An in vivo biosensor for neurotransmitter release and in situ receptor activity.

Tools from molecular biology, combined with in vivo optical imaging techniques, provide new mechanisms for noninvasively observing brain processes. Current approaches primarily probe cell-based variables, such as cytosolic calcium or membrane potential, but not cell-to-cell signaling. We devised cell-based neurotransmitter fluorescent engineered reporters (CNiFERs) to address this challenge and monitor in situ neurotransmitter receptor activation. CNiFERs are cultured cells that are engineered to express a chosen metabotropic receptor, use the G(q) protein-coupled receptor cascade to transform receptor activity into a rise in cytosolic [Ca(2+)] and report [Ca(2+)] with a genetically encoded fluorescent Ca(2+) sensor. The initial realization of CNiFERs detected acetylcholine release via activation of M1 muscarinic receptors. We used chronic implantation of M1-CNiFERs in frontal cortex of the adult rat to elucidate the muscarinic action of the atypical neuroleptics clozapine and olanzapine. We found that these drugs potently inhibited in situ muscarinic receptor activity

Modelling Robust Feedback Control Mechanisms That Ensure Reliable Coordination of Histone Gene Expression with DNA Replication

Funding: Andrea Christopher was supported by the University of Aberdeen through a Milner Studentship. Heike Hameister was supported by a Postgraduate Research Studentship of the University of Aberdeen. Oliver Ebenhöh was supported by the University of Aberdeen and the Deutsche Forschungsgemeinschaft [Cluster of Excellence on Plant Sciences, CEPLAS (EXC 1028)]. Berndt Müller was supported by the University of Aberdeen. Ekkehard Ullner was supported by the Scottish Universities Life Sciences Alliance (SULSA). The funders provided support in the form of salaries for authors but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section. Heike Hameister is currently employed by Merck Serono GmbH. Merck Serono GmbH did not provide any support for this work and did not have any role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. This does not alter our adherence to PLOS ONE policies on sharing data and materials.Peer reviewedPublisher PD

Characterization and Compensation of Network-Level Anomalies in Mixed-Signal Neuromorphic Modeling Platforms

Advancing the size and complexity of neural network models leads to an ever increasing demand for computational resources for their simulation. Neuromorphic devices offer a number of advantages over conventional computing architectures, such as high emulation speed or low power consumption, but this usually comes at the price of reduced configurability and precision. In this article, we investigate the consequences of several such factors that are common to neuromorphic devices, more specifically limited hardware resources, limited parameter configurability and parameter variations. Our final aim is to provide an array of methods for coping with such inevitable distortion mechanisms. As a platform for testing our proposed strategies, we use an executable system specification (ESS) of the BrainScaleS neuromorphic system, which has been designed as a universal emulation back-end for neuroscientific modeling. We address the most essential limitations of this device in detail and study their effects on three prototypical benchmark network models within a well-defined, systematic workflow. For each network model, we start by defining quantifiable functionality measures by which we then assess the effects of typical hardware-specific distortion mechanisms, both in idealized software simulations and on the ESS. For those effects that cause unacceptable deviations from the original network dynamics, we suggest generic compensation mechanisms and demonstrate their effectiveness. Both the suggested workflow and the investigated compensation mechanisms are largely back-end independent and do not require additional hardware configurability beyond the one required to emulate the benchmark networks in the first place. We hereby provide a generic methodological environment for configurable neuromorphic devices that are targeted at emulating large-scale, functional neural networks

Left, right then left again : educators at the intersection of global citizenship education, technology and academic literacies

The purpose of this article is to critically consider the roles that academic literacy facilitators fulfil in exposing students to Global Citizenship Education (GCE). In university disciplines, literacies are primary tools that students employ to interact with global events, knowledge, theories and problems. As such, multimodal literacies including written, audiovisual and cyber texts facilitate students’ access to the world through critical communication. Consequently, the authors construe GCE as disciplinary instruction that connects students to lived experiences beyond their own national borders. To demonstrate GCE, the authors employ the following methods for accessing, interpreting and generating knowledge: Firstly, a literature review is conducted. In doing so, key concepts and theories that define academic literacy and GCE are identified. Secondly, by combining reviewed literature that highlights GCE methods and scholarship pertaining to multimodal literacies, the authors make recommendations for integrating GCE into disciplines. In conclusion, the authors emphasise academic literacies, including digital discourses, as effective conduits for GCE principles and make further recommendations for future studies and methods that may be applied towards uniting literacies with international course content.https://journals.sagepub.com/home/CRChj2024Unit for Academic LiteracySDG-04:Quality Educatio

