Specific Type Of Interaction Research Articles

Learning Representation of Molecules in Association Network for Predicting Intermolecular Associations.

A key aim of post-genomic biomedical research is to systematically understand molecules and their interactions in human cells. Multiple biomolecules coordinate to sustain life activities, and interactions between various biomolecules are interconnected. However, existing studies usually only focusing on associations between two or very limited types of molecules. In this study, we propose a network representation learning based computational framework MAN-SDNE to predict any intermolecular associations. More specifically, we constructed a large-scale molecular association network of multiple biomolecules in human by integrating associations among long non-coding RNA, microRNA, protein, drug, and disease, containing 6,528 molecular nodes, 9 kind of,105,546 associations. And then, the feature of each node is represented by its network proximity and attribute features. Furthermore, these features are used to train Random Forest classifier to predict intermolecular associations. MAN-SDNE achieves a remarkable performance with an AUC of 0.9552 and an AUPR of 0.9338 under five-fold cross-validation. To indicate the ability to predict specific types of interactions, a case study for predicting lncRNA-protein interactions using MAN-SDNE is also executed. Experimental results demonstrate this work offers a systematic insight for understanding the synergistic associations between molecules and complex diseases and provides a network-based computational tool to systematically explore intermolecular interactions.

Discovering key interactions. How student interactions relate to progress in mathematical generalization

This article presents a study of 8th grade students working in groups to solve a task about generalizing patterns. The study aimed to openly explore how progress in mathematical thinking might relate to the discourse. To do this, we first studied both separately. The progress in mathematical thinking was studied by inspecting how the groups progressed through different levels of generalization. The discourse was studied by characterizing each student interaction. When combining these, we realized that some specific types of interactions were related to students progressing to a higher level of generalization. We call these key interactions, and they were mainly of the types of advocating, locating, and reformulating. These seem clearly important for identifying evidence of progress during the discourses, but might also be helpful for understanding how specific types of interactions relates to sharing and growing mathematical thinking.

Supramolecular insight into the substitution of sulfur by selenium, based on crystal structures, quantum-chemical calculations and biosystem recognition.

Statistical analysis of data from crystal structures extracted from the Cambridge Structural Database (CSD) has shown that S and Se atoms display a similar tendency towards specific types of interaction if they are part of a fragment that corresponds to the side chains of cysteine (Cys), methionine (Met) selenocysteine (Sec) and selenomethionine (Mse). The most numerous are structures with C-H...Se and C-H...S interactions (∼80%), notably less numerous are structures with Se...Se and S...S interactions (∼5%), and Se...π and S...π interactions are the least numerous. The results of quantum-chemical calculations have indicated that C-H...Se (∼-0.8 kcal mol-1) and C-H...S interactions are weaker than the most stable parallel interaction (∼-3.3 kcal mol-1) and electrostatic interactions of σ/π type (∼-2.6 kcal mol-1). Their significant presence can be explained by the abundance of CH groups compared with the numbers of Se and S atoms in the crystal structures, and also by the influence of substituents bonded to the Se or S atom that further reduce their possibilities for interacting with species from the environment. This can also offer an explanation as to why O-H...Se (∼-4.4 kcal mol-1) and N-H...Se interactions (∼-2.2 kcal mol-1) are less numerous. Docking studies revealed that S and Se rarely participate in interactions with the amino acid residues of target enzymes, mostly because those residues preferentially interact with the substituents bonded to Se and S. The differences between Se and S ligands in the number and positions of their binding sites are more pronounced if the substituents are polar and if there are more Se/S atoms in the ligand.

Політична еліта в інституційному середовищі.

This paper is a study of the subject-matter and features of the institutionalization of the elite in the process of modernization of the political system. It is proved that the functioning of the institutional environment takes place at the macro and micro levels. In this context, the article studies the degree of coherence of the institutional environment and its dependence on the consent of all the subjects to respect the rules and norms that ensure social and political order. The study reveals a set of legitimate rules of interaction and competitive political practices that form the basis of the institutional environment (functioning of the elite). It describes the communication processes that form such interactions in the institutional environment.It is concluded that clear rules and procedures of lobbying allow balancing the interests of public groups and political elites on the basis of compromise solutions. Accordingly, lobbying ensures a pluralism of legitimate opportunities for public participation in the development and adoption of political decisions, provides publicity to the process and activities of state authorities. Authors grounded that a set of legitimate rules of interaction and competitive political practices form the basis of the institutional environment of elite functioning. A holistic understanding of the rules of interaction and practices helps to determine the procedure of the elite institution in the political modernization processes, the dynamism of which is provided by the optimal choice of political technologies. Also, communication processes shape specific types of interaction in the institutional environment, facilitating feedback, optimal distribution of resources, and the use of political system capabilities to optimize modernization changes. The elite institute, forming and controlling communication processes, ensures the involvement of public initiative in the practical implementation of modernization projects on the basis of partnership and mutual responsibility.

