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BackgroundPrimary neuronal cultures enable cell-biological studies of Alzheimer’s disease (AD), albeit typically non-neuron-specific. The first cortical neurons affected in AD reside in layer II of the lateralmost part of the entorhinal cortex, and they undergo early accumulation of intracellular amyloid-β, form subsequent tau pathology, and start degenerating pre-symptomatically. These vulnerable entorhinal neurons uniquely express the glycoprotein reelin and provide selective inputs to the hippocampal memory system. Gaining a more direct access to study these neurons is therefore highly relevant.New methodWe demonstrate a methodological approach for microdissection and long-term culturing of adult lateral entorhinal layer II-neurons from AD-model mice.ResultsWe maintain adult microdissected lateralmost entorhinal layer II-neurons beyond two months in culture. We show that they express neuronal markers, and that they are electrophysiologically active by 15 daysin vitroand continuing beyond 2 months.Comparison with existing methodsPrimary neurons are typically harvested from embryonic or early postnatal brains because such neurons are easier to culture compared to adult neurons. Methods to culture adult primary neurons have been reported, however, to our knowledge, culturing of adult entorhinal subregion-specific primary neurons from AD-model animals has not been reported.ConclusionsOur methodological approach offers a window to study initial pathological changes in the AD disease-cascade. This includes the study of proteinopathy, single-neuron changes, and network-level dysfunction.HighlightsWe microdissect and culture neurons from layer II of the lateralmost part of the entorhinal cortex from adult AD model mice and littermate controlsThese entorhinal neurons self-organize into networks, express reelin, NeuN and intracellular amyloid-β.The neurons are electrophysiologically active by day 15 in culture and remain viable beyond two months.

Microfluidic devices interfaced with microelectrode arrays have in recent years emerged as powerful platforms for studying and manipulatingin vitroneuronal networks at the micro- and mesoscale. By segregating neuronal populations using microchannels only permissible to axons, neuronal networks can be designed to mimic the highly organized, modular topology of neuronal assemblies in the brain. However, little is known about how the underlying topological features of such engineered neuronal networks contribute to their functional profile. To start addressing this question, a key parameter is control of afferent or efferent connectivity within the network. In this study, we show that a microfluidic device featuring axon guiding channels with geometrical constraints inspired by a Tesla valve effectively promotes unidirectional axonal outgrowth between neuronal nodes, thereby enabling us to control afferent connectivity. Our results moreover indicate that these networks exhibit a more efficient network organization with higher modularity compared to single nodal controls. We verified this by applying designer viral tools to fluorescently label the neurons to visualize the structure of the networks, combined with extracellular electrophysiological recordings using embedded nanoporous microelectrodes to study the functional dynamics of these networks during maturation. We furthermore show that electrical stimulations of the networks induce signals selectively transmitted in a feedforward fashion between the neuronal populations. A key advantage with our microdevice is the ability to longitudinally study and manipulate both the structure and function of neuronal networks with high accuracy. This model system has the potential to provide novel insights into the development, topological organization, and neuroplasticity mechanisms of neuronal assemblies at the micro- and mesoscale in healthy and perturbed conditions.

Neurons in vitro connect to each other and form neural networks that display emergent electrophysiological activity. This activity begins as spontaneous uncorrelated firing in the early phase of development, and as functional excitatory and inhibitory synapses mature, the activity typically emerges as spontaneous network bursts. Network bursts are events of coordinated global activation among many neurons interspersed with periods of silencing and are important for synaptic plasticity, neural information processing, and network computation. While bursting is the consequence of balanced excitatory-inhibitory (E/I) interactions, the functional mechanisms underlying their evolution from physiological to potentially pathophysiological states, such as decreasing or increasing in synchrony, are still poorly understood. Synaptic activity, especially that related to maturity of E/I synaptic transmission, is known to strongly influence these processes. In this study, we used selective chemogenetic inhibition to target and disrupt excitatory synaptic transmission in in vitro neural networks to study functional response and recovery of spontaneous network bursts over time. We found that over time, inhibition resulted in increases in both network burstiness and synchrony. Our results indicate that the disruption in excitatory synaptic transmission during early network development likely affected inhibitory synaptic maturity which resulted in an overall decrease in network inhibition at later stages. These findings lend support to the importance of E/I balance in maintaining physiological bursting dynamics and, conceivably, information processing capacity in neural networks.

