-01

We investigate the adsorption process of an organic biomolecule (chitosan) on epoxy-functionalized graphene using ab-initio density functional methods incorporating van-der-waals (vdW) interactions. The role of London dispersion force on the cohesive energy and conformal preference of the molecule is quantitatively elucidated. Functionalizing graphene with epoxy leads to weak hydrogen-bond interactions with chitosan. Binding energy values increase by over an order of magnitude after including vdW corrections, implying that dispersive interactions dominate the physisorption process. Conformal study show binding upto 30 kcal/mol when the molecule is oriented with the hydroxyl group approaching the functionalized graphene. Our study advances the promise of functionalized graphene for a variety of applications.

Studies of HZE particle interactions and transport for space radiation protection purposes

NASA Technical Reports Server (NTRS)

Townsend, Lawrence W.; Wilson, John W.; Schimmerling, Walter; Wong, Mervyn

1987-01-01

The main emphasis is on developing general methods for accurately predicting high-energy heavy ion (HZE) particle interactions and transport for use by researchers in mission planning studies, in evaluating astronaut self-shielding factors, and in spacecraft shield design and optimization studies. The two research tasks are: (1) to develop computationally fast and accurate solutions to the Boltzmann (transport) equation; and (2) to develop accurate HZE interaction models, from fundamental physical considerations, for use as inputs into these transport codes. Accurate solutions to the HZE transport problem have been formulated through a combination of analytical and numerical techniques. In addition, theoretical models for the input interaction parameters are under development: stopping powers, nuclear absorption cross sections, and fragmentation parameters.

Coevolution study of mitochondria respiratory chain proteins: toward the understanding of protein--protein interaction.

PubMed

Yang, Ming; Ge, Yan; Wu, Jiayan; Xiao, Jingfa; Yu, Jun

2011-05-20

Coevolution can be seen as the interdependency between evolutionary histories. In the context of protein evolution, functional correlation proteins are ever-present coordinated evolutionary characters without disruption of organismal integrity. As to complex system, there are two forms of protein--protein interactions in vivo, which refer to inter-complex interaction and intra-complex interaction. In this paper, we studied the difference of coevolution characters between inter-complex interaction and intra-complex interaction using "Mirror tree" method on the respiratory chain (RC) proteins. We divided the correlation coefficients of every pairwise RC proteins into two groups corresponding to the binary protein--protein interaction in intra-complex and the binary protein--protein interaction in inter-complex, respectively. A dramatical discrepancy is detected between the coevolution characters of the two sets of protein interactions (Wilcoxon test, p-value = 4.4 × 10(-6)). Our finding reveals some critical information on coevolutionary study and assists the mechanical investigation of protein--protein interaction. Furthermore, the results also provide some unique clue for supramolecular organization of protein complexes in the mitochondrial inner membrane. More detailed binding sites map and genome information of nuclear encoded RC proteins will be extraordinary valuable for the further mitochondria dynamics study. Copyright © 2011. Published by Elsevier Ltd.

Symmetry-preserving contact interaction model for heavy-light mesons

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

Serna, F. E.; Brito, M. A.; Krein, G.

2016-01-22

We use a symmetry-preserving regularization method of ultraviolet divergences in a vector-vector contact interaction model for low-energy QCD. The contact interaction is a representation of nonperturbative kernels used Dyson-Schwinger and Bethe-Salpeter equations. The regularization method is based on a subtraction scheme that avoids standard steps in the evaluation of divergent integrals that invariably lead to symmetry violation. Aiming at the study of heavy-light mesons, we have implemented the method to the pseudoscalar π and K mesons. We have solved the Dyson-Schwinger equation for the u, d and s quark propagators, and obtained the bound-state Bethe-Salpeter amplitudes in a way thatmore » the Ward-Green-Takahashi identities reflecting global symmetries of the model are satisfied for arbitrary routing of the momenta running in loop integrals.« less

Properties of Ni^+ from microwave spectroscopy of n=9 Rydberg levels of Nickel

NASA Astrophysics Data System (ADS)

Woods, Shannon; Keele, Julie; Smith, Chris; Lundeen, Stephen

2012-06-01

The microwave/RESIS method was used to determine the relative positions of 15 of the n=9 Rydberg levels of Nickel with L >= 6. Because the ground state of the Ni^+ ion is a ^2D5/2 level, each Rydberg level (n,L) splits into six eigenstates whose relative positions are determined by long-range e-Ni^+ interactions present in addition to the dominant Coulomb interaction. A previous study with the optical RESIS method determined these positions with precision of +/- 30 MHz [1]. Using the microwave/RESIS method improves that precision by a factor of 300, and leads to much improved determinations of the Ni+ properties that control the long-range interactions. [4pt] [1] Julie A. Keele, Shannon L. Woods, M.E. Hanni, and S.R. Lundeen Phys. Rev. 81, 022506 (2010)

Changes in Patterns of Teacher Interaction in Primary Classrooms: 1976-96.

