Health promotion networks in two districts in Bavaria, Germany: an exploratory case study mapping networks with respect to thematic agenda and location.

Introduction: Building networks is an essential part of health promotion. However, network analysis remains relatively unexplored in this field. This study introduces a new technique that maps thematic agendas and geographical locations of health promotion actors. Methods: This case study used elements of quantitative and qualitative methods to analyse network data. We used empirical data from two networks in Bavaria, a federal state of Germany. Results: We identified a total of 55 actors in the first network and 64 actors in the second. We categorized the thematic agenda of actors according to their main field of work: "healthy childhood development," "healthy middle age phase," "healthy ageing," "health equity in all phases of life." One network showed a significant surplus of actors that focus on "healthy ageing." We combined and analysed data from both networks collectively. Two districts with no health promotion actors within their geographical borders were identified. To put geographical gaps into context, data about deprivation and age was included. Discussion: Results identified geographical areas with high need for support from health promotion actors. Through comparison of our results with existing literature, we derived potential network strategies for further successful networking. This study adds a new perspective to characterize health promotion networks by mapping them thematically and geographically. The concept can be used to give health promotion organisations relevant insight into network structures. This can improve decision-making processes concerning partnership strategy and finally lead to a positive health impact. Hence, our findings encourage further development of this technique and other networking methods in the field of health equity and health promotion.

Spatial learning impairments and discoordination of entorhinal-hippocampal circuit coding following prolonged febrile seizures.

How the development and function of neural circuits governing learning and memory are affected by insults in early life remains poorly understood. The goal of this study was to identify putative changes in cortico-hippocampal signaling mechanisms that could lead to learning and memory deficits in a clinically relevant developmental pathophysiological rodent model, Febrile status epilepticus (FSE). FSE in both pediatric cases and the experimental animal model, is associated with enduring physiological alterations of the hippocampal circuit and cognitive impairment. Here, we deconstruct hippocampal circuit throughput by inducing slow theta oscillations in rats under urethane anesthesia and isolating the dendritic compartments of CA1 and dentate gyrus subfields, their reception of medial and lateral entorhinal cortex inputs, and the efficacy of signal propagation to each somatic cell layer. We identify FSE-induced theta-gamma decoupling at cortical synaptic input pathways and altered signal phase coherence along the CA1 and dentate gyrus somatodendritic axes. Moreover, increased DG synaptic activity levels are predictive of poor cognitive outcomes. We propose that these alterations in cortico-hippocampal coordination interfere with the ability of hippocampal dendrites to receive, decode and propagate neocortical inputs. If this frequency-specific syntax is necessary for cortico-hippocampal coordination and spatial learning and memory, its loss could be a mechanism for FSE cognitive comorbidities.

Disordered network structure and function in dystonia: pathological connectivity vs. adaptive responses.

Primary dystonia is thought to emerge through abnormal functional relationships between basal ganglia and cerebellar motor circuits. These interactions may differ across disease subtypes and provide a novel biomarker for diagnosis and treatment. Using a network mapping algorithm based on resting-state functional MRI (rs-fMRI), a method that is readily implemented on conventional MRI scanners, we identified similar disease topographies in hereditary dystonia associated with the DYT1 or DYT6 mutations and in sporadic patients lacking these mutations. Both networks were characterized by contributions from the basal ganglia, cerebellum, thalamus, sensorimotor areas, as well as cortical association regions. Expression levels for the two networks were elevated in hereditary and sporadic dystonia, and in non-manifesting carriers of dystonia mutations. Nonetheless, the distribution of abnormal functional connections differed across groups, as did metrics of network organization and efficiency in key modules. Despite these differences, network expression correlated with dystonia motor ratings, significantly improving the accuracy of predictions based on thalamocortical tract integrity obtained with diffusion tensor MRI (DTI). Thus, in addition to providing unique information regarding the anatomy of abnormal brain circuits, rs-fMRI functional networks may provide a widely accessible method to help in the objective evaluation of new treatments for this disorder.

First-Year Implementation of the EXercise for Cancer to Enhance Living Well (EXCEL) Study: Building Networks to Support Rural and Remote Community Access to Exercise Oncology Resources.

