Social Interaction Effects on Fertility: Intentions and Behaviors

The existing literature shows that social interactions in individuals' networks affect their reproductive attitudes and behaviors through three mechanisms: social influence, social learning, and social support. In this paper, we discuss to what extent the Theory of Planned Behavior (TPB), an individual based theorization of intentions and behavior used to model fertility, takes these social mechanisms into account. We argue that the TPB already integrates social influence and that it could easily accommodate the two other social network mechanisms. By doing so, the theory would be enriched in two respects. First, it will explain more completely how macro level changes eventually ends in micro level changes in behavioral intentions. Indeed, mechanisms of social influence may explain why changes in representations of parenthood and ideal family size can be slower than changes in socio-economic conditions and institutions. Social learning mechanisms should also be considered, since they are crucial to distinguish who adopts new behavioral beliefs and practices, when change at the macro level finally sinks in. Secondly, relationships are a capital of services that can complement institutional offering (informal child care) as well as a capital of knowledge which help individuals navigate in a complex institutional reality, providing a crucial element to explain heterogeneity in the successful realization of fertility intentions across individuals. We develop specific hypotheses concerning the effect of social interactions on fertility intentions and their realization to conclude with a critical review of the existing surveys suitable to test them and their limits.

Dynamic simulation of regulatory networks using SQUAD.

BACKGROUND: The ambition of most molecular biologists is the understanding of the intricate network of molecular interactions that control biological systems. As scientists uncover the components and the connectivity of these networks, it becomes possible to study their dynamical behavior as a whole and discover what is the specific role of each of their components. Since the behavior of a network is by no means intuitive, it becomes necessary to use computational models to understand its behavior and to be able to make predictions about it. Unfortunately, most current computational models describe small networks due to the scarcity of kinetic data available. To overcome this problem, we previously published a methodology to convert a signaling network into a dynamical system, even in the total absence of kinetic information. In this paper we present a software implementation of such methodology. RESULTS: We developed SQUAD, a software for the dynamic simulation of signaling networks using the standardized qualitative dynamical systems approach. SQUAD converts the network into a discrete dynamical system, and it uses a binary decision diagram algorithm to identify all the steady states of the system. Then, the software creates a continuous dynamical system and localizes its steady states which are located near the steady states of the discrete system. The software permits to make simulations on the continuous system, allowing for the modification of several parameters. Importantly, SQUAD includes a framework for perturbing networks in a manner similar to what is performed in experimental laboratory protocols, for example by activating receptors or knocking out molecular components. Using this software we have been able to successfully reproduce the behavior of the regulatory network implicated in T-helper cell differentiation. CONCLUSION: The simulation of regulatory networks aims at predicting the behavior of a whole system when subject to stimuli, such as drugs, or determine the role of specific components within the network. The predictions can then be used to interpret and/or drive laboratory experiments. SQUAD provides a user-friendly graphical interface, accessible to both computational and experimental biologists for the fast qualitative simulation of large regulatory networks for which kinetic data is not necessarily available.

Aversive Stimuli and Functional Networks of Fear Learning in PTSD : 734

Background: One characteristic of post traumatic stress disorder is an inability to adapt to a safe environment i.e. to change behavior when predictions of adverse outcomes are not met. Recent studies have also indicated that PTSD patients have altered pain processing, with hyperactivation of the putamen and insula to aversive stimuli (Geuze et al, 2007). The present study examined neuronal responses to aversive and predicted aversive events. Methods: Twenty-four trauma exposed non-PTSD controls and nineteen subjects with PTSD underwent fMRI imaging during a partial reinforcement fear conditioning paradigm, with a mild electric shock as the unconditioned stimuli (UCS). Three conditions were analyzed: actual presentations of the UCS, events when a UCS was expected, but omitted (CS+), and events when the UCS was neither expected nor delivered (CS-). Results: The UCS evoked significant alterations in the pain matrix consisting of the brainstem, the midbrain, the thalamus, the insula, the anterior and middle cingulate and the contralateral somatosensory cortex. PTSD subjects displayed bilaterally elevated putamen activity to the electric shock, as compared to controls. In trials when USC was expected, but omitted, significant activations were observed in the brainstem, the midbrain, the anterior insula and the anterior cingulate. PTSD subjects displayed similar activations, but also elevated activations in the amygdala and the posterior insula. Conclusions: These results indicate altered fear and safety learning in PTSD, and neuronal activations are further explored in terms of functional connectivity using psychophysiological interaction analyses.

