Polysulfate hemmen durch elektrostatische Wechselwirkungen die SARS-CoV-2-Infektion

Wir zeigen, dass negativ geladene Polysulfate durch elektrostatische Wechselwirkungen an das Spike-Protein von SARS-CoV-2 binden. Durch einen Plaquereduktionstest verglichen wir die hemmende Wirkung von Heparin, Pentosanpolysulfat, linearem Polyglycerolsulfat (LPGS) und hyperverzweigtem Polyglycerolsulfat (HPGS) gegengber SARSCoV-2. Dabei ist das synthetische LPGS der vielversprechendste Inhibitor mit IC50=67 μgmL-1 (ca. 1,6 μm) und zeigt eine 60-fach hçhere virushemmende Aktivität als Heparin (IC50=4084 μgmL-1) bei zugleich deutlich geringerer gerinnungshemmender Aktivität. Außerdem konnten wir durch Moleküldynamiksimulationen bestätigen, dass LPGS stärker an das Spike-Protein bindet als Heparin selbst und dass LPGS sogar noch stärker an die Spike-Proteine der neuen N501Yund E484K-Varianten bindet. Unsere Studien belegen, dass die Aufnahme von SARS-CoV-2 in Wirtzellen über elektrostatische Wechselwirkungen blockiert werden kann. Deshalb kann LPGS als vielversprechender Prototyp für das Design weiterer neuartiger viraler Inhibitoren von SARS-CoV-2 herangezogen werden

Polysulfates block SARS-CoV-2 uptake through electrostatic interactions

Here we report that negatively charged polysulfates can bind to the spike protein of SARS-CoV-2 via electrostatic interactions. Using a plaque reduction assay, we compare inhibition of SARS-CoV-2 by heparin, pentosan sulfate, linear polyglycerol sulfate (LPGS) and hyperbranched polyglycerol sulfate (HPGS). Highly sulfated LPGS is the optimal inhibitor, with a half-maximal inhibitory concentration (IC50) of 67 μg/mL (approx.1.6 μM). This synthetic polysulfates exhibit more than 60-fold higher virus inhibitory activity than heparin (IC50: 4084μg/mL), along with much lower anticoagulant activity. Furthermore, in molecular dynamics simulations, we verified that LPGS can bind stronger to the spike protein than heparin, and that LPGS can interact even morewith the spike protein of the new N501Y and E484K variants. Our study demonstrates that the entry of SARS-CoV-2 into host cells can be blocked via electrostatic interaction, therefore LPGS can serve as a blueprint for the design of novel viral inhibitors of SARS-CoV-2

Fertility, Living Arrangements, Care and Mobility

There are four main interconnecting themes around which the contributions in this book are based. This introductory chapter aims to establish the broad context for the chapters that follow by discussing each of the themes. It does so by setting these themes within the overarching demographic challenge of the twenty-first century – demographic ageing. Each chapter is introduced in the context of the specific theme to which it primarily relates and there is a summary of the data sets used by the contributors to illustrate the wide range of cross-sectional and longitudinal data analysed

Exploring mechanisms of lipid nanoparticle-mucus interactions in healthy and cystic fibrosis conditions

Mucus forms the first defense line of human lungs, and as such hampers the efficient delivery of therapeutics to the underlying epithelium. This holds particularly true for genetic cargo such as CRISPR-based gene editing tools which cannot readily surmount the mucosal barrier. While lipid nanoparticles (LNPs) emerge as versatile non-viral gene delivery systems that can help overcome the delivery challenge, many knowledge gaps remain, especially for diseased states such as cystic fibrosis (CF). This study provides fundamental insights into Cas9 mRNA or ribonucleoprotein-loaded LNP-mucus interactions in healthy and diseased states by assessing the impact of the genetic cargo, mucin sialylation, mucin concentration, ionic strength, pH, and polyethylene glycol (PEG) concentration and nature on LNP diffusivity leveraging experimental approaches and Brownian dynamics (BD) simulations. Taken together, this study identifies key mucus and LNP characteristics that are critical to enabling a rational LNP design for transmucosal delivery

Unterstützung kommunalplanerischer Prozesse mit CityGLM-basierter Anbindung Modelica-getriebener Quartierssimulationen