ERIC Educational Resources Information Center

Galton, Maurice; Hargreaves, Linda; Comber, Chris; Wall, Debbie; Pell, Tony

1999-01-01

Addresses the effectiveness of teaching methods in English primary school classrooms. Evaluates the interventions designed to change primary educators' teaching methods by replicating the Observational Research and Classroom Learning Evaluation (ORACLE) study that was originally conducted in 1976. Compares the results from the original study to…

Plant microRNA-Target Interaction Identification Model Based on the Integration of Prediction Tools and Support Vector Machine

PubMed Central

Meng, Jun; Shi, Lin; Luan, Yushi

2014-01-01

Background Confident identification of microRNA-target interactions is significant for studying the function of microRNA (miRNA). Although some computational miRNA target prediction methods have been proposed for plants, results of various methods tend to be inconsistent and usually lead to more false positive. To address these issues, we developed an integrated model for identifying plant miRNA–target interactions. Results Three online miRNA target prediction toolkits and machine learning algorithms were integrated to identify and analyze Arabidopsis thaliana miRNA-target interactions. Principle component analysis (PCA) feature extraction and self-training technology were introduced to improve the performance. Results showed that the proposed model outperformed the previously existing methods. The results were validated by using degradome sequencing supported Arabidopsis thaliana miRNA-target interactions. The proposed model constructed on Arabidopsis thaliana was run over Oryza sativa and Vitis vinifera to demonstrate that our model is effective for other plant species. Conclusions The integrated model of online predictors and local PCA-SVM classifier gained credible and high quality miRNA-target interactions. The supervised learning algorithm of PCA-SVM classifier was employed in plant miRNA target identification for the first time. Its performance can be substantially improved if more experimentally proved training samples are provided. PMID:25051153

Economic evaluation of factorial randomised controlled trials: challenges, methods and recommendations

PubMed Central

Gray, Alastair

2017-01-01

Increasing numbers of economic evaluations are conducted alongside randomised controlled trials. Such studies include factorial trials, which randomise patients to different levels of two or more factors and can therefore evaluate the effect of multiple treatments alone and in combination. Factorial trials can provide increased statistical power or assess interactions between treatments, but raise additional challenges for trial‐based economic evaluations: interactions may occur more commonly for costs and quality‐adjusted life‐years (QALYs) than for clinical endpoints; economic endpoints raise challenges for transformation and regression analysis; and both factors must be considered simultaneously to assess which treatment combination represents best value for money. This article aims to examine issues associated with factorial trials that include assessment of costs and/or cost‐effectiveness, describe the methods that can be used to analyse such studies and make recommendations for health economists, statisticians and trialists. A hypothetical worked example is used to illustrate the challenges and demonstrate ways in which economic evaluations of factorial trials may be conducted, and how these methods affect the results and conclusions. Ignoring interactions introduces bias that could result in adopting a treatment that does not make best use of healthcare resources, while considering all interactions avoids bias but reduces statistical power. We also introduce the concept of the opportunity cost of ignoring interactions as a measure of the bias introduced by not taking account of all interactions. We conclude by offering recommendations for planning, analysing and reporting economic evaluations based on factorial trials, taking increased analysis costs into account. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. PMID:28470760

Time-course, negative-stain electron microscopy-based analysis for investigating protein-protein interactions at the single-molecule level.

