Specific Interaction Patterns Research Articles

Complex Network Analysis for Knowledge Management and Organizational Intelligence

The scope and focus of knowledge management has changed multiple times over the last decades, each shift revealing new challenges to management science. Recent change of perspective drawing from systems thinking is suggesting that knowledge is created through interaction between people. Complex network analysis is a rigorous method that can be used for evaluation of interaction patterns between employees. The literature suggests that specific interaction patterns are related to increased knowledge flow, innovativeness and performance. Aim of this paper is to provide an overview of various approaches utilizing the complex network analysis in organizations and present suggestions that might support managerial decision-making processes related to knowledge management and organizational intelligence.

Heaviness, space and journey – innovation opportunities and restrictions

PurposeThe purpose of this paper is to argue that if the authors want to understand the role of heaviness, space and journey in innovation, the authors have to start with the interaction itself, that is the exchange process taking place between economic actors. Three major aspects will be considered: the first is that heaviness, space and journey imply restrictions, the second is that these aspects can be positively utilised in innovation processes, and the third is their joint importance to contemporary policy. All innovation processes must bypass and build on existing investments in social and material resources, related across time and space.Design/methodology/approachThe theoretical foundation is a basic IMP observation: exchange has a content. Exchange is captured as an interaction process that creates specific imprints on material and social resources involved – across firm boundaries, and across time and space. The methodology is a consequence of the research question and the theoretical point of departure and is based on three earlier IMP studies, where heaviness has been measured in different ways. The authors utilize two earlier presented case studies to focus on the heaviness, space and journey dimensions.FindingsThree main aspects are discussed: the first aspect concerns the need for utilisation of others heaviness in order for the innovation to gain heaviness in itself. The second aspect concerns the consequences that the search for heaviness has for the creation of an innovation space. The third aspect concerns the innovation journey; the specific interaction patterns between significant actors as well as places hosting heavy using, producing and developing activities created through interactions over time.Research limitations/implicationsIn order to change or to establish a new economic exchange interface, there is an urgent need to be aware of and utilise heaviness, to find out in what way existing investments made in related interfaces can be taken advantage of. In order to do that, there is a need for a better understanding of the function of heaviness, spatial and journey aspects included.Practical implicationsIn contemporary policy, certain heaviness is recognised, however, only in a non-business developing setting. The first conclusion is that heaviness of established producing and using settings is a policy blind spot. This implies that analytical policy approaches are not equipped for recognitions or of estimations of heaviness, nor as a hindrance or as a possibility in producing and using settings. The second conclusion is that the policy definition of the role of place implies neglecting the innovation space. The third conclusion is that there is a need for policy to recognise the innovation journey and its consequences.Social implicationsIf the policy is expected to have regional effects, policy analysis has to start out from the established heaviness of the region and consider how it can be taken advantage of.Originality/valueThe paper draws attention to an aspect neglected in policy attempts to boost innovation, that the mobilising support has to come from actors representing heavy producing and using networks – and that these already have space and journey characteristics. A peripheral actor can come up with a suggestion for change – but it cannot alone mobilise the resources necessary for an innovation to get a space and journey in relation to established resource constellations.

Dynamic interneuron-principal cell interplay leads to a specific pattern of in vitro ictogenesis

Ictal discharges induced by 4-aminopyridine in the in vitro rodent entorhinal cortex present with either low-voltage fast or sudden onset patterns. The role of interneurons in initiating low-voltage fast onset ictal discharges is well established but the processes leading to sudden onset ictal discharges remain unclear. We analysed here the participation of interneurons (n = 75) and principal cells (n = 13) in the sudden onset pattern by employing in vitro tetrode wire recordings in the entorhinal cortex of brain slices from Sprague-Dawley rats. Ictal discharges emerged from a background of frequently occurring interictal spikes that were associated to a specific interneuron/principal cell interplay. High rates of interneuron firing occurred 12 ms before interictal spike onset while principal cells fired later during low interneuron firing. In contrast, the onset of sudden ictal discharges was characterized by increased firing from principal cells 627 ms before ictal onset whereas interneurons increased their firing rates 161 ms before ictal onset. Our data show that sudden onset ictogenesis is associated with frequently occurring interictal spikes resting on the interplay between interneurons and principal cells while ictal discharges stem from enhanced principal cell firing leading to increased interneuron activity. These findings indicate that specific patterns of interactions between interneurons and principal cells shape interictal and ictal discharges with sudden onset in the rodent entorhinal cortex. We propose that specific neuronal interactions lead to the generation of distinct onset patterns in focal epileptic disorders.