Geoarchaeological insights into the location of Indus settlements on the plains of northwest India

AbstractThis article presents a geomorphological and micromorphological study of the locational context of four Indus civilisation archaeological sites—Alamgirpur, Masudpur I and VII, and Burj—all situated on the Sutlej-Yamuna interfluve in northwest India. The analysis indicates a strong correlation between settlement foundation and particular landscape positions on an extensive alluvial floodplain. Each of the analysed sites was located on sandy levees and/or riverbank deposits associated with former channels. These landscape positions would have situated settlements above the level of seasonal floodwater resulting from the Indian summer monsoon. In addition, the sandy soils on the margins of these elevated landscape positions would have been seasonally replenished with water, silt, clay, and fine organic matter, considerably enhancing their capacity for water retention and fertility and making them particularly suitable for agriculture. These former landscapes are obscured by recent modification and extensive agricultural practices. These geoarchaeological evaluations indicate that there is a hidden landscape context for each Indus settlement. This specific type of interaction between humans and their local context is an important aspect of Indus cultural adaptations to diverse, variable, and changing environments.

Aqueous on/off fluorescent switches based on systems of quinoline / quinoline-macrocycle

The changes in the spectrophotometric and the spectrofluorimetric properties of Quinoline (QUI) by the addition of water soluble macrocycles with different characteristics such as cyclodextrins (CD; α, β, hydroxypropyl-β, methyl-β and γ) and sulfonate calixarenes (SCAn, n = 6 and 8) were analyzed at acidic and neutral pH at 25.0 °C. Spectral changes were observed for the basic form of QUI. Small decreases of absorbance were indicative of interactions between QUI and the macrocycles. The association constants were determined in the cases of QUI-βCD and QUI-γCD. In all cases, the fluorescence of QUI was quenched in the presence of the macrocycles. The values of the Stern-Volmer constants (KQ/M−1) were (54.030 ± 0.001) and (57.050 ± 0.001) for βCD and γCD and (3.8 ± 0.1) x 104 and (2.40 ± 0.06) x 104 for SCA6 and SCA8. These values were interpreted as the association constants (KA) of the non fluorescent complexes formed in the ground state since the fluorescence quenching was evaluated as static. The unusual quenching of fluorescence produced by the CD macrocycles and the high differences in the values of the KA for CD and SCA were interpreted by the different types of specific interactions operating in the systems studied acting as switches on/off.

A new model isolates glioblastoma clonal interactions and reveals unexpected modes for regulating motility, proliferation, and drug resistance

Tumor clonal heterogeneity drives treatment resistance. But robust models are lacking that permit eavesdropping on the basic interaction network of tumor clones. We developed an in vitro, functional model of clonal cooperation using U87MG glioblastoma cells, which isolates fundamental clonal interactions. In this model pre-labeled clones are co-cultured to track changes in their individual motility, growth, and drug resistance behavior while mixed. This highly reproducible system allowed us to address a new class of fundamental questions about clonal interactions. We demonstrate that (i) a single clone can switch off the motility of the entire multiclonal U87MG cell line in 3D culture, (ii) maintenance of clonal heterogeneity is an intrinsic and influential cancer cell property, where clones coordinate growth rates to protect slow growing clones, and (iii) two drug sensitive clones can develop resistance de novo when cooperating. Furthermore, clonal communication for these specific types of interaction did not require diffusible factors, but appears to depend on cell-cell contact. This model constitutes a straightforward but highly reliable tool for isolating the complex clonal interactions that make up the fundamental “hive mind” of the tumor. It uniquely exposes clonal interactions for future pharmacological and biochemical studies.

Cyanopropyl-Cation Ionic Liquids as High Polar Stationary Phases for Capillary Gas Chromatography

The present work was devoted to the investigation of highly polar capillary columns with stationary phases based on ionic liquids (IL) with cyanopropyl-containing cations. Five imidazole and quinolinium cyanopropyl-containing ILs have been studied. Their high polarity has been demonstrated. The measured Abraham selectivity has demonstrated an increase in specific types of interaction comparing to noncyanopropyl analogs. High thermal stability up to 300°C has been shown, especially for dicationic ILs. Examples of separation for one-dimensional and two-dimensional gas chromatography have been shown.