PubMed

Nogal, Bartek; Bowman, Charles A; Ward, Andrew B

2017-11-24

Several biophysical approaches are available to study protein-protein interactions. Most approaches are conducted in bulk solution, and are therefore limited to an average measurement of the ensemble of molecular interactions. Here, we show how single-particle EM can enrich our understanding of protein-protein interactions at the single-molecule level and potentially capture states that are unobservable with ensemble methods because they are below the limit of detection or not conducted on an appropriate time scale. Using the HIV-1 envelope glycoprotein (Env) and its interaction with receptor CD4-binding site neutralizing antibodies as a model system, we both corroborate ensemble kinetics-derived parameters and demonstrate how time-course EM can further dissect stoichiometric states of complexes that are not readily observable with other methods. Visualization of the kinetics and stoichiometry of Env-antibody complexes demonstrated the applicability of our approach to qualitatively and semi-quantitatively differentiate two highly similar neutralizing antibodies. Furthermore, implementation of machine-learning techniques for sorting class averages of these complexes into discrete subclasses of particles helped reduce human bias. Our data provide proof of concept that single-particle EM can be used to generate a "visual" kinetic profile that should be amenable to studying many other protein-protein interactions, is relatively simple and complementary to well-established biophysical approaches. Moreover, our method provides critical insights into broadly neutralizing antibody recognition of Env, which may inform vaccine immunogen design and immunotherapeutic development. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

On the use of sibling recurrence risks to select environmental factors liable to interact with genetic risk factors.

PubMed

Kazma, Rémi; Bonaïti-Pellié, Catherine; Norris, Jill M; Génin, Emmanuelle

2010-01-01

Gene-environment interactions are likely to be involved in the susceptibility to multifactorial diseases but are difficult to detect. Available methods usually concentrate on some particular genetic and environmental factors. In this paper, we propose a new method to determine whether a given exposure is susceptible to interact with unknown genetic factors. Rather than focusing on a specific genetic factor, the degree of familial aggregation is used as a surrogate for genetic factors. A test comparing the recurrence risks in sibs according to the exposure of indexes is proposed and its power is studied for varying values of model parameters. The Exposed versus Unexposed Recurrence Analysis (EURECA) is valuable for common diseases with moderate familial aggregation, only when the role of exposure has been clearly outlined. Interestingly, accounting for a sibling correlation for the exposure increases the power of EURECA. An application on a sample ascertained through one index affected with type 2 diabetes is presented where gene-environment interactions involving obesity and physical inactivity are investigated. Association of obesity with type 2 diabetes is clearly evidenced and a potential interaction involving this factor is suggested in Hispanics (P=0.045), whereas a clear gene-environment interaction is evidenced involving physical inactivity only in non-Hispanic whites (P=0.028). The proposed method might be of particular interest before genetic studies to help determine the environmental risk factors that will need to be accounted for to increase the power to detect genetic risk factors and to select the most appropriate samples to genotype.

NIRS-Based Hyperscanning Reveals Inter-brain Neural Synchronization during Cooperative Jenga Game with Face-to-Face Communication.

PubMed

Liu, Ning; Mok, Charis; Witt, Emily E; Pradhan, Anjali H; Chen, Jingyuan E; Reiss, Allan L

2016-01-01

Functional near-infrared spectroscopy (fNIRS) is an increasingly popular technology for studying social cognition. In particular, fNIRS permits simultaneous measurement of hemodynamic activity in two or more individuals interacting in a naturalistic setting. Here, we used fNIRS hyperscanning to study social cognition and communication in human dyads engaged in cooperative and obstructive interaction while they played the game of Jenga™. Novel methods were developed to identify synchronized channels for each dyad and a structural node-based spatial registration approach was utilized for inter-dyad analyses. Strong inter-brain neural synchrony (INS) was observed in the posterior region of the right middle and superior frontal gyrus, in particular Brodmann area 8 (BA8), during cooperative and obstructive interaction. This synchrony was not observed during the parallel game play condition and the dialog section, suggesting that BA8 was involved in goal-oriented social interaction such as complex interactive movements and social decision-making. INS was also observed in the dorsomedial prefrontal cortex (dmPFC), in particular Brodmann 9, during cooperative interaction only. These additional findings suggest that BA9 may be particularly engaged when theory-of-mind (ToM) is required for cooperative social interaction. The new methods described here have the potential to significantly extend fNIRS applications to social cognitive research.

Medical biochemistry: Is it time to change the teaching style?