One of the neuropathological hallmarks of Alzheimer’s disease (AD) is the accumulation of amyloid-β (Aβ) plaques, which is preceded by intraneuronal build-up of toxic, aggregated Aβ during disease progression. Aβ plaques are first deposited in the neocortex before appearing in the medial temporal lobe, and tau pathology with subsequent neurodegeneration in the latter anatomical region causes early memory impairments in patients. Current research suggests that early intraneuronal Aβ build-up may begin in superficial layers of lateral entorhinal cortex (LEC). To examine whether manipulation of neuronal activity of LEC layer II neurons affected intraneuronal Aβ levels in LEC and in downstream perforant path terminals in the hippocampus (HPC), we used a chemogenetic approach to selectively and chronically silence superficial LEC neurons in young and aged 3xTg AD mice and monitored its effect on intraneuronal Aβ levels in LEC and HPC. Chronic chemogenetic silencing of LEC neurons led to reduced early intraneuronal Aβ in LEC and in projection terminals in the HPC, compared with controls. Early intraneuronal Aβ levels in the downstream HPC correlated with activity levels in superficial layers of LEC, with the subiculum being the earliest subregion involved, and our findings give evidence to early AD neuropathology originating in select neuronal populations.

A patterned spread of proteinopathy represents a common characteristic of many neurodegenerative diseases. In Parkinson’s disease (PD), misfolded forms of alpha-synuclein proteins accumulate in hallmark pathological inclusions termed Lewy bodies and Lewy neurites. Such protein aggregates seem to affect selectively vulnerable neuronal populations in the substantia nigra and to propagate within interconnected neuronal networks. Research findings suggest that these proteinopathic inclusions are present at very early timepoints in disease development, even before clear behavioural symptoms of dysfunction arise. In this study we investigate the early pathophysiology developing after induced formation of such PDrelated alpha-synuclein inclusions, in a physiologically relevant in vitro setup using engineered human neural networks. We monitor the neural network activity using multielectrode arrays (MEAs) for a period of three weeks following proteinopathy induction to identify associated changes in network function, with a special emphasis on the measure of network criticality. Self-organised criticality represents the critical point between resilience against perturbation and adaptational flexibility, which appears to be a functional trait in self-organising neural networks, both in vitro and in vivo. We show that although developing pathology at early onset is not clearly manifest in standard measurements of network function, it may be discerned by investigating differences in network criticality states. This work was supported by The Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, NTNU; The Liaison Committee for Education, Research and Innovation in Central Norway (Samarbeidsorganet HMN, NTNU); and the SOCRATES project (NFR project agreement 270961). The TEM preparation was performed at the Cellular and Molecular Imaging Core Facility (CMIC, NTNU); The AFM and UV-vis spectroscopy were performed by Birgitte Hjelmeland McDonagh at the Norwegian Micro- and Nano-Fabrication Facility (NorFab), Norwegian University of Science and Technology (NTNU).

Although deep learning has recently increased in popularity, it suffers from various problems including high computational complexity, energy greedy computation, and lack of scalability, to mention a few. In this paper, we investigate an alternative brain-inspired method for data analysis that circumvents the deep learning drawbacks by taking the actual dynamical behavior of biological neural networks into account. For this purpose, we develop a general framework for dynamical systems that can evolve and model a variety of substrates that possess computational capacity. Therefore, dynamical systems can be exploited in the reservoir computing paradigm, i.e., an untrained recurrent nonlinear network with a trained linear readout layer. Moreover, our general framework, called EvoDynamic, is based on an optimized deep neural network library. Hence, generalization and performance can be balanced. The EvoDynamic framework contains three kinds of dynamical systems already implemented, namely cellular automata, random Boolean networks, and echo state networks. The evolution of such systems towards a dynamical behavior, called criticality, is investigated because systems with such behavior may be better suited to do useful computation. The implemented dynamical systems are stochastic and their evolution with genetic algorithm mutates their update rules or network initialization. The obtained results are promising and demonstrate that criticality is achieved. In addition to the presented results, our framework can also be utilized to evolve the dynamical systems connectivity, update and learning rules to improve the quality of the reservoir used for solving computational tasks and physical substrate modeling. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