Barriers to exercise-oncology programs remain for those living with and beyond cancer in rural and remote communities, including geographic isolation and access to programs. The EXercise for Cancer to Enhance Living Well (EXCEL) study was designed to support exercise-oncology implementation in rural and remote communities across Canada. The purpose of this analysis was to evaluate the first-year reach, adoption, and implementation of the EXCEL study. Reach outcomes included participant characteristics, study enrolment, and referral type (self vs. healthcare-provider [HCP] referral). Adoption outcomes included the number of clinical contacts, trained qualified exercise professionals (QEPs), and QEPs delivering EXCEL exercise classes. Implementation outcomes included retention, adherence, assessment completion rates, and adverse-event reporting. A total of 290 individuals living with cancer enrolled in EXCEL in year one, with an 81.4% retention to the study intervention. Most participants self-referred to EXCEL (75.8%). EXCEL's HCP network consisted of 163 clinical contacts, and the QEP network included 45 trained QEPs, 22 of whom delivered EXCEL classes. Adherence to the exercise intervention was 78.2%, and only one adverse event (mild) was reported. Fitness assessment and patient-reported outcome completion rates were above 85% pre- and post-intervention. EXCEL has developed HCP and QEP networks supporting exercise referral and online delivery, and the intervention is meeting feasibility markers. These implementation findings will inform the continued gathering of feedback across stakeholders to ensure that best evidence informs best practices.

Long-term morphological and functional dynamics of human stem cell-derived neuronal networks on high-density micro-electrode arrays.

Comprehensive electrophysiological characterizations of human induced pluripotent stem cell (hiPSC)-derived neuronal networks are essential to determine to what extent these in vitro models recapitulate the functional features of in vivo neuronal circuits. High-density micro-electrode arrays (HD-MEAs) offer non-invasive recording with the best spatial and temporal resolution possible to date. For 3 months, we tracked the morphology and activity features of developing networks derived from a transgenic hiPSC line in which neurogenesis is inducible by neurogenic transcription factor overexpression. Our morphological data revealed large-scale structural changes from homogeneously distributed neurons in the first month to the formation of neuronal clusters over time. This led to a constant shift in position of neuronal cells and clusters on HD-MEAs and corresponding changes in spatial distribution of the network activity maps. Network activity appeared as scarce action potentials (APs), evolved as local bursts with longer duration and changed to network-wide synchronized bursts with higher frequencies but shorter duration over time, resembling the emerging burst features found in the developing human brain. Instantaneous firing rate data indicated that the fraction of fast spiking neurons (150-600 Hz) increases sharply after 63 days post induction (dpi). Inhibition of glutamatergic synapses erased burst features from network activity profiles and confirmed the presence of mature excitatory neurotransmission. The application of GABAergic receptor antagonists profoundly changed the bursting profile of the network at 120 dpi. This indicated a GABAergic switch from excitatory to inhibitory neurotransmission during circuit development and maturation. Our results suggested that an emerging GABAergic system at older culture ages is involved in regulating spontaneous network bursts. In conclusion, our data showed that long-term and continuous microscopy and electrophysiology readouts are crucial for a meaningful characterization of morphological and functional maturation in stem cell-derived human networks. Most importantly, assessing the level and duration of functional maturation is key to subject these human neuronal circuits on HD-MEAs for basic and biomedical applications.

A strategic scheme for partnership supply networks focusing on green multi-agent transportations: a game theory approach.

Competition to gain more market share leads to the development of a dynamic environment and the fulfillment of an improvement cycle in supply networks. In this paper, as the first attempt, two strategic periods based on the introduction and growth phases of supply networks are considered. Each of these periods has its own characteristics and develops different competitive structures. The allocation of market share between competing supply networks is carried out on the extent of their relationships with green orientations in the network. The ownership of supply sources in these networks is replaced by that of relationships (partnership supply) developed by some parent brands. The efforts of each parent brand towards establishing green supply relationships lead to a greater market share for it. Further to competition between the supply networks, co-petition within each network also results in the emergence of different virtual alliance structures. The performance history of each brand and its subsidiary partners in the first period is included in the second period's assessments and leads to the development or decline of the network. Another dimension of the paper lies in the development of multi-agent transportation arising from the green requirements. Two gaming-based heuristic algorithms are proposed for handling the decentralized decision-making structures in the multi-period multi-stage platform under discussion. To evaluate the taken approach, a real-world inspired case is taken into account. The numerical results prove the better performance of the proposed scheme towards green coverage of the network and, thereupon, increased market share.