PubMed

Palocaren, Jeeji; Pillai, Lekha S; Celine, T M

2016-01-01

The Medical Council of India (MCI) recommendations on medical education suggest a shift from didactic lectures to more interactive lectures. This study assessed the effectiveness of different pedagogical methods in biochemistry and the perceptions of students and teachers about the shift from didactic to interactive lectures. An interventional crossover study was done with the topic divided into three biochemical modules and one clinical module. The students were divided into two batches, one of which was given didactic and the other, interactive lectures. They were assessed immediately after the lecture and four months later. Anonymous feedback was obtained to gauge the students' perceptions regarding the mode of teaching. The teachers' feedback on the use of both pedagogical styles was also obtained. There was no significant difference between the performance of the two groups in either examination in three of the modules. However, there was a statistically significant difference between the two groups' performance in the module that had clinical applications, with students from the interactive lecture group performing better. All students preferred interactive classes, irrespective of the topic taught. The teachers indicated that, although at the outset the interactive lectures were difficult to manage, both in terms of content and time, these drawbacks could be overcome with time and practice. Interactive lectures are an effective teaching method in biochemistry, especially in topics involving clinical application.

In Cell Footprinting Coupled with Mass Spectrometry for the Structural Analysis of Proteins in Live Cells.

PubMed

Espino, Jessica A; Mali, Vishaal S; Jones, Lisa M

2015-08-04

Protein footprinting coupled with mass spectrometry has become a widely used tool for the study of protein-protein and protein-ligand interactions and protein conformational change. These methods provide residue-level analysis on protein interaction sites and have been successful in studying proteins in vitro. The extension of these methods for in cell footprinting would open an avenue to study proteins that are not amenable for in vitro studies and would probe proteins in their native environment. Here we describe the application of an oxidative-based footprinting approach inside cells in which hydroxyl radicals are used to oxidatively modify proteins. Mass spectrometry is used to detect modification sites and to calculate modification levels. The method is probing biologically relevant proteins in live cells, and proteins in various cellular compartments can be oxdiatively modified. Several different amino acid residues are modified making the method a general labeling strategy for the study of a variety of proteins. Further, comparison of the extent of oxidative modification with solvent accessible surface area reveals the method successfully probes solvent accessibility. This marks the first time protein footprinting has been performed in live cells.

A Partial Least Square Approach for Modeling Gene-gene and Gene-environment Interactions When Multiple Markers Are Genotyped

PubMed Central

Wang, Tao; Ho, Gloria; Ye, Kenny; Strickler, Howard; Elston, Robert C.

2008-01-01

Genetic association studies achieve an unprecedented level of resolution in mapping disease genes by genotyping dense SNPs in a gene region. Meanwhile, these studies require new powerful statistical tools that can optimally handle a large amount of information provided by genotype data. A question that arises is how to model interactions between two genes. Simply modeling all possible interactions between the SNPs in two gene regions is not desirable because a greatly increased number of degrees of freedom can be involved in the test statistic. We introduce an approach to reduce the genotype dimension in modeling interactions. The genotype compression of this approach is built upon the information on both the trait and the cross-locus gametic disequilibrium between SNPs in two interacting genes, in such a way as to parsimoniously model the interactions without loss of useful information in the process of dimension reduction. As a result, it improves power to detect association in the presence of gene-gene interactions. This approach can be similarly applied for modeling gene-environment interactions. We compare this method with other approaches: the corresponding test without modeling any interaction, that based on a saturated interaction model, that based on principal component analysis, and that based on Tukey’s 1-df model. Our simulations suggest that this new approach has superior power to that of the other methods. In an application to endometrial cancer case-control data from the Women’s Health Initiative (WHI), this approach detected AKT1 and AKT2 as being significantly associated with endometrial cancer susceptibility by taking into account their interactions with BMI. PMID:18615621

A partial least-square approach for modeling gene-gene and gene-environment interactions when multiple markers are genotyped.