All disease-targeting drug trials completed to date have fallen short of meeting the clinical endpoint of significantly slowing cognitive decline in Alzheimer’s disease patients. Even the recently approved drug Aducanumab, has proven effective in removing amyloid-β, but does not reduce cognitive decline. This emphasizes the urgent need for novel therapeutic approaches that could reduce several AD neuropathologies simultaneously, eventually leading to improved cognitive performance. To validate whether our mouse model replicates AD neuropathology as observed in patients, we characterized the 3xTg AD mouse model to avoid premature translation of successful results. In this study we have repurposed two FDA-approved drugs, Fasudil and Lonafarnib, targeting the Wnt signaling and endosomal-lysosomal pathway respectively, to test their potential to attenuate AD pathology. Using intracerebral microdialysis, we simultaneously infused these disease-targeting drugs between 1-2 weeks, separately and also in combination, while collecting cerebrospinal fluid. We found that Fasudil reduces intracellular amyloid-β in young, and amyloid plaques in old animals, and overall cerebrospinal fluid amyloid-β. Lonafarnib reduces tau neuropathology and cerebrospinal fluid tau biomarkers in young and old animals. Co-infusion of both drugs was more effective in reducing intracellular amyloid-β than either drug alone, and appeared to improve contextual memory performance. However, an unexpected finding was that Lonafarnib treatment increased amyloid plaque size, suggesting that activating the endosomal-lysosomal system may inadvertently increase amyloid-β pathology if administered too late in the AD continuum. Taken together, these findings lend support to the application of repurposed drugs to attenuate AD neuropathology at various therapeutic time windows.One Sentence SummaryHere we circumvented the blood-brain barrier for drug delivery aimed at attenuating AD neuropathology.

Background Preclinical models of Alzheimer's disease (AD) can provide valuable insights into the onset and progression of the disease, such as changes in concentrations of amyloid-β (Aβ) and tau in cerebrospinal fluid (CSF). However, such models are currently underutilized due to limited advancement in techniques that allow for longitudinal CSF monitoring. Objective An elegant way to understand the biochemical environment in the diseased brain is intracerebral microdialysis, a method that has until now been limited to short-term observations, or snapshots, of the brain microenvironment. Here we draw upon patient-based findings to characterize CSF biomarkers in a commonly used preclinical mouse model for AD. Methods Our modified push-pull microdialysis method was first validated ex vivo with human CSF samples, and then in vivo in an AD mouse model, permitting assessment of dynamic changes of CSF Aβ and tau and allowing for better translational understanding of CSF biomarkers. Results We demonstrate that CSF biomarker changes in preclinical models capture what is observed in the brain; with a decrease in CSF Aβ observed when plaques are deposited, and an increase in CSF tau once tau pathology is present in the brain parenchyma. We found that a high molecular weight cut-off membrane allowed for simultaneous sampling of Aβ and tau, comparable to CSF collection by lumbar puncture in patients. Conclusion Our approach can further advance AD and other neurodegenerative research by following evolving neuropathology along the disease cascade via consecutive sampling from the same animal and can additionally be used to administer pharmaceutical compounds and assess their efficacy (Bjorkli, unpublished data).