Data for the modelling of the future power system with a high share of variable renewable energy.

Energy and power system models have become necessary tools that provide challenges and technical and economic solutions for integrating high shares of Variable Renewable Energy. Models are focused on analysing strategies of power systems to achieve their decarbonisation targets. The data presented in this paper includes the model algorithm, inputs, equations, modelling assumptions, supplementary materials, and results of the simulations supporting the research article titled "Facing the high share of variable renewable energy in the power system: flexibility and stability requirements". The analysis is based on data from the system operator of one of the European Union member states (Spain). The developed model allows making projections and calculations to obtain the power generation of each technology, the international interconnections, inertia, emissions, system costs and flexibility requirements of new technologies. These data can be used for energy policy development or decision making on power capacity and the balancing needs of the future power system.

Long Arm of Motorway-The Impact of Fenced Road on the Mortality of European Badgers.

We studied the impact of the new fenced and accident-safe motorway on the mortality of European badgers Meles meles on local roads in western Poland in 2010-2015. We monitored the badgers mortality on local roads of three categories: main roads, secondary roads and county roads. The study was conducted before and after the opening of the motorway in 2012. We hypothesized that the mortality of badgers is lower due to traffic concentration on motorway. Ninety two badgers were killed in collisions with vehicles on all monitored roads. Mean number of killed badgers was lowest in 2010 before the motorway opening and the highest in 2012. The mortality of badgers on regional roads was highest after the opening of the motorway due to the changes in traffic on the access roads. Within the road network, the mortality of badgers was 5.8 individuals/10 km of road per whole study period with the highest rate on main roads 8.5 individuals/10 km. The badgers mortality was highest on county roads but it was lower than expected in relation to the road network density. The highest vehicle collision risk for badgers of both sexes occurred in June. Distance to human settlements was the only environmental factor that was positively related to badger mortality on roads. We conclude that the new motorway did not reduce the mortality rate of badgers on the adjacent roads because the status of local roads has changed and now they mainly function as access roads to the motorway.

The University of Alabama at Birmingham COVID-19 Collaborative Outcomes Research Enterprise: Developing an institutional learning health system in response to the global pandemic.

Introduction: As a local response to the COVID-19 global pandemic, the University of Alabama at Birmingham (UAB) established the UAB COVID-19 Collaborative Outcomes Research Enterprise (CORE), an institutional learning health system (LHS) to achieve an integrated health services outcomes and research response. Methods: We developed a network of expertise and capabilities to rapidly develop and deploy an institutional-level interdisciplinary LHS. Based upon a scoping review of the literature and the Knowledge to Action Framework, we adopted a LHS framework identifying contributors and components necessary to developing a system within and between the university academic and medical centers. We used social network analysis to examine the emergence of informal work patterns and diversified network capabilities based on the LHS framework. Results: This experience report details three principal characteristics of the UAB COVID-19 CORE LHS development: (a) identifying network contributors and components; (b) building the institutional network; and (c) diversifying network capabilities. Contributors and committees were identified from seven components of LHS: (a) collaborative and executive leadership committee, (b) research coordinating committee, (c) oversight and ethics committee, (d) thematic scientific working groups, (e) programmatic working groups, (f) informatics capabilities, and (g) patient advisory groups. Evolving from the topical interests of the initial CORE participants, scientific working groups emerged to support the learning system network. Programmatic working groups were charged with developing a comprehensive and mutually accessible COVID-19 database. Discussion: Our LHS framework allowed for effective integration of multiple academic and medical centers into a cohesive institutional-level learning system. Network analysis indicated diversity of institutional disciplines, professional rank, and topical focus pertaining to COVID-19, with each center leveraging existing institutional responsibilities to minimize gaps in network capabilities. Conclusion: Incorporating an adapted LHS framework designed for academic medical centers served as a foundational resource supporting further institutional-level efforts to develop agile and responsive learning networks.