PubMed

Wang, Tao; Ho, Gloria; Ye, Kenny; Strickler, Howard; Elston, Robert C

2009-01-01

Genetic association studies achieve an unprecedented level of resolution in mapping disease genes by genotyping dense single nucleotype polymorphisms (SNPs) in a gene region. Meanwhile, these studies require new powerful statistical tools that can optimally handle a large amount of information provided by genotype data. A question that arises is how to model interactions between two genes. Simply modeling all possible interactions between the SNPs in two gene regions is not desirable because a greatly increased number of degrees of freedom can be involved in the test statistic. We introduce an approach to reduce the genotype dimension in modeling interactions. The genotype compression of this approach is built upon the information on both the trait and the cross-locus gametic disequilibrium between SNPs in two interacting genes, in such a way as to parsimoniously model the interactions without loss of useful information in the process of dimension reduction. As a result, it improves power to detect association in the presence of gene-gene interactions. This approach can be similarly applied for modeling gene-environment interactions. We compare this method with other approaches, the corresponding test without modeling any interaction, that based on a saturated interaction model, that based on principal component analysis, and that based on Tukey's one-degree-of-freedom model. Our simulations suggest that this new approach has superior power to that of the other methods. In an application to endometrial cancer case-control data from the Women's Health Initiative, this approach detected AKT1 and AKT2 as being significantly associated with endometrial cancer susceptibility by taking into account their interactions with body mass index.

Evaluating the Quality of the Interaction between Persons with Profound Intellectual and Multiple Disabilities and Direct Support Staff: A Preliminary Application of Three Observation Scales from Parent-Infant Research

ERIC Educational Resources Information Center

Hostyn, Ine; Petry, Katja; Lambrechts, Greet; Maes, Bea

2011-01-01

Background: Affective and reciprocal interactions with others are essential for persons with profound intellectual and multiple disabilities (PIMD), but it is a challenge to assess their quality. This study aimed to investigate the usefulness of instruments from parent-infant research to evaluate these interactions. Method: Eighteen videotaped…

Acoustics and dynamics of coaxial interacting vortex rings

NASA Technical Reports Server (NTRS)

Shariff, Karim; Leonard, Anthony; Zabusky, Norman J.; Ferziger, Joel H.

1988-01-01

Using a contour dynamics method for inviscid axisymmetric flow we examine the effects of core deformation on the dynamics and acoustic signatures of coaxial interacting vortex rings. Both 'passage' and 'collision' (head-on) interactions are studied for initially identical vortices. Good correspondence with experiments is obtained. A simple model which retains only the elliptic degree of freedom in the core shape is used to explain some of the calculated features.

Interactions of gaseous molecules with X-ray photons and photoelectrons in AP-XPS study of solid surface in gas phase.

PubMed

Tao, Franklin Feng; Nguyen, Luan

2018-04-18

Studies of the surface of a catalyst in the gas phase via photoelectron spectroscopy is an important approach to establish a correlation between the surface of a catalyst under reaction conditions or during catalysis and its corresponding catalytic performance. Unlike the well understood interactions between photoelectrons and the atomic layers of a surface in ultrahigh vacuum (UHV) and the well-developed method of quantitative analysis of a solid surface in UHV, a fundamental understanding of the interactions between X-ray photons and gaseous molecules and between photoelectrons and molecules of the gas phase in ambient pressure X-ray photoelectron spectroscopy (AP-XPS) is lacking. Through well designed experiments, here the impact of the interactions between photoelectrons and gaseous molecules and interactions between X-ray photons and gaseous molecules on the intensity of the collected photoelectrons have been explored. How the changes in photoelectron intensity resulting from these interactions influence measurement of the authentic atomic ratio of element M to A of a solid surface has been discussed herein, and methods to correct the measured nominal atomic ratio of two elements of a solid surface upon travelling through a gas phase to its authentic atomic ratio have been developed.

How to Develop Electrochemistry SETS-Based Interactive E-Book?

NASA Astrophysics Data System (ADS)

Munawwarah, M.; Anwar, S.; Sunarya, Y.

2017-09-01

This study aims to develop SETS-based interactive e-book teaching material through 4S TMD methode. The research methode in this study is the Development Research (RD) Richey and Klein that consists of design, phase, and evaluation. The design step was to analyze and plan the types of teaching materials instructional developed. There are 12 indicators from 3 standard competences that produced in selection step based new curriculum, the compatibility subject matter and indicators, and the relations between value and subject matter. Structuring steps yield concept map, macro structure, and multiple representation that were arranged to be first draft of teaching material that was used for develop the instruments for characterization step. Chatacterization test have been done to students in 12nd grades with 68 texts. Characterization results indicated that there were some texts included to difficult text. Difficult texts have been reduced with the ways back to qualitative steps and particulation. The second draft of teaching material was arranged based the results of didactic reduction of difficult texts. This draft was used for arranged interactive e-book. The characteristics of this SETS-based interactive e-book that developed were mention about the connection between science with environment, technology, and society. This interactive e-book consists of animation, task, and quizes that taken the interaction of students directly.