Eine integrale Planung städtischer (Energie-)Systeme bedarf einer planungsbegleitenden Unterstützung durch IT-basierte Planungs- und Simulationswerkzeuge. Die durchgängige Anwendung dieser digitalen Planungshilfsmittel wird allerdings bislang insbesondere durch den sehr hohen Aufwand bei der Spezifizierung und Erfassung benötigter Datengrundlagen sowie eine mangelhafte Interoperabilität zwischen den Systemen gehemmt. Im Rahmen eines Forschungsverbundprojektes wird dieses Problemfeld mittels praxisbezogener Prozessanalysen genauer spezifiziert und die technische und fachliche Integration durch die prozessbezogene Spezifikation relevanter Informationsbedarfe sowie die Entwicklung einer darauf aufbauenden, bidirektionalen Schnittstelle auf Basis des etablierten virtuellen Stadtmodellstandards CityGML verbessert. Als exemplarisches Anwendungsszenario innerhalb kommunaler Planungsprozesse wurde die Ausweisung von Vorranggebieten der Fernwärmenutzung basierend auf einer räumlichen Analyse des Wärmebedarfs für verschiedene Entwicklungsszenarien mittels einer bidirektionalen standard-basierten Koppelung von CityGML und Modelica ausgearbeitet

The Energy Application Domain Extension for CityGML: enhancing interoperability for urban energy simulations

The road towards achievement of the climate protection goals requires, among the rest, a thorough rethinking of the energy planning tools (and policies) at all levels, from local to global. Nevertheless, it is in the cities where the largest part of energy is produced and consumed, and therefore it makes sense to focus the attention particularly on the cities as they yield great potentials in terms of energy consumption reduction and efficiency increase. As a direct consequence, a comprehensive knowledge of the demand and supply of energy resources, including their spatial distribution within urban areas, is therefore of utmost importance. Precise, integrated knowledge about 3D urban space, i.e. all urban (above and underground) features, infrastructures, their functional and semantic characteristics, and their mutual dependencies and interrelations play a relevant role for advanced simulation and analyses. As a matter of fact, what in the last years has proven to be an emerging and effective approach is the adoption of standard-based, integrated semantic 3D virtual city models, which represent an information hub for most of the abovementioned needs. In particular, being based on open standards (e.g. on the CityGML standard by the Open Geospatial Consortium), virtual city models firstly reduce the effort in terms of data preparation and provision. Secondly, they offer clear data structures, ontologies and semantics to facilitate data exchange between different domains and applications. However, a standardised and omni-comprehensive urban data model covering also the energy domain is still missing at the time of writing (January 2018). Even CityGML falls partially short when it comes to the definition of specific entities and attributes for energy-related applications. Nevertheless, and starting from the current version of CityGML (i.e. 2.0), this article describes the conception and the definition of an Energy Application Domain Extension (ADE) for CityGML. The Energy ADE is meant to offer a unique and standard-based data model to fill, on one hand, the above-mentioned gap, and, on the other hand, to allow for both detailed single-building energy simulation (based on sophisticated models for building physics and occupant behaviour) and city-wide, bottom-up energy assessments, with particular focus on the buildings sector. The overall goal is to tackle the existing data interoperability issues when dealing with energy-related applications at urban scale. The article presents the rationale behind the Energy ADE, it describes its main characteristics, the relation to other standards, and provides some examples of current applications and case studies already adopting it

SARS-CoV-2-reactive T cells in healthy donors and patients with COVID-19

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the rapidly unfolding coronavirus disease 2019 (COVID-19) pandemic1,2. Clinical manifestations of COVID-19 vary, ranging from asymptomatic infection to respiratory failure. The mechanisms that determine such variable outcomes remain unresolved. Here we investigated CD4+ T cells that are reactive against the spike glycoprotein of SARS-CoV-2 in the peripheral blood of patients with COVID-19 and SARS-CoV-2-unexposed healthy donors. We detected spike-reactive CD4+ T cells not only in 83% of patients with COVID-19 but also in 35% of healthy donors. Spike-reactive CD4+ T cells in healthy donors were primarily active against C-terminal epitopes in the spike protein, which show a higher homology to spike glycoproteins of human endemic coronaviruses, compared with N-terminal epitopes. Spike-protein-reactive T cell lines generated from SARS-CoV-2-naive healthy donors responded similarly to the C-terminal region of the spike proteins of the human endemic coronaviruses 229E and OC43, as well as that of SARS-CoV-2. This results indicate that spike-protein cross-reactive T cells are present, which were probably generated during previous encounters with endemic coronaviruses. The effect of pre-existing SARS-CoV-2 cross-reactive T cells on clinical outcomes remains to be determined in larger cohorts. However, the presence of spike-protein cross-reactive T cells in a considerable fraction of the general population may affect the dynamics of the current pandemic, and has important implications for the design and analysis of upcoming trials investigating COVID-19 vaccines