Calculating the Gibbs Energies of Solvation of 2,2'-Dipyridyl in Nonaqueous Solvents

The Gibbs energies of solvation of 2,2'-dipyridyl (2,2'-Dipy) in methanol (MeOH), acetonitrile (AN), dimethylsulfoxide (DMSO), and N,N-dimethylformamide (DMF) are calculated via quantum chemical modeling. Estimates are made for the contributions from universal and specific types of interaction between the molecules of 2,2'-Dipy and the solvent to the change in the Gibbs energies of solvation of the amine when MeOH is replaced with AN, DMSO, and DMF.

A multidimensional perspective on microbial interactions.

ABSTRACTBeyond being simply positive or negative, beneficial or inhibitory, microbial interactions can involve a diverse set of mechanisms, dependencies and dynamical properties. These more nuanced features have been described in great detail for some specific types of interactions, (e.g. pairwise metabolic cross-feeding, quorum sensing or antibiotic killing), often with the use of quantitative measurements and insight derived from modeling. With a growing understanding of the composition and dynamics of complex microbial communities for human health and other applications, we face the challenge of integrating information about these different interactions into comprehensive quantitative frameworks. Here, we review the literature on a wide set of microbial interactions, and explore the potential value of a formal categorization based on multidimensional vectors of attributes. We propose that such an encoding can facilitate systematic, direct comparisons of interaction mechanisms and dependencies, and we discuss the relevance of an atlas of interactions for future modeling and rational design efforts.

3-Mercaptopropionic, 4-Mercaptobenzoic, and Oleic Acid-Capped CdSe Quantum Dots: Interparticle Distance, Anchoring Groups, and Surface Passivation

The optoelectronic properties of quantum dots are strongly controlled by the chemical nature of their surface-passivating ligands. In this work, we present the synthesis, characterization, and surface modification of CdSe quantum dots (QDs) and their application in solar cells. CdSe QDs were capped in oleic acid (OA), 3-mercaptopropionic acid (MPA), and 4-mercaptobenzoic acid (MBA). The QDs were characterized by transmission electron microscopy (TEM), UV-Vis absorption and emission spectrophotometry, thermogravimetric analyses, and 1H and 13C NMR. From TEM analysis, it has been observed that interparticle distance can be effectively controlled by the presence of different molecular size ligands. From the 1H and 13C NMR, specific types of interactions between the Cd2+ and the ligands have been observed. Although CdSe/OA presented larger interparticle distance as compared to CdSe/MPA and CdSe/MBA, the photocatalytic oxidation of the thiol groups on the surface of the MPA- and MBA-based quantum dots resulted in poor surface stabilization, ultimately resulting in poor power conversion efficiencies which were ca. 70% smaller than that of OA-based solar cell.

Study of contributions of diffractive processes to forward neutral particle production with the ATLAS-LHCf detector

LHCf is an experiment dedicated to verify the hadronic interaction models by measuring the forward neutral particle production at the LHC. Corresponding data are very important for understanding hadronic interactions occurring in air-shower development. According to the current LHCf results, no simulation model predicts the LHCf data perfectly. In order to provide more specific data, it is necessary to classify the LHCf observables into specific interaction types: diffraction or non-diffraction. Combining the information of ATLAS, LHCf is able to classify these specific interaction types experimentally. Especially, the ATLAS-LHCf joint experiment will have the unique sensitivity to low mass diffraction. LHCf and ATLAS have succeeded in the common data-taking in p-p collisions at √s = 13 TeV. We will report the first ATLAS-LHCf joint analysis result and discuss the impact of the corresponding joint analysis result to the determination of mass composition of ultra-high energy cosmic-rays.

Утицај климатских промена на политичке немире и сукобе у Африци: студија случаја Етиопијe

Security challenges, risks, and threats, beyond traditional forms, have become so complex that understanding them is a way of identifying specific types of interaction that threaten security. Climate change and global warming can have serious consequences for human health, social and economic development. Intensifying climate change can increase the risk of political unrest and conflict in countries whose economic and social development is conditioned by free access to natural resources. The cause of conflict is never easy to determine because it is a set of different factors that interact with one another. A brief overview of conflicts in Africa with a particular focus on conflicts in Ethiopia and the region is presented. Th is paper reports on the complexity and interdependence of climate change and its consequences on political decisions, social unrest, forced migration and civil and international conflicts.