Promoting Students' Health at University: Key Stakeholders, Cooperation, and Network Development.

Background: Cooperation among university units is considered a cornerstone for the promotion of students' health. The underlying mechanisms of health-promoting networks at universities have rarely been examined so far. Shedding light on partnerships is generally limited to the naming of allied actors in a network. Objectives and Methods: In this study, we used network analysis intending to visualize and describe the positions and characteristics of the network actors, and examine organizational relationships to determine the characteristics of the complete network. Results: The network analysis at hand provides in-depth insights into university structures promoting students' health comprising 33 organizational units and hundreds of ties. Both cooperation and communication network show a flat, non-hierarchical structure, which is reflected by its low centralization indices (39-43%) and short average distances (1.43-1.47) with low standard deviations (0.499-0.507), small diameter (3), and the non-existence of subgroups. Density lies between 0.53 and 0.57. According to the respondents, the University Sports Center is considered the most important actor in the context of students' health. Presidium and Institute of Sport and Sports Science play an integral role in terms of network functionality. Conclusion: In the health-promoting network, numerous opportunities for further integration and interaction of actors exist. Indications for transferring results to other universities are discussed. Network analysis enables universities to profoundly analyze their health-promoting structures, which is the basis for sustained network governance and development.

Warped rhythms: Epileptic activity during critical periods disrupts the development of neural networks for human communication.

It is well established that temporal lobe epilepsy-the most common and well-studied form of epilepsy-can impair communication by disrupting social-emotional and language functions. In pediatric epilepsy, where seizures co-occur with the development of critical brain networks, age of onset matters: The earlier in life seizures begin, the worse the disruption in network establishment, resulting in academic hardship and social isolation. Yet, little is known about the processes by which epileptic activity disrupts developing human brain networks. Here we take a synthetic perspective-reviewing a range of research spanning studies on molecular and oscillatory processes to those on the development of large-scale functional networks-in support of a novel model of how such networks can be disrupted by epilepsy. We seek to bridge the gap between research on molecular processes, on the development of human brain circuitry, and on clinical outcomes to propose a model of how epileptic activity disrupts brain development.

Natural Environment and Social Relationship in the Development of Attentional Network.

The attention mechanism is related to both voluntary and automatic processes, that may be summarized in three distinct networks: alert, orientation, and inhibitory control. These networks can be modulated by different contextual and relational situations. Aim of this review is to explain how a combination of natural and social stimuli can positively affect the attentional processes. It has been proposed that the exposition to natural environment can positively affect direct attention, a common resource supporting both executive functioning and self-regulation processes in cognition. It has been suggested that the decrease of the effort required to voluntary control attention from the bottom upwards could determine some internal reflection that may support creative thinking secondarily to a simultaneous reduction in the effort required to orient attention between thoughts and impressions. In my view, not only exposition to natural and green environment improves attentional processes but also the involvement in social relationship. The development of the orientation and inhibitory control networks is sensitive to the social nature of the stimuli, for instance, in a task, including socially relevant stimuli the efficiency of these two attentional networks increases in children, in adults and in elderly subjects. Social attention, starting very early in the life (joint attention) is a very important mechanism for the regulation of social relationships. A key for a better development of cognitive functions such as attentional processes is the promotion of the immersion in the natural environment and the involvement in social relationship.

Development and analysis of an adverse outcome pathway network for human neurotoxicity.