Do labour mobility and networks foster geographical knowledge diffusion? The case of European regions

The goal of this paper is twofold: first, we aim to assess the role played by inventors’ cross-regional mobility and networks of collaboration in fostering knowledge diffusion across regions and subsequent innovation. Second, we intend to evaluate the feasibility of using mobility and networks information to build cross-regional interaction matrices to be used within the spatial econometrics toolbox. To do so, we depart from a knowledge production function where regional innovation intensity is a function not only of the own regional innovation inputs but also external accessible R&D gained through interregional interactions. Differently from much of the previous literature, cross-section gravity models of mobility and networks are estimated to use the fitted values to build our ‘spatial’ weights matrices, which characterize the intensity of knowledge interactions across a panel of 269 regions covering most European countries over 6 years.

Networks of PhD Students and Academic Performance: A Comparison across Countries

In this article we compare regression models obtained to predict PhD students’ academic performance in the universities of Girona (Spain) and Slovenia. Explanatory variables are characteristics of PhD student’s research group understood as an egocentered social network, background and attitudinal characteristics of the PhD students and some characteristics of the supervisors. Academic performance was measured by the weighted number of publications. Two web questionnaires were designed, one for PhD students and one for their supervisors and other research group members. Most of the variables were easily comparable across universities due to the careful translation procedure and pre-tests. When direct comparison was notpossible we created comparable indicators. We used a regression model in which the country was introduced as a dummy coded variable including all possible interaction effects. The optimal transformations of the main and interaction variables are discussed. Some differences between Slovenian and Girona universities emerge. Some variables like supervisor’s performance and motivation for autonomy prior to starting the PhD have the same positive effect on the PhD student’s performance in both countries. On the other hand, variables like too close supervision by the supervisor and having children have a negative influence in both countries. However, we find differences between countries when we observe the motivation for research prior to starting the PhD which increases performance in Slovenia but not in Girona. As regards network variables, frequency of supervisor advice increases performance in Slovenia and decreases it in Girona. The negative effect in Girona could be explained by the fact that additional contacts of the PhD student with his/her supervisor might indicate a higher workload in addition to or instead of a better advice about the dissertation. The number of external student’s advice relationships and social support mean contact intensity are not significant in Girona, but they have a negative effect in Slovenia. We might explain the negative effect of external advice relationships in Slovenia by saying that a lot of external advice may actually result from a lack of the more relevant internal advice

A targeted association study of immunity genes and networks suggests novel associations with placental malaria infection

A large proportion of the death toll associated with malaria is a consequence of malaria infection during pregnancy, causing up to 200,000 infant deaths annually. We previously published the first extensive genetic association study of placental malaria infection, and here we extend this analysis considerably, investigating genetic variation in over 9,000 SNPs in more than 1,000 genes involved in immunity and inflammation for their involvement in susceptibility to placental malaria infection. We applied a new approach incorporating results from both single gene analysis as well as gene-gene interactionson a protein-protein interaction network. We found suggestive associations of variants in the gene KLRK1 in the single geneanalysis, as well as evidence for associations of multiple members of the IL-7/IL-7R signalling cascade in the combined analysis. To our knowledge, this is the first large-scale genetic study on placental malaria infection to date, opening the door for follow-up studies trying to elucidate the genetic basis of this neglected form of malaria.

Adolescent support networks in a health care context: the interface between health, family and education

AbstractOBJECTIVEAnalyze adolescents' perceptions about support networks and their health needs.METHODAnalytical and interpretive study using focus groups conducted in municipal state schools in Fortaleza, in the State of Ceará during the first semester of 2012. The sample comprised 36 male and female adolescents aged between 13 and 16 years attending the ninth grade of the second phase of elementary school.RESULTSThematic analysis revealed that the health care support network and interaction between health professionals, education professionals and family members was insufficient, constituting a lack of an integrated network to enable and provide support for health promotion.CONCLUSIONCoordination between education, health and family services has the potential to act as a support network to help meet adolescents' healthcare needs and demands.

On circuit functionality in boolean networks.

It has been proved, for several classes of continuous and discrete dynamical systems, that the presence of a positive (resp. negative) circuit in the interaction graph of a system is a necessary condition for the presence of multiple stable states (resp. a cyclic attractor). A positive (resp. negative) circuit is said to be functional when it "generates" several stable states (resp. a cyclic attractor). However, there are no definite mathematical frameworks translating the underlying meaning of "generates." Focusing on Boolean networks, we recall and propose some definitions concerning the notion of functionality along with associated mathematical results.

A protein interaction atlas for the nuclear receptors: properties and quality of a hub-based dimerisation network.