Examining the Impact of Maternal Individual Features on Children's Behavioral Problems in Adoptive Families: The Role of Maternal Temperament and Neurobiological Markers.

The first year after adoption constitutes a sensitive period for both strengthening the new emotional bond in the family and checking its appropriate development by adoption services. A key variable for children’s catch-up are adoptive parents’ socioemotional and individual features. The aim of this study is to investigate links between adoptive mothers’ individual features and behavioral problems in their children in the first year after adoption placement, by testing the moderating role of both age at adoption and maternal genetic polymorphisms. Seventy-eight adoptive mothers completed temperament and genetic measures. Mothers showed a specific pattern of interaction between basic temperament traits and genetic markers in their assessment of children’s behavioral problems; dopamine D4 receptor gene and children’s age at adoption are two moderators in the association in which mothers’ temperament was affecting the evaluation of their children’s behavioral problems. Findings highlight a still undervalued area of parenting resources in the process of post-institutionalized children’s catch-up after adoption placement, by showing how individual features count in the commonly measured variable of children’s behavioral and emotional problems. This could help in orienting identification and choice of key variables for family assessment after adoption placement, thus contributing in fostering children’s healthy development.

Using process mining to analyze students' quiz-taking behavior patterns in a learning management system

The aim of this paper is to explore students' behavior and interaction patterns in different types of online quiz-based activities within learning management systems (LMS). Analyzing students' behavior in online learning activities and detecting specific patterns of interaction in LMS is a topic of great interest for the educational data mining (EDM) and learning analytics (LA) research communities. Previous studies have focused primarily on frequency analysis without addressing the temporal aspects of students' learning behavior. Therefore, we apply a process-oriented approach, investigating perspectives on using process mining methods in the context of online learning and assessment. To explore a broad range of possible student behavior patterns, we analyze students' interactions in several online quizzes from different courses and with different settings. Using process mining methods, we identify specific types of interaction sequences that shed new light on students’ quiz-taking strategies in LMS. We believe that these findings bring important implications for researchers studying student behavior in online environments as well as practitioners using online quizzes for learning and assessment.

Scaffolding Young Children: The Utility of Mediation in a Classification Test

Introduction. Studies of Dynamic Assessment of cognitive abilities reveal that young children profit from assistance while carrying out tasks that elicit cognitive effort. Dynamic assessment refers to a test format of a pretest-mediation-posttest in which the mediation phase includes scaffolding to assist the child to grasp the purpose of the task. The aim of the study was to investigate how the mediation phase proceeds. The approach is based upon a Dynamic Systems Theory that explains that the interaction between tester/assessor and testee is based upon reciprocal processes that shape both tester and testee behavior in a highly individualized situational manner.Method. A micro-genetic methodology was applied to study the dynamics of scaffolding in the mediation phase. Transition matrices were developed in order to specify the nature and reciprocity of the dynamic system. The participants tested were four 4 year-old Dutch children attending preschool whose first language was Spanish. The test of Classification was offered. It requires from children to grasp the sorting of blocks in three categories: Color, form and size. The skill is one of the prerequisites of numeracy development.Results. The findings show how mediation by the assessor is reciprocally adapted between each child and the assessor, generating specific patterns of dyad interaction in order to achieve the task.Discussion and Conclusion. The scaffolding applied in the mediation phase of a Dynamic Assessment task generates significant improvements in the performance levels showed by the children in the posttest phase results. When the Dynamic System Theory is applied into the mediation phase it is possible to observe how the assessor adapts to the special necessities of the child and therefore is also modified. This fact suggests that scaffolding is a personalized process that moves along the semi-scripted mediation procedure and reveals that children not only differ with regard to their potential to learn but also differ in their ability to elicit scaffolding from the assessor.