An adverse outcome pathway (AOP) network is an attempt to represent the complexity of systems toxicology. This study illustrates how an AOP network can be derived and analysed in terms of its topological features to guide research and support chemical risk assessment. A four-step workflow describing general design principles and applied design principles was established and implemented. An AOP network linking nine linear AOPs was mapped and made available in AOPXplorer. The resultant AOP network was modelled and analysed in terms of its topological features, including level of degree, eccentricity and betweenness centrality. Several well-connected KEs were identified, and cell injury/death was established as the most hyperlinked KE across the network. The derived network expands the utility of linear AOPs to better understand signalling pathways involved in developmental and adult/ageing neurotoxicity. The results provide a solid basis to guide the development of in vitro test method batteries, as well as further quantitative modelling of key events (KEs) and key event relationships (KERs) in the AOP network, with an eventual aim to support hazard characterisation and chemical risk assessment.

Intrinsic temporal tuning of neurons in the optic tectum is shaped by multisensory experience.

For a biological neural network to be functional, its neurons need to be connected with synapses of appropriate strength, and each neuron needs to appropriately respond to its synaptic inputs. This second aspect of network tuning is maintained by intrinsic plasticity; yet it is often considered secondary to changes in connectivity and mostly limited to adjustments of overall excitability of each neuron. Here we argue that even nonoscillatory neurons can be tuned to inputs of different temporal dynamics and that they can routinely adjust this tuning to match the statistics of their synaptic activation. Using the dynamic clamp technique, we show that, in the tectum of Xenopus tadpole, neurons become selective for faster inputs when animals are exposed to fast visual stimuli but remain responsive to longer inputs in animals exposed to slower, looming, or multisensory stimulation. We also report a homeostatic cotuning between synaptic and intrinsic temporal properties of individual tectal cells. These results expand our understanding of intrinsic plasticity in the brain and suggest that there may exist an additional dimension of network tuning that has been so far overlooked.NEW & NOTEWORTHY We use dynamic clamp to show that individual neurons in the tectum of Xenopus tadpoles are selectively tuned to either shorter (more synchronous) or longer (less synchronous) synaptic inputs. We also demonstrate that this intrinsic temporal tuning is strongly shaped by sensory experiences. This new phenomenon, which is likely to be mediated by changes in sodium channel inactivation, is bound to have important consequences for signal processing and the development of local recurrent connections.

Meta-Network Analysis of Structural Correlation Networks Provides Insights Into Brain Network Development.

Analysis of developmental brain networks is fundamentally important for basic developmental neuroscience. In this paper, we focus on the temporally-covarying connection patterns, called meta-networks, and develop a new mathematical model for meta-network decomposition. With the proposed model, we decompose the developmental structural correlation networks of cortical thickness into five meta-networks. Each meta-network exhibits a distinctive spatial connection pattern, and its covarying trajectory highlights the temporal contribution of the meta-network along development. Systematic analysis of the meta-networks and covarying trajectories provides insights into three important aspects of brain network development.

The development of brain network hubs.

Some brain regions have a central role in supporting integrated brain function, marking them as network hubs. Given the functional importance of hubs, it is natural to ask how they emerge during development and to consider how they shape the function of the maturing brain. Here, we review evidence examining how brain network hubs, both in structural and functional connectivity networks, develop over the prenatal, neonate, childhood, and adolescent periods. The available evidence suggests that structural hubs of the brain arise in the prenatal period and show a consistent spatial topography through development, but undergo a protracted period of consolidation that extends into late adolescence. In contrast, the hubs of brain functional networks show a more variable topography, being predominantly located in primary cortical areas in early development, before moving to association areas by late childhood. These findings suggest that while the basic anatomical infrastructure of hubs may be established early, the functional viability and integrative capacity of these areas undergoes extensive postnatal maturation. Not all findings are consistent with this view however. We consider methodological factors that might drive these inconsistencies, and which should be addressed to promote a more rigorous investigation of brain network development.

Adverse outcome pathway networks I: Development and applications.