A Platform of Phenol-Based Nitroxide Radicals as an "EPR Toolbox" in Supramolecular and Click Chemistry.

A large number (63) of well-defined nitroxide radicals, all phenol-based TEMPO and PROXYL esters, were synthesized using different strategies based on well-established Steglich esterifications. All of these radicals can be used as spin probes (SPs) and spin labels (SLs) for electron paramagnetic resonance (EPR) spectroscopy of supramolecular systems. Depending on the nature of the functional group(s) on each SP/SL, the synthesized nitroxide radicals serve as polyphilic molecular "toolbox" for the EPR-spectroscopic detection and characterization of specific types of interactions, e. g. π-π interactions, sulfur-sulfur interactions, hydrogen bonding, electrostatic and dipole-dipole interactions, and van der Waals and hydrophobic interactions, in the presence of the selected supramolecular systems of interest (e. g. proteins, peptides). For each synthesized SP/SL the water solubility was gravimetrically determined for use in aqueous solution at pH 7.

Solvation of Piperidine in Nonaqueous Solvents

The enthalpies of solvation of piperidine (Ppd) in methanol (MeOH), ethanol (EtOH), N,N‑dimethylformamide (DMF), and dimethylsulfoxide (DMSO) are calculated by means of quantum-chemical modeling. The enthalpies of solvation of Ppd in EtOH and DMF are determined calorimetrically. The energies of Ppd solvation in aprotic solvents is found to be generally governed by universal types of interactions between amine and solvent molecules. The energy contributions from both universal and specific types of interactions to the overall enthalpy of Ppd solvation are determined in amphoteric MeOH and EtOH.

Instrument constituencies and public policy-making: an introduction

For many years, policy-making has been envisioned as a process in which subsets of policy actors engage in specific types of interactions involved in the definition of policy problems, the articulation of solutions and their matching or enactment. This activity involves the definition of policy goals (both broad and specific), the creation or identification of the means and mechanisms that need to be implemented to realize these goals, and the set of bureaucratic, partisan, electoral and other political struggles involved in their acceptance and transformation into action. While past research on policy subsystems has often assumed or implied that these tasks could be undertaken by any actor, more recent research argues that distinct sets of actors are involved in these three tasks: epistemic communities that are engaged in discussions about policy dilemmas and problems; instrument constituencies that define and promote policy instruments and alternatives; and advocacy coalitions which compete to have their choice of policy alternative and problem frames adopted. Two of these three sets of actors are quite well known and, indeed, have their own literature about what it takes to be a member of an epistemic community or advocacy coalition, although interactions between the two are rarely discussed. The third subset, the instrument constituency, is much less known but has from the outset been considered in relation to these other policy actors. The articles in this special issue focus on better understanding the nature of actor interactions undertaken by instrument constituencies and how these relate to the other kinds of actors involved in policy-making.

Cultural entrainment of motor skill development: Learning to write hiragana in Japanese primary school.

The aim of the present study was to examine how the social norms shared in a classroom environment influence the development of movement dynamics of handwriting of children who participate in the environment. To look into this issue, the following aspects of the entire period of classroom learning of hiragana letters in Japanese 1st graders who had just entered primary school were studied: First, the structure of classroom events and the specific types of interaction and learning within such environment were described. Second, in the experiment involving 6‐year‐old children who participated in the class, writing movements of children and their changes over the period of hiragana education were analyzed for each stroke composing letters. It was found that writing movement of children became differentiated in a manner specific to the different types of stroke endings, to which children were systematically encouraged to attend in the classroom. The results provide a detailed description of the process of how dynamics of fine motor movement of children is modulated by the social norms of a populated, classroom environment in a non‐Latin alphabet writing system.

Protease-Inhibitor Interaction Predictions: Lessons on the Complexity of Protein–Protein Interactions