Objective Extraction of temporal features of neuronal activity from electrophysiological data can be used for accurate classification of neural networks in healthy and pathologically perturbed conditions. In this study, we provide an extensive approach for the classification of human in vitro neural networks with and without an underlying pathology, from electrophysiological recordings obtained using a microelectrode array (MEA) platform. Approach We developed a Dirichlet mixture (DM) Point Process statistical model able to extract temporal features related to neurons. We then applied a machine learning algorithm to discriminate between healthy control and pathologically perturbed in vitro neural networks. Main Results We found a high degree of separability between the classes using DM point process features (p-value

BackgroundPreclinical models of Alzheimer’s disease (AD) can provide valuable insights into the onset and progression of the disease, such as changes in concentrations of amyloid-β (Aβ) and tau in cerebrospinal fluid (CSF). However, such models are currently underutilized due to limited advancement in techniques that allow for longitudinal monitoring of CSF akin to methods employed in AD patients. An elegant way to understand the biochemical environment in the diseased brain is intracerebral microdialysis, a method that has until now been limited to short-term observations, or snapshots, of the brain microenvironment. ResultsOur novel push-pull microdialysis method in AD mice permits in vivo longitudinal monitoring of dynamic changes of Aβ and tau in CSF and allows for better translational understanding of CSF biomarkers. Specifically, we demonstrate that CSF concentrations of Aβ and tau along disease progression in transgenic mice mirror what is observed in patients, with a decrease in CSF Aβ observed when plaques are deposited, and an increase in CSF tau once tau pathology is present in the brain. We found that a high molecular weight cut-off membrane allowed for simultaneous sampling of Aβ and tau, comparable to lumbar puncture CSF collection in patients. We furthermore provide specific recommendations for optimal application of our novel microdialysis method, such as achieving optimal recovery of analytes, which depends heavily on the flow rate of perfusion, probe properties and perfusate composition. ConclusionsOur approach can further advance AD research by following evolving neuropathology along the disease cascade via consecutive sampling from the same animal, and can additionally be used to administer pharmaceutical compounds and assess their efficacy in treating AD.

Herein, we report the synthesis of differently sized gadolinium oxide nanodisks and gadolinium doped iron oxide spherical and cubic nanoparticles through the thermal decomposition of an oleate precursor. We also demonstrate that these nanoparticles are promising candidates for MR contrast agents.

A patterned spread of proteinopathy represents a common characteristic of many neurodegenerative diseases. In Parkinson’s disease (PD), misfolded forms of alpha-synuclein proteins aggregate and accumulate in hallmark pathological inclusions termed Lewy bodies and Lewy neurites, which seems to affectselectively vulnerable neuronal populations and propagate within interconnected neuronal networks. Research findings suggest that these proteinopathic inclusions are present at very early timepoints in disease development, even before strong behavioural symptoms of dysfunction arise, but that these underlying pathologies might be masked by homeostatic processes working to maintain the function of the degenerating neural circuits. This study investigates whether inducing the PD-related alpha-synuclein pathology in engineered human neural networks can be associated with changes in network function, and particularly with network criticality states. Self-organised criticality represents the critical point between resilience against perturbation and adaptational flexibility, which appears to be a functional trait in self-organising neural networks, both in vitro and in vivo. By monitoring the developing neural network activity through the use of multielectrode arrays (MEAs) for a period of three weeks following proteinopathy induction, we show that although this developing pathology is not clearly manifest in standard measurements of network function, it may be discerned by differences in network criticality states. This work was supported by The Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, NTNU; The Liaison Committee for Education, Research and Innovation in Central Norway (Samarbeidsorganet HMN, NTNU); and the SOCRATES project (NFR project agreement 270961). The TEM preparation was performed at the Cellular and Molecular Imaging Core Facility (CMIC, NTNU); The AFM and UV-vis spectroscopy were performed by Birgitte Hjelmeland McDonagh at the Norwegian Micro- and Nano-Fabrication Facility (NorFab), Norwegian University of Science and Technology (NTNU).