Identifying Causes of Patterns in Ecological Networks: Opportunities and Limitations

Ecological networks depict the interactions between species, mainly based on observations in the field. The information contained in such interaction matrices depends on the sampling design, and typically, compounds preferences (specialization) and abundances (activity). Null models are the primary vehicles to disentangle the effects of specialization from those of sampling and abundance, but they ignore the feedback of network structure on abundances. Hence, network structure, as exemplified here by modularity, is difficult to link to specific causes. Indeed, various processes lead to modularity and to specific interaction patterns more generally. Inferring (co)evolutionary dynamics is even more challenging, as competition and trait matching yield identical patterns of interactions. A satisfactory resolution of the underlying factors determining network structure will require substantial additional information, not only on independently assessed abundances, but also on traits, and ideally on fitness consequences as measured in experimental setups.

Novel pyrrolocycloalkylpyrazole analogues as CB1 ligands.

Novel 1,4-dihydropyrazolo[3,4-a]pyrrolizine-, 4,5-dihydro-1H-pyrazolo[4,3-g]indolizine- and 1,4,5,6-tetrahydropyrazolo[3,4-c]pyrrolo[1,2-a]azepine-3-carboxamide-based compounds were designed and synthesized for cannabinoid CB1 and CB2 receptor interactions. Any of the new synthesized compounds showed high affinity for CB2 receptor with Ki values superior to 314nm, whereas some of them showed moderate affinity for CB1 receptor with Ki values inferior to 400nm. 7-Chloro-1-(2,4-dichlorophenyl)-N-(homopiperidin-1-yl)-4,5-dihydro-1H-pyrazolo[4,3-g]indolizine-3-carboxamide (2j) exhibited good affinity for CB1 receptor (Ki CB1 =81nm) and the highest CB2 /CB1 selectively ratio (>12). Docking studies carried out on such compounds were performed using the hCB1 X-ray in complex with the close pyrazole analogue AM6538 and disclosed specific pattern of interactions related to the tricyclic pyrrolopyrazole scaffolds as CB1 ligands.

A novel toolbox to investigate tissue spatial organization applied to the study of the islets of Langerhans

Thanks to the development of new 3D Imaging techniques, volumetric data of thick samples, especially tissues, are commonly available. Several algorithms were proposed to analyze cells or nuclei in tissues, however these tools are limited to two dimensions. Within any given tissue, cells are not likely to be organized randomly and as such have specific patterns of cell-cell interaction forming complex communication networks. In this paper, we propose a new set of tools as an approach to segment and analyze tissues in 3D with single cell resolution. This new tool box can identify and compute the geographical location of single cells and analyze the potential physical interactions between different cell types and in 3D. As a proof-of-principle, we applied our methodology to investigation of the cyto-architecture of the islets of Langerhans in mice and monkeys. The results obtained here are a significant improvement in current methodologies and provides new insight into the organization of alpha cells and their cellular interactions within the islet’s cellular framework.

Empathy-Related Responses to Depicted People in Art Works.

Existing theories of empathic response to visual art works postulate the primacy of automatic embodied reaction to images based on mirror neuron mechanisms. Arguing for a more inclusive concept of empathy-related response and integrating four distinct bodies of literature, we discuss contextual, and personal factors which modulate empathic response to depicted people. We then present an integrative model of empathy-related responses to depicted people in art works. The model assumes that a response to empathy-eliciting figural artworks engages the dynamic interaction of two mutually interlinked sets of processes: socio-affective/cognitive processing, related to the person perception, and esthetic processing, primarily concerned with esthetic appreciation and judgment and attention to non-social aspects of the image. The model predicts that the specific pattern of interaction between empathy-related and esthetic processing is co-determined by several sets of factors: (i) the viewer's individual characteristics, (ii) the context variables (which include various modes of priming by narratives and other images), (iii) multidimensional features of the image, and (iv) aspects of a viewer's response. Finally we propose that the model is implemented by the interaction of functionally connected brain networks involved in socio-cognitive and esthetic processing.