Arctic Navigation: Stakes, Benefits and Limits of the Polaris System

Ensuring safe navigation is paramount for the economic development of the Arctic. Aware of this strategic issue, the International Maritime Organization (IMO), supported by the Arctic coastal states, adopted the International Code for Ships Operating in Polar Waters (Polar Code) with a set of navigation tools including the well-known Polar Operational Limit Assessment Risk Indexing System (POLARIS). Designed for assessing operational capabilities for ships operating in ice, POLARIS is useful for various stakeholders such as the International Association of Classification Society (IACS) organizations and underwriters. Other important beneficiaries are shipowners and their crew. Even though POLARIS deals with topical issues, so far, this system has not been subjected to extensive studies of its capabilities and limitations. The aim of this analysis in hand is to assess the stakes, benefits and limits of POLARIS for Arctic navigation with a managerial approach and through the lens of risk assessment. Results show that POLARIS integrates various parameters to assess risk of navigation in ice, and that POLARIS can provide relevant managerial solutions to shipowners. Nevertheless, certain limitations remain; in particular, human factors such as the lack of crew experience or the issue of non-compliance are not taken into consideration. Finally, it is important to highlight the fact that POLARIS is not a mandatory requiremen

New low surface brightness dwarf galaxies in the Centaurus group

Context. The distribution of satellite galaxies around the Milky Way and Andromeda and their correlation in phase space pose a major challenge to the standard ΛCDM model of structure formation. Other nearby groups of galaxies are now being scrutinized to test for the ubiquity of the phenomenon. Aims. We conducted an extensive CCD imaging survey for faint, unresolved dwarf galaxies of very low surface brightness in the whole Centaurus group region, encompassing the Cen A and M 83 subgroups lying at a distance of roughly 4 and 5 Mpc, respectively. The aim is to significantly increase the sample of known Centaurus group members down to a fainter level of completeness, serving as a basis for future studies of the 3D structure of the group. Methods. Following our previous survey of 60 square degrees covering the M 83 subgroup, we extended and completed our survey of the Centaurus group region by imaging another 500 square degrees area in the g and r bands with the wide-field Dark Energy Survey camera at the 4 m Blanco telescope at CTIO. The surface brightness limit reached for unresolved dwarf galaxies is μr ≈ 29 mag arcsec-2. The faintest suspected Centaurus members found have mr ≈ 19.5 mag or Mr ≈ −8.8 mag at the mean distance of the group. The images were enhanced using different filtering techniques. Results. We found 41 new dwarf galaxy candidates, which together with the previously discovered 16 dwarf candidates in the M 83 subgroup amounts to almost a doubling of the number of known galaxies in the Centaurus complex, if the candidates are confirmed. We carried out surface photometry in g and r, and report the photometric parameters derived therefrom, for all new candidates as well as previously known members in the surveyed area. The photometric properties of the candidates, when compared to those of Local Group dwarfs and previously known Centaurus dwarfs, suggest membership in the Centaurus group. The sky distribution of the new objects is generally following a common envelope around the Cen A and M 83 subgroups. How the new dwarfs are connected to the intriguing double-planar feature recently reported must await distance information for the candidatesO.M. and B.B. are grateful to the Swiss National Science Foundation for financial support. H.J. acknowledges the support of the Australian Research Council through Discovery projects DP120100475 and DP150100862

PyNEST: A Convenient Interface to the NEST Simulator

The neural simulation tool NEST (http://www.nest-initiative.org) is a simulator for heterogeneous networks of point neurons or neurons with a small number of compartments. It aims at simulations of large neural systems with more than 104 neurons and 107 to 109 synapses. NEST is implemented in C++ and can be used on a large range of architectures from single-core laptops over multi-core desktop computers to super-computers with thousands of processor cores. Python (http://www.python.org) is a modern programming language that has recently received considerable attention in Computational Neuroscience. Python is easy to learn and has many extension modules for scientific computing (e.g. http://www.scipy.org). In this contribution we describe PyNEST, the new user interface to NEST. PyNEST combines NEST's efficient simulation kernel with the simplicity and flexibility of Python. Compared to NEST's native simulation language SLI, PyNEST makes it easier to set up simulations, generate stimuli, and analyze simulation results. We describe how PyNEST connects NEST and Python and how it is implemented. With a number of examples, we illustrate how it is used