Ensemble Architecture for Prediction of Enzyme-ligand Binding Residues Using Evolutionary Information.

PubMed

Pai, Priyadarshini P; Dattatreya, Rohit Kadam; Mondal, Sukanta

2017-11-01

Enzyme interactions with ligands are crucial for various biochemical reactions governing life. Over many years attempts to identify these residues for biotechnological manipulations have been made using experimental and computational techniques. The computational approaches have gathered impetus with the accruing availability of sequence and structure information, broadly classified into template-based and de novo methods. One of the predominant de novo methods using sequence information involves application of biological properties for supervised machine learning. Here, we propose a support vector machines-based ensemble for prediction of protein-ligand interacting residues using one of the most important discriminative contributing properties in the interacting residue neighbourhood, i. e., evolutionary information in the form of position-specific- scoring matrix (PSSM). The study has been performed on a non-redundant dataset comprising of 9269 interacting and 91773 non-interacting residues for prediction model generation and further evaluation. Of the various PSSM-based models explored, the proposed method named ROBBY (pRediction Of Biologically relevant small molecule Binding residues on enzYmes) shows an accuracy of 84.0 %, Matthews Correlation Coefficient of 0.343 and F-measure of 39.0 % on 78 test enzymes. Further, scope of adding domain knowledge such as pocket information has also been investigated; results showed significant enhancement in method precision. Findings are hoped to boost the reliability of small-molecule ligand interaction prediction for enzyme applications and drug design. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Gene-Environment Interactions in Cardiovascular Disease

PubMed Central

Flowers, Elena; Froelicher, Erika Sivarajan; Aouizerat, Bradley E.

2011-01-01

Background Historically, models to describe disease were exclusively nature-based or nurture-based. Current theoretical models for complex conditions such as cardiovascular disease acknowledge the importance of both biologic and non-biologic contributors to disease. A critical feature is the occurrence of interactions between numerous risk factors for disease. The interaction between genetic (i.e. biologic, nature) and environmental (i.e. non-biologic, nurture) causes of disease is an important mechanism for understanding both the etiology and public health impact of cardiovascular disease. Objectives The purpose of this paper is to describe theoretical underpinnings of gene-environment interactions, models of interaction, methods for studying gene-environment interactions, and the related concept of interactions between epigenetic mechanisms and the environment. Discussion Advances in methods for measurement of genetic predictors of disease have enabled an increasingly comprehensive understanding of the causes of disease. In order to fully describe the effects of genetic predictors of disease, it is necessary to place genetic predictors within the context of known environmental risk factors. The additive or multiplicative effect of the interaction between genetic and environmental risk factors is often greater than the contribution of either risk factor alone. PMID:21684212

Characterizing Topology of Probabilistic Biological Networks.

PubMed

Todor, Andrei; Dobra, Alin; Kahveci, Tamer

2013-09-06

Biological interactions are often uncertain events, that may or may not take place with some probability. Existing studies analyze the degree distribution of biological networks by assuming that all the given interactions take place under all circumstances. This strong and often incorrect assumption can lead to misleading results. Here, we address this problem and develop a sound mathematical basis to characterize networks in the presence of uncertain interactions. We develop a method that accurately describes the degree distribution of such networks. We also extend our method to accurately compute the joint degree distributions of node pairs connected by edges. The number of possible network topologies grows exponentially with the number of uncertain interactions. However, the mathematical model we develop allows us to compute these degree distributions in polynomial time in the number of interactions. It also helps us find an adequate mathematical model using maximum likelihood estimation. Our results demonstrate that power law and log-normal models best describe degree distributions for probabilistic networks. The inverse correlation of degrees of neighboring nodes shows that, in probabilistic networks, nodes with large number of interactions prefer to interact with those with small number of interactions more frequently than expected.