Determinants of BH3 Sequence Specificity for the Disruption of Bcl-xL/cBid Complexes in Membranes

The prosurvival Bcl-2 proteins exhibit a specific pattern of interactions with BH3-only proteins that determines the cellular dependence on apoptotic stress. This specificity is crucial for the development of BH3 mimetics, a class of anticancer molecules based on the BH3 domain with promising activity in clinical trials. Although complex formation mainly takes place in the mitochondrial outer membrane, most studies so far addressed the interaction between BH3 peptides and truncated Bcl-2 proteins in solution. As a consequence, quantitative understanding of the sequence specificity determinants of BH3 peptides in the membrane environment is missing. Here, we tackle this issue by systematically quantifying the ability of BH3 peptides to compete for the complexes between cBid and Bcl-xL in giant unilamellar vesicles and compare it with solution and mitochondria. We show that the BH3 peptides derived from Hrk, Bim, Bid, and Bad are the most efficient in disrupting cBid/Bcl-xL complexes in the membrane, which correlates with their activity in mitochondria. Our findings support the targeting to the membrane of small molecules that bind Bcl-2 proteins as a strategy to improve their efficiency.

Gut Microbial Diversity Assessment of Indian Type-2-Diabetics Reveals Alterations in Eubacteria, Archaea, and Eukaryotes.

Diabetes in India has distinct genetic, nutritional, developmental and socio-economic aspects; owing to the fact that changes in gut microbiota are associated with diabetes, we employed semiconductor-based sequencing to characterize gut microbiota of diabetic subjects from this region. We suggest consolidated dysbiosis of eubacterial, archaeal and eukaryotic components in the gut microbiota of newly diagnosed (New-DMs) and long-standing diabetic subjects (Known-DMs) compared to healthy subjects (NGTs). Increased abundance of phylum Firmicutes (p = 0.010) and Operational Taxonomic Units (OTUs) of Lactobacillus (p < 0.01) were observed in Known-DMs subjects along with the concomitant graded decrease in butyrate-producing bacterial families like Ruminococcaceae and Lachnospiraceae. Eukaryotes and fungi were the least affected components in these subjects but archaea, except Methanobrevibacter were significantly decreased in them. The two dominant archaea viz. Methanobrevibacater and Methanosphaera followed opposite trends in abundance from NGTs to Known-DMs subjects. There was a substantial reduction in eubacteria, with a noticeable decrease in Bacteroidetes phylum (p = 0.098) and an increased abundance of fungi in New-DMs subjects. Likewise, opportunistic fungal pathogens such as Aspergillus, Candida were found to be enriched in New-DMs subjects. Analysis of eubacterial interaction network revealed disease-state specific patterns of ecological interactions, suggesting the distinct behavior of individual components of eubacteria in response to the disease. PERMANOVA test indicated that the eubacterial component was associated with diabetes-related risk factors like high triglyceride (p = 0.05), low HDL (p = 0.03), and waist-to-hip ratio (p = 0.02). Metagenomic imputation of eubacteria depict deficiencies of various essential functions such as carbohydrate metabolism, amino acid metabolism etc. in New-DMs subjects. Results presented here shows that in diabetes, microbial dysbiosis may not be just limited to eubacteria. Due to the inter-linked metabolic interactions among the eubacteria, archaea and eukarya in the gut, it may extend into other two domains leading to trans-domain dysbiosis in microbiota. Our results thus contribute to and expand the identification of biomarkers in diabetes.

Binding affinity of pro-apoptotic BH3 peptides for the anti-apoptotic Mcl-1 and A1 proteins: Molecular dynamics simulations of Mcl-1 and A1 in complex with six different BH3 peptides