Dynamical systems possess a computational capacity that may be exploited in a reservoir computing paradigm. This paper presents a general representation of dynamical systems which is based on matrix multiplication. That is similar to how an artificial neural network (ANN) is represented in a deep learning library and its computation can be faster because of the optimized matrix operations that such type of libraries have. Initially, we implement the simplest dynamical system, a cellular automaton. The mathematical fundamentals behind an ANN are maintained, but the weights of the connections and the activation function are adjusted to work as an update rule in the context of cellular automata. The advantages of such implementation are its usage on specialized and optimized deep learning libraries, the capabilities to generalize it to other types of networks and the possibility to evolve cellular automata and other dynamical systems in terms of connectivity, update and learning rules. Our implementation of cellular automata constitutes an initial step towards a more general framework for dynamical systems. Our objective is to evolve such systems to optimize their usage in reservoir computing and to model physical computing substrates. Furthermore, we present promising preliminary results toward the evolution of complex behavior and criticality using genetic algorithm in stochastic elementary cellular automata. This is a post-peer-review, pre-copyedit version of a chapter. The final authenticated version is available online at: https://doi.org/10.1007/978-3-030-43722-0_9

Mutations in the LRRK2 gene have been widely linked to Parkinson ́s disease. The G2019S variant has been shown to contribute uniquely to both familial and sporadic forms of the disease. LRRK2-related mutations have been extensively studied, yet the wide variety of cellular and network events directly or indirectly related to these mutations remain poorly understood. In this study, we structured multi-nodal human neural networks carrying the G2019S mutation using custom-designed microfluidic chips coupled to microelectrode-arrays. By applying live imaging approaches, immunocytochemistry and computational modelling, we have revealed alterations in both the structure and function of the resulting neural networks when compared to controls. We provide first evidence of increased neuritic density associated with the G2019S LRRK2 mutation, while previous studies have found either a strong decrease, or no change, compared to controls. Additionally, we corroborate previous findings regarding increased baseline network activity compared to control neural networks. Furthermore, we can reveal additional network alterations attributable to the specific mutation by selectively inducing transient overexcitation to confined parts of the structured multi-nodal networks. These alterations, which we were able to capture both at the micro- and mesoscale manifested as differences in relative network activity and correlation, as well as in mitochondria activation, neuritic remodelling, and synaptic alterations. Our study thus provides important new insights into early signs of neural network pathology significantly expanding upon the current knowledge relating to the G2019S Parkinson’s disease mutation. This work was supported by The Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, NTNU; The Liaison Committee for Education, Research and Innovation in Central Norway (Samarbeidsorganet HMN, NTNU); The Joint Research Committee between St Olav’s Hospital and the Faculty of Medicine and Health Sciences, NTNU; and the Research Council of Norway, Norwegian Micro- and Nano-Fabrication Facility, NorFab, project number 245963/F50, NTNU program for Enabling Technologies, (Nanotechnology). All imaging procedures requiring the use of the EVOS2 or the Zeiss 510 META live confocal scanning microscope were performed at the Cellular and Molecular Imaging Core Facility (CMIC), Norwegian University of Science and Technology (NTNU). CMIC is funded by the Faculty of Medicine at NTNU and Central Norwegian Regional Health Authority.

In this work, we report the preliminary analysis of the electrophysiological behavior of in vitro neuronal networks to identify when the networks are in a critical state based on the size distribution of network-wide avalanches of activity. The results presented here demonstrate the importance of selecting appropriate parameters in the evaluation of the size distribution and indicate that it is possible to perturb networks showing highly synchronized---or supercritical---behavior into the critical state by increasing the level of inhibition in the network. The classification of critical versus non-critical networks is valuable in identifying networks that can be expected to perform well on computational tasks, as criticality is widely considered to be the state in which a system is best suited for computation. This type of analysis is expected to enable the identification of networks that are well-suited for computation and the classification of networks as perturbed or healthy. This study is part of a larger research project, the overarching aim of which is to develop computational models that are able to reproduce target behaviors observed in in vitro neuronal networks. These models will ultimately be used to aid in the realization of these behaviors in nanomagnet arrays to be used in novel computing hardwares., Comment: 8 pages, 3 figures, submitted to IEEE SSCI2019 ALIFE Symposium. arXiv admin note: substantial text overlap with arXiv:1907.02351