BACKGROUND: The nuclear receptors are a large family of eukaryotic transcription factors that constitute major pharmacological targets. They exert their combinatorial control through homotypic heterodimerisation. Elucidation of this dimerisation network is vital in order to understand the complex dynamics and potential cross-talk involved. RESULTS: Phylogeny, protein-protein interactions, protein-DNA interactions and gene expression data have been integrated to provide a comprehensive and up-to-date description of the topology and properties of the nuclear receptor interaction network in humans. We discriminate between DNA-binding and non-DNA-binding dimers, and provide a comprehensive interaction map, that identifies potential cross-talk between the various pathways of nuclear receptors. CONCLUSION: We infer that the topology of this network is hub-based, and much more connected than previously thought. The hub-based topology of the network and the wide tissue expression pattern of NRs create a highly competitive environment for the common heterodimerising partners. Furthermore, a significant number of negative feedback loops is present, with the hub protein SHP [NR0B2] playing a major role. We also compare the evolution, topology and properties of the nuclear receptor network with the hub-based dimerisation network of the bHLH transcription factors in order to identify both unique themes and ubiquitous properties in gene regulation. In terms of methodology, we conclude that such a comprehensive picture can only be assembled by semi-automated text-mining, manual curation and integration of data from various sources.

Splenium of corpus callosum: patterns of interhemispheric interaction in children and adults.

The splenium of the corpus callosum connects the posterior cortices with fibers varying in size from thin late-myelinating axons in the anterior part, predominantly connecting parietal and temporal areas, to thick early-myelinating fibers in the posterior part, linking primary and secondary visual areas. In the adult human brain, the function of the splenium in a given area is defined by the specialization of the area and implemented via excitation and/or suppression of the contralateral homotopic and heterotopic areas at the same or different level of visual hierarchy. These mechanisms are facilitated by interhemispheric synchronization of oscillatory activity, also supported by the splenium. In postnatal ontogenesis, structural MRI reveals a protracted formation of the splenium during the first two decades of human life. In doing so, the slow myelination of the splenium correlates with the formation of interhemispheric excitatory influences in the extrastriate areas and the EEG synchronization, while the gradual increase of inhibitory effects in the striate cortex is linked to the local inhibitory circuitry. Reshaping interactions between interhemispherically distributed networks under various perceptual contexts allows sparsification of responses to superfluous information from the visual environment, leading to a reduction of metabolic and structural redundancy in a child's brain.

A role for septins in the interaction between the Listeria monocytogenes INVASION PROTEIN InlB and the Met receptor.

Septins are conserved GTPases that form filaments and are required for cell division. During interphase, septin filaments associate with cellular membrane and cytoskeleton networks, yet the functional significance of these associations have, to our knowledge, remained unknown. We recently discovered that different septins, SEPT2 and SEPT11, regulate the InlB-mediated entry of Listeria monocytogenes into host cells. Here we address the role of SEPT2 and SEPT11 in the InlB-Met interactions underlying Listeria invasion to explore how septins modulate surface receptor function. We observed that differences in InlB-mediated Listeria entry correlated with differences in Met surface expression caused by septin depletion. Using atomic force microscopy on living cells, we show that septin depletion significantly reduced the unbinding force of InlB-Met interaction and the viscosity of membrane tethers at locations where the InlB-Met interaction occurs. Strikingly, the same order of difference was observed for cells in which the actin cytoskeleton was disrupted. Consistent with a proposed role of septins in association with the actin cytoskeleton, we show that cell elasticity is decreased upon septin or actin inactivation. Septins are therefore likely to participate in anchorage of the Met receptor to the actin cytoskeleton, and represent a critical determinant in surface receptor function.

Gene Ontology Function prediction in Mollicutes using Protein-Protein Association Networks

Abstract Background: Many complex systems can be represented and analysed as networks. The recent availability of large-scale datasets, has made it possible to elucidate some of the organisational principles and rules that govern their function, robustness and evolution. However, one of the main limitations in using protein-protein interactions for function prediction is the availability of interaction data, especially for Mollicutes. If we could harness predicted interactions, such as those from a Protein-Protein Association Networks (PPAN), combining several protein-protein network function-inference methods with semantic similarity calculations, the use of protein-protein interactions for functional inference in this species would become more potentially useful. Results: In this work we show that using PPAN data combined with other approximations, such as functional module detection, orthology exploitation methods and Gene Ontology (GO)-based information measures helps to predict protein function in Mycoplasma genitalium. Conclusions: To our knowledge, the proposed method is the first that combines functional module detection among species, exploiting an orthology procedure and using information theory-based GO semantic similarity in PPAN of the Mycoplasma species. The results of an evaluation show a higher recall than previously reported methods that focused on only one organism network.