The anti-apoptotic members of Bcl-2 family of proteins bind to their pro-apoptotic counterparts to induce or prevent cell death.Based on the distinct binding profiles for specific pro-apoptotic BH3 peptides, the anti-apoptotic Bcl-2 proteins can be divided into at least two subclasses. The subclass that includes Bcl-XL binds strongly to Bad BH3 peptide while it has weak binding affinity for the second subclass of Bcl-2 proteins such as Mcl-1 and A1. Anti-apoptotic Bcl-2 proteins are considered to be attractive drug targets for anti-cancer drugs. BH3-mimetic inhibitors such as ABT-737 have been shown to be specific to Bcl-XL subclass while Mcl-1 and A1 show resistance to the same drug. An efficacious inhibitor should target all the anti-apoptotic Bcl-2 proteins. Hence, development of inhibitors selective to Mcl-1 and A1 is of prime importance for targeted cancer therapeutics. The first step to achieve this goal is to understand the molecular basis of high binding affinities of specific pro-apoptotic BH3 peptides for Mcl-1 and A1. To understand the interactions between the BH3 peptides and Mcl-1/A1, we performed multi-nanosecond molecular dynamics (MD) simulations of six complex structures of Mcl-1 and A1. With the exception of Bad, all complex structures were experimentally determined. Bad complex structures were modeled. Our simulation studies identified specific pattern of polar interactions between Mcl-1/A1 and high-affinity binding BH3 peptides. The lack of such polar interactions in Bad peptide complex is attributed to specific basic residues present before and after the highly conserved Leu residue. The close approach of basic residues in Bad and Mcl-1/A1 is hypothesized to be the cause of weak binding affinity. To test this hypothesis, we generated in silico mutants of these basic residues in Bad peptide and Mcl-1/A1 proteins. MD simulations of the mutant systems established the pattern of stable polar interactions observed in high-affinity binding BH3 peptides. We have thus identified specific residue positions in Bad and Mcl-1/A1 responsible for the weak binding affinity. Results from these simulation studies will aid in the development of inhibitors specific to Mcl-1 and A1 proteins.

New pyridazinone-4-carboxamides as new cannabinoid receptor type-2 inverse agonists: Synthesis, pharmacological data and molecular docking

In the last few years, cannabinoid type-2 receptor (CB2R) selective ligands have shown a great potential as novel therapeutic drugs in several diseases. With the aim of discovering new selective cannabinoid ligands, a series of pyridazinone-4-carboxamides was designed and synthesized, and the new derivatives tested for their affinity toward the hCB1R and hCB2R. The 6-(4-chloro-3-methylphenyl)-2-(4-fluorobenzyl)-N-(cis-4-methylcyclohexyl)-3-oxo-2,3-dihydropyridazine-4-carboxamide (9) displayed high CB2-affinity (KiCB2 = 2.0 ± 0.81 nM) and a notable selectivity (KiCB1/KiCB2 > 2000). In addition, 9 and other active new synthesized entities have demonstrated to behave as CB2R inverse agonists in [35S]-GTPγS binding assay. ADME predictions of the newly synthesized CB2R ligands suggest a favourable pharmacokinetic profile. Docking studies disclosed the specific pattern of interactions of these derivatives. Our results support that pyridazinone-4-carboxamides represent a new promising scaffold for the development of potent and selective CB2R ligands.

Morphine Decreases Social Interaction of Adult Male Rats, While THC Does Not Affect It

The aim of the present study was to compare effect of three low doses of morphine (MOR) and delta9-tetrahydrocannabinol (THC) on social behavior tested in Social interaction test (SIT). 45 min prior to testing adult male rats received one of the drugs or solvents: MOR (1; 2.5; 5 mg/kg); saline as a solvent for MOR; THC (0.5; 1; 2 mg/kg); ethanol as a solvent for THC. Occurrence and time spent in specific patterns of social interactions (SI) and non-social activities (locomotion and rearing) was video-recorded for 5 min and then analyzed. MOR in doses of 1 and 2.5 mg/kg displayed decreased SI in total. Detailed analysis of specific patterns of SI revealed decrease in mutual sniffing and allo-grooming after all doses of MOR. The highest dose (5 mg/kg) of MOR decreased following and increased genital investigation. Rearing activity was increased by lower doses of MOR (1 and 2.5 mg/kg). THC, in each of the tested doses, did not induce any specific changes when compared to matching control group (ethanol). However, an additional statistical analysis showed differences between all THC groups and their ethanol control group when compared to saline controls. There was lower SI in total, lower mutual sniffing and allo-grooming, but higher rearing in THC and ethanol groups than in saline control group. Thus, changes seen in THC and ethanol groups are seemed to be attributed mainly to the effect of the ethanol. Based on the present results we can assume that opioids affect SI more than cannabinoid.