The feasibility of ex vivo expansion allows us to consider the steady-state peripheral blood as an alternative source of hematopoietic stem progenitor cells for transplantation when growth factor-induced cell mobilization is contraindicated or inapplicable. Ex vivo expansion dramatically enhances the in vivo reconstituting cell population from steady-state blood. In order to investigate phenotype and the expression of homing molecules, the expression of CD34, CD133, CD90, CD45RA, CD26 and CD9 was determined on sorted CD34+ cells according to CXCR4 (“neg”, “low” “bright”) and CD133 expression before and after ex vivo expansion. Hematopoietic stem cell activity was determined in vivo on the basis of hematopoietic repopulation of primary and secondary recipients - NSG immuno-deficient mice. In vivo reconstituting cells in the steady-state blood CD34+ cell fraction before expansion belong to the CD133+ population and are CXCR4low or, to a lesser extent, CXCR4neg, while after ex vivo expansion they are contained only in the CD133+CXCR4low cells. The failure of the CXCR4bright population to engraft is probably due to the exclusive expression of CD26 by these cells. The limiting-dilution analysis showed that both repopulating cell number and individual proliferative capacity were enhanced by ex vivo expansion. Thus, steady-state peripheral blood cells exhibit a different phenotype compared to mobilized and cord blood cells, as well as to those issued from the bone marrow. These data represent the first phenotypic characterization of steady-state blood cells exhibiting short- and long-term hematopoietic reconstituting potential, which can be expanded ex vivo, a sine qua non for their subsequent use for transplantation. Copyright © 2018 Ferrata Storti Foundation Material published in Haematologica is covered by copyright. All rights are reserved to the Ferrata Storti Foundation. Use of published material is allowed under the following terms and conditions: https://creativecommons.org/licenses/by-nc/4.0/legalcode

High post-transplantation cell mortality is the main limitation of various approaches that are aimed at improving regeneration of injured neural tissue by an injection of neural stem cells (NSCs) and mesenchymal stromal cells (MStroCs) in and/or around the lesion. Therefore, it is of paramount importance to identify efficient ways to increase cell transplant viability. We have previously proposed the "evolutionary stem cell paradigm," which explains the association between stem cell anaerobic/microaerophilic metabolic set-up and stem cell self-renewal and inhibition of differentiation. Applying these principles, we have identified the main critical point in the collection and preparation of these cells for experimental therapy: exposure of the cells to atmospheric O2, that is, to oxygen concentrations that are several times higher than the physiologically relevant ones. In this way, the primitive anaerobic cells become either inactivated or adapted, through commitment and differentiation, to highly aerobic conditions (20%-21% O2 in atmospheric air). This inadvertently compromises the cells' survival once they are transplanted into normal tissue, especially in the hypoxic/anoxic/ischemic environment, which is typical of central nervous system (CNS) lesions. In addition to the findings suggesting that stem cells can shift to glycolysis and can proliferate in anoxia, recent studies also propose that stem cells may be able to proliferate in completely anaerobic or ischemic conditions by relying on anaerobic mitochondrial respiration. In this systematic review, we propose strategies to enhance the survival of NSCs and MStroCs that are implanted in hypoxic/ischemic neural tissue by harnessing their anaerobic nature and maintaining as well as enhancing their anaerobic properties via appropriate ex vivo conditioning.