The Impact of ICTs on Lecturer and Student Interaction in University Education Processes

Interaction is a basic element in any educational process, and it is something that needs to be reconsidered in the light of technology. In order to examine the methodological changes that ICTs bring to teaching from an interaction perspective, a study was carried out at the University of Lleida to observe interaction processes in various face-to-face, blended learning and e-learning subjects. The methodological design was based on three data collection techniques: documentary analysis of subject curricula, lecturer and student questionnaires, and lecturer interviews. The data showed that, as the online component of subjects increased, the lecturers and students used more technological tools to communicate (e-mail, forums, chats, social networks, etc.). Furthermore, we found that the lecturers and students basically communicated for academic purposes. While they hardly ever communicated for personal reasons (guidance, support, etc.), they claimed that closer contact with a non-academic focus would be preferable. We also observed that the students’ work was more individual in e-learning subjects. Although there is still a considerable way to go in ICT-mediated lecturer-student interaction, both the lecturers and students recognise the potential of such technologies, even though they still do not use them as they feel they should.

Social network extraction and analysis based on multimodal dyadic interaction

Social interactions are a very important component in people"s lives. Social network analysis has become a common technique used to model and quantify the properties of social interactions. In this paper, we propose an integrated framework to explore the characteristics of a social network extracted from multimodal dyadic interactions. For our study, we used a set of videos belonging to New York Times" Blogging Heads opinion blog. The Social Network is represented as an oriented graph, whose directed links are determined by the Influence Model. The links" weights are a measure of the"influence" a person has over the other. The states of the Influence Model encode automatically extracted audio/visual features from our videos using state-of-the art algorithms. Our results are reported in terms of accuracy of audio/visual data fusion for speaker segmentation and centrality measures used to characterize the extracted social network.

Cultural aspects of globalizing university-industry knowledge interaction in China

Previous studies of the local involvement of multinational corporation (MNC) subsidiaries focus on host-country firms and local business partners such as suppliers and customers. The role of host-country universities in the same context of innovation networks is neglected. Furthermore, there are many organizational culture- and knowledge-related differences between universities and companies, and this is likely to pose additional challenges for successful collaboration. Early university-industry (U-I) studies have primarily been limited within a national boundary, being concerned with a single level of culture (i.e., at an organizational level) and one-way knowledge transfer from university to industry. Research on more dynamic knowledge interaction in multinational settings is lacking. This is particularly true in the business context of China. In today’s globalizing and rapidly changing organizations, addressing cultural differences and clashes is an everyday reality, and inter-cultural U-I collaboration is becoming a key asset for gaining global competitiveness. This study deals with Finnish MNC subsidiaries’ research collaboration with Chinese universities. It aims to explore the essence of such U-I collaboration and knowledge interaction, uncovering the deep functioning mechanisms of culture underlying effective collaborative knowledge creation and innovation. The study reviews critically different bodies of literature including knowledge management theories and studies, U-I collaboration and knowledge interaction, and cross-cultural research in terms of organizational knowledge generation and utilization. It adopts a case study strategy with qualitative research methods, and data is collected through in-depth interviews and participant observation. The study presents the following major findings: 1. In the light of a comprehensive analysis of U-I collaboration, an effective matching strategy is proposed, in the assumption that good alignment of knowledge interaction strategies and approaches with their corresponding knowledge type, capability development and research task may greatly enhance the effectiveness of cross-cultural U-I collaboration and knowledge interaction. 2. It is proposed that in the Chinese MNC context more dynamic types of knowledge interaction like knowledge co-creation should be of key concern particularly when dealing simultaneously with multi-disciplinary applied research of human factors and technologies. U-I knowledge interaction, otherwise, pays attention only to the study of one-way technology and knowledge transfer. 3. It is posited that the influence of culture on collaborative knowledge interaction can be studied in a valuable way when knowledge-related variables are simultaneously taken into account. A systematic analysis of the role of knowledge in cross-cultural knowledge interaction could best be approached from multi-aspects of knowledge including not only nature, characteristics and types of knowledge but also the process of knowledge (e.g., intensifications of knowledge interaction). 4. The study demonstrates the significant role of aspects of the host-country culture (e.g., Chinese guanxi) in U-I collaboration and knowledge interaction. This is evident, for instance, in issues related to interpersonal relationships and trust, true interest and the relatedness of the research, mutual commitment and learning, communication intensity and interaction, and awareness of cultural and knowledge-related differences between collaboration partners. Theoretical and practical implications of the findings are suggested and discussed.