The Interaction Network Ontology-supported modeling and mining of complex interactions represented with multiple keywords in biomedical literature.

BackgroundThe Interaction Network Ontology (INO) logically represents biological interactions, pathways, and networks. INO has been demonstrated to be valuable in providing a set of structured ontological terms and associated keywords to support literature mining of gene-gene interactions from biomedical literature. However, previous work using INO focused on single keyword matching, while many interactions are represented with two or more interaction keywords used in combination.MethodsThis paper reports our extension of INO to include combinatory patterns of two or more literature mining keywords co-existing in one sentence to represent specific INO interaction classes. Such keyword combinations and related INO interaction type information could be automatically obtained via SPARQL queries, formatted in Excel format, and used in an INO-supported SciMiner, an in-house literature mining program. We studied the gene interaction sentences from the commonly used benchmark Learning Logic in Language (LLL) dataset and one internally generated vaccine-related dataset to identify and analyze interaction types containing multiple keywords. Patterns obtained from the dependency parse trees of the sentences were used to identify the interaction keywords that are related to each other and collectively represent an interaction type.ResultsThe INO ontology currently has 575 terms including 202 terms under the interaction branch. The relations between the INO interaction types and associated keywords are represented using the INO annotation relations: ‘has literature mining keywords’ and ‘has keyword dependency pattern’. The keyword dependency patterns were generated via running the Stanford Parser to obtain dependency relation types. Out of the 107 interactions in the LLL dataset represented with two-keyword interaction types, 86 were identified by using the direct dependency relations. The LLL dataset contained 34 gene regulation interaction types, each of which associated with multiple keywords. A hierarchical display of these 34 interaction types and their ancestor terms in INO resulted in the identification of specific gene-gene interaction patterns from the LLL dataset. The phenomenon of having multi-keyword interaction types was also frequently observed in the vaccine dataset.ConclusionsBy modeling and representing multiple textual keywords for interaction types, the extended INO enabled the identification of complex biological gene-gene interactions represented with multiple keywords.Electronic supplementary materialThe online version of this article (doi:10.1186/s13040-016-0118-0) contains supplementary material, which is available to authorized users.

Synthesis, molecular modeling and SAR study of novel pyrazolo[5,1-f][1,6]naphthyridines as CB2 receptor antagonists/inverse agonists

Pyrazolo[5,1-f][1,6]naphthyridine-carboxamide derivatives were synthesized and evaluated for the affinity at CB1 and CB2 receptors. Based on the AgOTf and proline-cocatalyzed multicomponent methodology, the ethyl 5-(p-tolyl)pyrazolo[5,1-f][1,6]naphthyridine-2-carboxylate (12) and ethyl 5-(2,4-dichlorophenyl)pyrazolo[5,1-f][1,6]naphthyridine-2-carboxylate (13) intermediates were synthesized from the appropriate o-alkynylaldehydes, p-toluenesulfonyl hydrazide and ethyl pyruvate. Most of the novel compounds feature a p-tolyl (8a–i) or a 2,4-dichlorophenyl (8j) motif at the C5-position of the tricyclic pyrazolo[5,1-f][1,6]naphthyridine scaffold. Structural variation on the carboxamide moiety at the C2-position includes basic monocyclic, terpenoid and adamantine-based amines. Among these derivatives, compound 8h (N-adamant-1-yl-5-(p-tolyl)pyrazolo[5,1-f][1,6]naphthyridine-2-carboxamide) exhibited the highest CB2 receptor affinity (Ki=33nM) and a high degree of selectivity (KiCB1/KiCB2=173:1), whereas a similar trend in the near nM range was seen for the bornyl analogue (compound 8f, Ki=53nM) and the myrtanyl derivative 8j (Ki=67nM). Effects of 8h, 8f and 8j on forskolin-stimulated cAMP levels were determined, showing antagonist/inverse agonist properties for such compounds. Docking studies conducted for these derivatives and the reference antagonist/inverse agonist compound 4 (SR144528) disclosed the specific pattern of interactions probably related to the pyrazolo[5,1-f][1,6]naphthyridine scaffold as CB2 inverse agonists.