Protein interactions shape proteome function and thus biology. Identification of protein interactions is a major goal in molecular biology, but biochemical methods, although improving, remain limited in coverage and accuracy. Whereas computational predictions can guide biochemical experiments, low validation rates of predictions remain a major limitation. Here, we investigated computational methods in the prediction of a specific type of interaction, the inhibitory interactions between proteases and their inhibitors. Proteases generate thousands of proteoforms that dynamically shape the functional state of proteomes. Despite the important regulatory role of proteases, knowledge of their inhibitors remains largely incomplete with the vast majority of proteases lacking an annotated inhibitor. To link inhibitors to their target proteases on a large scale, we applied computational methods to predict inhibitory interactions between proteases and their inhibitors based on complementary data, including coexpression, phylogenetic similarity, structural information, co-annotation, and colocalization, and also surveyed general protein interaction networks for potential inhibitory interactions. In testing nine predicted interactions biochemically, we validated the inhibition of kallikrein 5 by serpin B12. Despite the use of a wide array of complementary data, we found a high false positive rate of computational predictions in biochemical follow-up. Based on a protease-specific definition of true negatives derived from the biochemical classification of proteases and inhibitors, we analyzed prediction accuracy of individual features, thereby we identified feature-specific limitations, which also affected general protein interaction prediction methods. Interestingly, proteases were often not coexpressed with most of their functional inhibitors, contrary to what is commonly assumed and extrapolated predominantly from cell culture experiments. Predictions of inhibitory interactions were indeed more challenging than predictions of nonproteolytic and noninhibitory interactions. In summary, we describe a novel and well-defined but difficult protein interaction prediction task and thereby highlight limitations of computational interaction prediction methods.

Molecular Dynamics in Mixed Solvents Reveals Protein-Ligand Interactions, Improves Docking, and Allows Accurate Binding Free Energy Predictions.

One of the most important biological processes at the molecular level is the formation of protein-ligand complexes. Therefore, determining their structure and underlying key interactions is of paramount relevance and has direct applications in drug development. Because of its low cost relative to its experimental sibling, molecular dynamics (MD) simulations in the presence of different solvent probes mimicking specific types of interactions have been increasingly used to analyze protein binding sites and reveal protein-ligand interaction hot spots. However, a systematic comparison of different probes and their real predictive power from a quantitative and thermodynamic point of view is still missing. In the present work, we have performed MD simulations of 18 different proteins in pure water as well as water mixtures of ethanol, acetamide, acetonitrile and methylammonium acetate, leading to a total of 5.4 μs simulation time. For each system, we determined the corresponding solvent sites, defined as space regions adjacent to the protein surface where the probability of finding a probe atom is higher than that in the bulk solvent. Finally, we compared the identified solvent sites with 121 different protein-ligand complexes and used them to perform molecular docking and ligand binding free energy estimates. Our results show that combining solely water and ethanol sites allows sampling over 70% of all possible protein-ligand interactions, especially those that coincide with ligand-based pharmacophoric points. Most important, we also show how the solvent sites can be used to significantly improve ligand docking in terms of both accuracy and precision, and that accurate predictions of ligand binding free energies, along with relative ranking of ligand affinity, can be performed.

Ontology-based literature mining of E. coli vaccine-associated gene interaction networks

BackgroundPathogenic Escherichia coli infections cause various diseases in humans and many animal species. However, with extensive E. coli vaccine research, we are still unable to fully protect ourselves against E. coli infections. To more rational development of effective and safe E. coli vaccine, it is important to better understand E. coli vaccine-associated gene interaction networks.MethodsIn this study, we first extended the Vaccine Ontology (VO) to semantically represent various E. coli vaccines and genes used in the vaccine development. We also normalized E. coli gene names compiled from the annotations of various E. coli strains using a pan-genome-based annotation strategy. The Interaction Network Ontology (INO) includes a hierarchy of various interaction-related keywords useful for literature mining. Using VO, INO, and normalized E. coli gene names, we applied an ontology-based SciMiner literature mining strategy to mine all PubMed abstracts and retrieve E. coli vaccine-associated E. coli gene interactions. Four centrality metrics (i.e., degree, eigenvector, closeness, and betweenness) were calculated for identifying highly ranked genes and interaction types.ResultsUsing vaccine-related PubMed abstracts, our study identified 11,350 sentences that contain 88 unique INO interactions types and 1,781 unique E. coli genes. Each sentence contained at least one interaction type and two unique E. coli genes. An E. coli gene interaction network of genes and INO interaction types was created. From this big network, a sub-network consisting of 5 E. coli vaccine genes, including carA, carB, fimH, fepA, and vat, and 62 other E. coli genes, and 25 INO interaction types was identified. While many interaction types represent direct interactions between two indicated genes, our study has also shown that many of these retrieved interaction types are indirect in that the two genes participated in the specified interaction process in a required but indirect process. Our centrality analysis of these gene interaction networks identified top ranked E. coli genes and 6 INO interaction types (e.g., regulation and gene expression).ConclusionsVaccine-related E. coli gene-gene interaction network was constructed using ontology-based literature mining strategy, which identified important E. coli vaccine genes and their interactions with other genes through specific interaction types.