Perception of medical undergraduate students about interactive lectures in an outcome-based integrated curriculum: A cross-sectional study

PubMed Central

Asad, Mohammad Rehan; Amir, Khwaja; Tadvi, Naser Ashraf; Afzal, Kamran; Sami, Waqas; Irfan, Abdul

2017-01-01

OBJECTIVE: The objective of this study is to explore the student's perspectives toward the interactive lectures as a teaching and learning method in an integrated curriculum. MATERIALS AND METHODS: This cross-sectional study was conducted among 1st, 2nd and 3rd year male medical students (n = 121). A self-administered questionnaire based on the Visual, Auditory, Reader, Kinesthetic learning styles, learning theories, and role of feedback in teaching and learning on five-point Likert rating scale was used. The questionnaire was constructed after extensive literature review. RESULTS: There was an 80% response rate in this study. The total number of undergraduate medical students responded in the study were n = 97, 34 students of 1st year, n = 30 students of 2nd year and n = 33 student were in 3rd year, the mean scores of the student responses were calculated using Independent samples Kruskal–Wallis. There was no significant difference in the responses of the students of different years except for the question “The Interactive lectures facilitate effective use of learning resources.” Which showed significant difference in the responses of the 3 years students by Independent samples Kruskal–Wallis test. No significant association was found between the year of study and items of the questionnaire except for the same item, “ The Interactive lectures facilitates effective use of learning resources” by Spearman rank correlation test. CONCLUSION: The students perceive interactive lecture as an effective tool for facilitating visual and auditory learning modes, and for achieving curricular strategies. The student find the feedback given during the interactive lectures is effective in modifying learning attitude and enhancing motivation toward learning. PMID:29296601

Statistical results on restorative dentistry experiments: effect of the interaction between main variables

PubMed Central

CAVALCANTI, Andrea Nóbrega; MARCHI, Giselle Maria; AMBROSANO, Gláucia Maria Bovi

2010-01-01

Statistical analysis interpretation is a critical field in scientific research. When there is more than one main variable being studied in a research, the effect of the interaction between those variables is fundamental on experiments discussion. However, some doubts can occur when the p-value of the interaction is greater than the significance level. Objective To determine the most adequate interpretation for factorial experiments with p-values of the interaction nearly higher than the significance level. Materials and methods The p-values of the interactions found in two restorative dentistry experiments (0.053 and 0.068) were interpreted in two distinct ways: considering the interaction as not significant and as significant. Results Different findings were observed between the two analyses, and studies results became more coherent when the significant interaction was used. Conclusion The p-value of the interaction between main variables must be analyzed with caution because it can change the outcomes of research studies. Researchers are strongly advised to interpret carefully the results of their statistical analysis in order to discuss the findings of their experiments properly. PMID:20857003

Inferring Mechanisms of Compensation from E-MAP and SGA Data Using Local Search Algorithms for Max Cut

PubMed Central

Leiserson, Mark D.M.; Tatar, Diana; Cowen, Lenore J.

2011-01-01

Abstract A new method based on a mathematically natural local search framework for max cut is developed to uncover functionally coherent module and BPM motifs in high-throughput genetic interaction data. Unlike previous methods, which also consider physical protein-protein interaction data, our method utilizes genetic interaction data only; this becomes increasingly important as high-throughput genetic interaction data is becoming available in settings where less is known about physical interaction data. We compare modules and BPMs obtained to previous methods and across different datasets. Despite needing no physical interaction information, the BPMs produced by our method are competitive with previous methods. Biological findings include a suggested global role for the prefoldin complex and a SWR subcomplex in pathway buffering in the budding yeast interactome. PMID:21882903

Highly accurate prediction of protein self-interactions by incorporating the average block and PSSM information into the general PseAAC.

PubMed

Zhai, Jing-Xuan; Cao, Tian-Jie; An, Ji-Yong; Bian, Yong-Tao

2017-11-07

It is a challenging task for fundamental research whether proteins can interact with their partners. Protein self-interaction (SIP) is a special case of PPIs, which plays a key role in the regulation of cellular functions. Due to the limitations of experimental self-interaction identification, it is very important to develop an effective biological tool for predicting SIPs based on protein sequences. In the study, we developed a novel computational method called RVM-AB that combines the Relevance Vector Machine (RVM) model and Average Blocks (AB) for detecting SIPs from protein sequences. Firstly, Average Blocks (AB) feature extraction method is employed to represent protein sequences on a Position Specific Scoring Matrix (PSSM). Secondly, Principal Component Analysis (PCA) method is used to reduce the dimension of AB vector for reducing the influence of noise. Then, by employing the Relevance Vector Machine (RVM) algorithm, the performance of RVM-AB is assessed and compared with the state-of-the-art support vector machine (SVM) classifier and other exiting methods on yeast and human datasets respectively. Using the fivefold test experiment, RVM-AB model achieved very high accuracies of 93.01% and 97.72% on yeast and human datasets respectively, which are significantly better than the method based on SVM classifier and other previous methods. The experimental results proved that the RVM-AB prediction model is efficient and robust. It can be an automatic decision support tool for detecting SIPs. For facilitating extensive studies for future proteomics research, the RVMAB server is freely available for academic use at http://219.219.62.123:8888/SIP_AB. Copyright © 2017 Elsevier Ltd. All rights reserved.