Compartmentalized microfluidic culture systems provide new perspectives in in vitro disease modelling as they enable co-culture of different relevant cell types in interconnected but fluidically isolated microenvironments. Such systems are thus particularly interesting in the context of in vitro modelling of mechanistic aspects of neurodegenerative diseases such as amyotrophic lateral sclerosis, which progressively affect the function of neuromuscular junctions, as they enable the co-culture of motor neurons and muscle cells in separate, but interconnected compartments. In combination with cell reprogramming technologies for the generation of human (including patient-specific) motor neurons, microfluidic platforms can thus become important research tools in preclinical studies. In this study, we present the application of a microfluidic chip with a differentially-perturbable microenvironment as a platform for establishing functional neuromuscular junctions using human induced pluripotent stem cell derived motor neurons and human myotubes. As a novel approach, we demonstrate the functionality of the platform using a designer pseudotyped ΔG-rabies virus for retrograde monosynaptic tracing.Graphical abstractFunctional neuromuscular junction in a microfluidic chip(a) Overview of microfluidic chip. Human iPS cell-derived motor neuron aggregates (spheroids indicated by black arrows) are seeded in the three lateral compartments of the chip, while human myotubes (white arrows) are seeded in the middle compartment.(b) Directed connectivity and retrograde virus tracing. Outgrowing axons (yellow arrow) from the motor neuron aggregate enter the directional axon tunnels (grey rectangles) and form connections with the myotubes (white arrow) within the opposite compartment. Addition of a designer monosynaptic pseudotyped ΔG-rabies virus to the myotube compartment, infects the myotubes (green) expressing an exogenous receptor (TVA) and rabies glycoprotein (G), subsequently making infectious viruses that are retrogradely transported through the motor neuron axons (green arrow) back to the neuronal cell bodies within the aggregate, validating neuromuscular junction functionality.

With development in the synthesis of shape- and size-dependent gold (Au) nanostructures (NSs) and their applications in nanomedicine, one of the biggest challenges is to understand the interaction of these shapes with cancer cells. Herein, we study the interaction of Au NSs of five different shapes with glioblastoma-astrocytoma cells. Three different shapes (nanorods, tetrahexahedra, and bipyramids), possessing tunable optical properties, have been synthesized by a single-step seed-mediated growth approach employing binary surfactant mixtures of CTAB and a secondary surfactant. By the use of two-step seed-mediated approach, we obtained new NSs, named nanomakura (Makura is a Japanese word used for pillow) which is reported for the first time here. Spherical Au nanoparticles were prepared by the Turkevich method. To study NS-cell interactions, we functionalized the NSs using thiolated PEG followed by 11-Mercaptoundecanoic acid. The influence of shape and concentration of NSs on the cytotoxicity were assessed with a LIVE/DEAD assay in glioblastoma-astrocytoma cells. Furthermore, the time-dependent uptake of nanomakura was studied with TEM. Our results indicate that unlike the other shapes studied here, the nanomakura were taken up both via receptor-mediated endocytosis and macropinocytosis. Thus, from our library of different NSs with similar surface functionality, the shape is found to be an important parameter for cellular uptake. © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/)

Neuroplasticity after ischaemic injury involves both spontaneous rewiring of neural networks and circuits as well as functional responses in neurogenic niches. These events involve complex interactions with activated microglia, which evolve in a dynamic manner over time. Although the exact mechanisms underlying these interactions remain poorly understood, increasing experimental evidence suggests a determining role of pro‐ and anti‐inflammatory microglial activation profiles in shaping both synaptogenesis and neurogenesis. While the inflammatory response of microglia was thought to be detrimental, a more complex profile of the role of microglia in tissue remodelling is emerging. Experimental evidence suggests that microglia in response to injury can rapidly modify neuronal activity and modulate synaptic function, as well as be beneficial for the proliferation and integration of neural progenitor cells (NPCs) from endogenous neurogenic niches into functional networks thereby supporting stroke recovery. The manner in which microglia contribute towards sculpting neural synapses and networks, both in terms of activity‐dependent and homeostatic plasticity, suggests that microglia‐mediated pro‐ and/or anti‐inflammatory activity may significantly contribute towards spontaneous neuronal plasticity after ischaemic lesions. In this review, we first introduce some of the key cellular and molecular mechanisms underlying neuroplasticity in stroke and then proceed to discuss the crosstalk between microglia and endogenous neuroplasticity in response to brain ischaemia with special focus on the engagement of synapses and neural networks and their implications for grey matter integrity and function in stroke repair. Locked until 22.5.2019 due to copyright restrictions. This is the peer reviewed version of an article, which has been published in final form at [https://doi.org/10.1111/ejn.13959]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.