Based on the results of a Horizon Scanning exercise sponsored by the Society of Environmental Toxicology and Chemistry that focused on advancing the adverse outcome pathway (AOP) framework, the development of guidance related to AOP network development was identified as a critical need. This not only included questions focusing directly on AOP networks, but also on related topics such as mixture toxicity assessment and the implementation of feedback loops within the AOP framework. A set of two articles has been developed to begin exploring these concepts. In the present article (part I), we consider the derivation of AOP networks in the context of how it differs from the development of individual AOPs. We then propose the use of filters and layers to tailor AOP networks to suit the needs of a given research question or application. We briefly introduce a number of analytical approaches that may be used to characterize the structure of AOP networks. These analytical concepts are further described in a dedicated, complementary article (part II). Finally, we present a number of case studies that illustrate concepts underlying the development, analysis, and application of AOP networks. The concepts described in the present article and in its companion article (which focuses on AOP network analytics) are intended to serve as a starting point for further development of the AOP network concept, and also to catalyze AOP network development and application by the different stakeholder communities. Environ Toxicol Chem 2018;37:1723-1733. © 2018 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Defining toxicological tipping points in neuronal network development.

Measuring electrical activity of neural networks by microelectrode array (MEA) has recently shown promise for screening level assessments of chemical toxicity on network development and function. Important aspects of interneuronal communication can be quantified from a single MEA recording, including individual firing rates, coordinated bursting, and measures of network synchrony, providing rich datasets to evaluate chemical effects. Further, multiple recordings can be made from the same network, including during the formation of these networks in vitro. The ability to perform multiple recording sessions over the in vitro development of network activity may provide further insight into developmental effects of neurotoxicants. In the current study, a recently described MEA-based screen of 86 compounds in primary rat cortical cultures over 12 days in vitro was revisited to establish a framework that integrates all available primary measures of electrical activity from MEA recordings into a composite metric for deviation from normal activity (total scalar perturbation). Examining scalar perturbations over time and increasing concentration of compound allowed for definition of critical concentrations or "tipping points" at which the neural networks switched from recovery to non-recovery trajectories for 42 compounds. These tipping point concentrations occurred at predominantly lower concentrations than those causing overt cell viability loss or disrupting individual network parameters, suggesting tipping points may be a more sensitive measure of network functional loss. Comparing tipping points for six compounds with plasma concentrations known to cause developmental neurotoxicity in vivo demonstrated strong concordance and suggests there is potential for using tipping points for chemical prioritization.

Sage on the Stage: Women's Representation at an Academic Conference.

Who presents at conferences matters. Presenting research benefits speakers, and presenters shape the conclusions audiences draw about who can succeed in a field. This is particularly important for members of historically underrepresented or disadvantaged groups, such as women. We investigated gender representation over a 13-year period among speakers at the largest social and personality psychology conference. On average, women were underrepresented as speakers, though this effect diminished over time. Chairs appeared to serve as gatekeepers: In symposia chaired by women, almost half of the invited speakers were women, whereas in symposia chaired by men, it was a third. The representation of women as speakers varied significantly by academic rank, with women underrepresented at lower ranks but not as full professors, and by topic. Women also tended to present with a smaller, less varied array of individuals than men, though this could be explained by women's lower average academic rank.

A multivariate extension of mutual information for growing neural networks.

Recordings of neural network activity in vitro are increasingly being used to assess the development of neural network activity and the effects of drugs, chemicals and disease states on neural network function. The high-content nature of the data derived from such recordings can be used to infer effects of compounds or disease states on a variety of important neural functions, including network synchrony. Historically, synchrony of networks in vitro has been assessed either by determination of correlation coefficients (e.g. Pearson's correlation), by statistics estimated from cross-correlation histograms between pairs of active electrodes, and/or by pairwise mutual information and related measures. The present study examines the application of Normalized Multiinformation (NMI) as a scalar measure of shared information content in a multivariate network that is robust with respect to changes in network size. Theoretical simulations are designed to investigate NMI as a measure of complexity and synchrony in a developing network relative to several alternative approaches. The NMI approach is applied to these simulations and also to data collected during exposure of in vitro neural networks to neuroactive compounds during the first 12 days in vitro, and compared to other common measures, including correlation coefficients and mean firing rates of neurons. NMI is shown to be more sensitive to developmental effects than first order synchronous and nonsynchronous measures of network complexity. Finally, NMI is a scalar measure of global (rather than pairwise) mutual information in a multivariate network, and hence relies on less assumptions for cross-network comparisons than historical approaches.