Detection of Protein Interactions in T3S Systems Using Yeast Two-Hybrid Analysis.

PubMed

Nilles, Matthew L

2017-01-01

Two-hybrid systems, sometimes termed interaction traps, are genetic systems designed to find and analyze interactions between proteins. The most common systems are yeast based (commonly Saccharomyces cerevisae) and rely on the functional reconstitution of the GAL4 transcriptional activator. Reporter genes, such as the lacZ gene of Escherichia coli (encodes β-galactosidase), are placed under GAL4-dependent transcriptional control to provide quick and reliable detection of protein interactions. In this method the use of a yeast-based two-hybrid system is described to study protein interactions between components of type III secretion systems.

Content-Related Interactions and Methods of Reasoning within Self-Initiated Organic Chemistry Study Groups

ERIC Educational Resources Information Center

Christian, Karen Jeanne

2011-01-01

Students often use study groups to prepare for class or exams; yet to date, we know very little about how these groups actually function. This study looked at the ways in which undergraduate organic chemistry students prepared for exams through self-initiated study groups. We sought to characterize the methods of social regulation, levels of…

The Effectiveness of Teacher Interaction on Televised Instruction Designed to Supplement a Reading Program for Second-Graders.

ERIC Educational Resources Information Center

Ienatsch, Grant Peter

The purpose of this study was to determine the effect that various methods of using television have on instruction in reading for second graders. A specific part of the study was to explore whether teacher interaction is an important consideration in the use of the educational television program, "The Electric Company." A sample of 156…

Does Parent-Child Interaction Therapy Reduce Future Physical Abuse? A Meta-Analysis

ERIC Educational Resources Information Center

Kennedy, Stephanie C.; Kim, Johnny S.; Tripodi, Stephen J.; Brown, Samantha M.; Gowdy, Grace

2016-01-01

Objective: To use meta-analytic techniques to evaluating the effectiveness of parent-child interaction therapy (PCIT) at reducing future physical abuse among physically abusive families. Methods: A systematic search identified six eligible studies. Outcomes of interest were physical abuse recurrence, child abuse potential, and parenting stress.…

The Dynamics of Social Interaction in Telecollaborative Tandem Exchanges

ERIC Educational Resources Information Center

Janssen Sanchez, Brianna

2015-01-01

Using both quantitative and qualitative methods of inquiry, this dissertation study undertakes an exploration of the dynamics of the social interaction in discourse co-constructed by pairs of college students in telecollaborative tandem exchanges. Two groups of participants, Mexican learners of English as a foreign language and American learners…

Educational Technology Research Journals: "Interactive Learning Environments," 2004-2013

ERIC Educational Resources Information Center

Christensen, Steven S.; Andrews, Carolyn; Harris, Scott P.; Lloyd, Adam; Turley, Chad; West, Richard E.

2015-01-01

This study examined the journal "Interactive Learning Environments" to discover trends from 2004-2013. The authors looked at trends in article topics, research methods, authorship, citations, keyword frequencies, phrase counts of article abstracts, and article citations according to Google Scholar. Evidence is provided of the journal's…

Developing & Using Interaction Geography in a Museum

ERIC Educational Resources Information Center

Shapiro, Ben Rydal; Hall, Rogers P.; Owens, David A.

2017-01-01

There are many approaches that support studies of learning in relation to the physical environment, people's interaction with one another, or people's movement. However, what these approaches achieve in granularity of description, they tend to lose in synthesis and integration, and to date, there are not effective methods and concepts to study…

The Interaction of Lexical Characteristics and Speech Production in Parkinson's Disease

ERIC Educational Resources Information Center

Chiu, Yi-Fang; Forrest, Karen

2017-01-01

Purpose: This study sought to investigate the interaction of speech movement execution with higher order lexical parameters. The authors examined how lexical characteristics affect speech output in individuals with Parkinson's disease (PD) and healthy control (HC) speakers. Method: Twenty speakers with PD and 12 healthy speakers read sentences…