Multifaceted analyses of the interactions between human heart type fatty acid binding protein and its specific aptamers

BackgroundAptamer-protein interaction studies have been mainly confined to dissociation constant (Kd) determination. A combinatorial approach involving limited proteolysis mass spectroscopy, molecular docking and CD studies is reported here to elucidate the specific interactions involved. MethodsTo generate aptamers specific for human FABP3, SELEX was performed incorporating counter SELEX cycles against control FABPs and GST tag, followed by their characterization by EMSA, CD and SVD analysis. Based on computationally obtained aptamer-protein complex models, the interacting aptamer, and protein residues were predicted and supported by limited proteolysis experiments. ResultsTwo aptamers N13 and N53 specific for human fatty acid binding protein (FABP3) were isolated with corresponding Kd of 0.0743±0.0142μM and 0.3337±0.1485μM for FABP3 interactions. Both aptamers possess stable B-DNA structures at salt concentration of 100mM and pH range (6–9). The N13 aptamer led interaction involved 3 salt bridges and 2 hydrogen bonds, whereas N53 had 2 salt bridges with 8 hydrogen and 7 hydrophobic interactions. ConclusionsThe aptamers generated are the first to be reported against human FABP3. The higher interaction footprint of N53 incited synergistic conformational changes in both N53 and FABP3 during interaction, leading to a decline in binding affinity in comparison to N13 which corroborated to the calculated Kd values. General significanceThis combinatorial method may be used to retrieve the possible specific binding modes and interaction patterns involved in large aptamer-protein complexes. Thus the method can be exploited to identify the optimum aptamer length for in-depth structure-function studies and its tailored applications.

Quantitative approach to collaborative learning: performance prediction, individual assessment, and group composition

The benefits of collaborative learning, although widely reported, lack the quantitative rigor and detailed insight into the dynamics of interactions within the group, while individual contributions and their impacts on group members and their collaborative work remain hidden behind joint group assessment. To bridge this gap we intend to address three important aspects of collaborative learning focused on quantitative evaluation and prediction of group performance. First, we use machine learning techniques to predict group performance based on the data of member interactions and thereby identify whether, and to what extent, the group’s performance is driven by specific patterns of learning and interaction. Specifically, we explore the application of Extreme Learning Machine and Classification and Regression Trees to assess the predictability of group academic performance from live interaction data. Second, we propose a comparative model to unscramble individual student performances within the group. These performances are then used further in a generative mixture model of group grading as an explicit combination of isolated individual student grade expectations and compared against the actual group performances to define what we coined as collaboration synergy - directly measuring the improvements of collaborative learning. Finally the impact of group composition of gender and skills on learning performance and collaboration synergy is evaluated. The analysis indicates a high level of predictability of group performance based solely on the style and mechanics of collaboration and quantitatively supports the claim that heterogeneous groups with the diversity of skills and genders benefit more from collaborative learning than homogeneous groups.

The interactome of Streptococcus pneumoniae and its bacteriophages show highly specific patterns of interactions among bacteria and their phages

Although an abundance of bacteriophages exists, little is known about interactions between their proteins and those of their bacterial hosts. Here, we experimentally determined the phage-host interactomes of the phages Dp-1 and Cp-1 and their underlying protein interaction network in the host Streptococcus pneumoniae. We compared our results to the interaction patterns of E. coli phages lambda and T7. Dp-1 and Cp-1 target highly connected host proteins, occupy central network positions, and reach many protein clusters through the interactions of their targets. In turn, lambda and T7 targets cluster to conserved and essential proteins in E. coli, while such patterns were largely absent in S. pneumoniae. Furthermore, targets in E. coli were mutually strongly intertwined, while targets of Dp-1 and Cp-1 were strongly connected through essential and orthologous proteins in their immediate network vicinity. In both phage-host systems, the impact of phages on their protein targets appears to extend from their network neighbors, since proteins that interact with phage targets were located in central network positions, have a strong topologically disruptive effect and touch complexes with high functional heterogeneity. Such observations suggest that the phages, biological impact is accomplished through a surprisingly limited topological reach of their targets.