Analysis of co-isogenic prion protein deficient mice reveals behavioral deficits, learning impairment, and enhanced hippocampal excitability

Background Cellular prion protein (PrPC) is a cell surface GPI-anchored protein, usually known for its role in the pathogenesis of human and animal prionopathies. However, increasing knowledge about the participation of PrPC in prion pathogenesis contrasts with puzzling data regarding its natural physiological role. PrPC is expressed in a number of tissues, including at high levels in the nervous system, especially in neurons and glial cells, and while previous studies have established a neuroprotective role, conflicting evidence for a synaptic function has revealed both reduced and enhanced long-term potentiation, and variable observations on memory, learning, and behavior. Such evidence has been confounded by the absence of an appropriate knock-out mouse model to dissect the biological relevance of PrPC, with some functions recently shown to be misattributed to PrPC due to the presence of genetic artifacts in mouse models. Here we elucidate the role of PrPC in the hippocampal circuitry and its related functions, such as learning and memory, using a recently available strictly co-isogenic Prnp0/0 mouse model (PrnpZH3/ZH3). Results We performed behavioral and operant conditioning tests to evaluate memory and learning capabilities, with results showing decreased motility, impaired operant conditioning learning, and anxiety-related behavior in PrnpZH3/ZH3 animals. We also carried in vivo electrophysiological recordings on CA3-CA1 synapses in living behaving mice and monitored spontaneous neuronal firing and network formation in primary neuronal cultures of PrnpZH3/ZH3 vs wildtype mice. PrPC absence enhanced susceptibility to high-intensity stimulations and kainate-induced seizures. However, long-term potentiation (LTP) was not enhanced in the PrnpZH3/ZH3 hippocampus. In addition, we observed a delay in neuronal maturation and network formation in PrnpZH3/ZH3 cultures. Conclusion Our results demonstrate that PrPC promotes neuronal network formation and connectivity. PrPC mediates synaptic function and protects the synapse from excitotoxic insults. Its deletion may underlie an epileptogenic-susceptible brain that fails to perform highly cognitive-demanding tasks such as associative learning and anxiety-like behaviors.

Creating and Managing EU Funded Research Networks: An Exploratory Case

The collaborative European funded research and development landscape drives competitiveness among innovative organisations. Recently it has seen the rise of public private partnerships significantly impacting the dynamics of these networks. Thus, the complexity of managing research networks has intensified with the increased diversity of research network members. Additionally, the emergence of the academic entrepreneur has augmented the focus of educational institutions to include innovation and building start-up organisations. The impact of research is scalable if an optimum research network is created and managed effectively. This paper investigates network embeddedness; the nature of relationships, links and nodes within a research network, specifically their structure, configuration and quality. The contribution of this paper extends our understanding for establishing and maintaining effective collaborative research networks. The effects of network embeddedness are recognized in the literature as pertinent to innovation and the economy. Network theory literature claims that networks are essential to innovative clusters such as Silicon valley and innovation in high tech industries. The concept of embeddedness is what differentiates network theory from economic theory. This study adopts a qualitative approach and uncovers some of the challenges of multi-disciplinary research through case study insights. One challenge is competition between network members over ownership and sharing of data. The contribution of this paper recommends the establishment of scaffolding to accommodate cooperation in research networks, role appointment, and addressing contextual complexities early to avoid problem cultivation. Furthermore, it suggests recommendations in relation to network formation, incubation and operations. The network capability is enhanced by the recognition of network theory, open innovation and social exchange with the understanding that the network structure has an impact on innovation and social exchange in research networks and subsequently on research output. The research concludes that the success of collaborative research is reliant upon establishing a common language and understanding between network members to realise their research objectives.

Dynamic Network Formation for FSO Satellite Communication

Satellite network optimization is essential, particularly since the cost of manufacturing, launching and maintaining each satellite is significant. Moreover, classical communication optimization methods, such as Minimal Spanning Tree, cannot be applied directly in dynamic scenarios where the satellite constellation is constantly changing. Motivated by the rapid growth of the Star-Link constellation that, as of Q4 2021, consists of over 1600 operational LEO satellites with thousands more expected in the coming years, this paper focuses on the problem of constructing an optimal inter-satellite (laser) communication network. More formally, given a large set of LEO satellites, each equipped with a fixed number of laser links, we direct each laser module on each satellite such that the underlying laser network will be optimal with respect to a given objective function and communication demand. In this work, we present a novel heuristic to create an optimal dynamic optical network communication using an Ant Colony algorithm. This method takes into account both the time it takes to establish an optical link (acquisition time) and the bounded number of communication links, as each satellite has a fixed amount of optical communication modules installed. Based on a large number of simulations, we conclude that, although the underlying problem of bounded-degree-spanning-tree is NP-hard (even for static cases), the suggested ant-colony heuristic is able to compute cost-efficient solutions in semi-real-time.

Epilepsy Research Now in 3D: Harnessing the Power of Brain Organoids in Epilepsy

Brain organoids represent a powerful tool for studying human neurological diseases, particularly those that affect brain growth and structure. However, many diseases manifest with clear evidence of physiological and network abnormality in the absence of anatomical changes, raising the question of whether organoids possess sufficient neural network complexity to model these conditions. Here, we explore the network-level functions of brain organoids using calcium sensor imaging and extracellular recording approaches that together reveal the existence of complex network dynamics reminiscent of intact brain preparations. We demonstrate highly abnormal and epileptiform-like activity in organoids derived from induced pluripotent stem cells from individuals with Rett syndrome, accompanied by transcriptomic differences revealed by single-cell analyses. We also rescue key physiological activities with an unconventional neuroregulatory drug, pifithrin-α. Together, these findings provide an essential foundation for the utilization of brain organoids to study intact and disordered human brain network formation and illustrate their utility in therapeutic discovery.

When community change theory meets practice: Exploring some of the challenges to information sharing networks for community change

Networked community change (NCC) efforts focus on building and supporting networks of stakeholders in communities to address complex problems, with a particular focus on tie formation among stakeholders and organizer facilitation of an information-sharing network (Lawlor & Neal, 2016). NCC approaches include, for example, systemic action research (Burns, 2007), Collective Impact (Kania & Kramer, 2011), and network action research (Foth, 2006) and can be understood as community-level interventions supporting change (Bess, 2015). Previous research demonstrates the promising nature of NCC efforts under ideal circumstances for efficient information sharing in community change efforts. However, these efforts frequently operate in non-ideal conditions, needing to adapt to a variety of community challenges. This article extends the agent-based simulation model presented in Lawlor and Neal (2016) to reflect the challenges that arise when stakeholders implement these approaches to community change and identify how they can impact information-sharing networks. First, we review literature to establish common challenges that arise in these efforts. Second, we employ the Lawlor and Neal (2016) model to examine these challenges and report on the resulting structure of the information-sharing networks that emerge from implementing them in the simulation model. We conclude with implications of common networked community change challenges on network formation and future directions for addressing these real-world challenges as communities work on complex problems.