Leibniz University of Hanover

About: Leibniz University of Hanover is a education organization based out in Hanover, Niedersachsen, Germany. It is known for research contribution in the topics: Finite element method & Computer science. The organization has 14283 authors who have published 29845 publications receiving 682152 citations.

Iron-regulatory proteins secure iron availability in cardiomyocytes to prevent heart failure.

Abstract: Aims Iron deficiency (ID) is associated with adverse outcomes in heart failure (HF) but the underlying mechanisms are incompletely understood. Intracellular iron availability is secured by two mRNA-binding iron-regulatory proteins (IRPs), IRP1 and IRP2. We generated mice with a cardiomyocyte-targeted deletion of Irp1 and Irp2 to explore the functional implications of ID in the heart independent of systemic ID and anaemia. Methods and results Iron content in cardiomyocytes was reduced in Irp-targeted mice. The animals were not anaemic and did not show a phenotype under baseline conditions. Irp-targeted mice, however, were unable to increase left ventricular (LV) systolic function in response to an acute dobutamine challenge. After myocardial infarction, Irp-targeted mice developed more severe LV dysfunction with increased HF mortality. Mechanistically, the activity of the iron-sulphur cluster-containing complex I of the mitochondrial electron transport chain was reduced in left ventricles from Irp-targeted mice. As demonstrated by extracellular flux analysis in vitro, mitochondrial respiration was preserved at baseline but failed to increase in response to dobutamine in Irp-targeted cardiomyocytes. As shown by 31P-magnetic resonance spectroscopy in vivo, LV phosphocreatine/ATP ratio declined during dobutamine stress in Irp-targeted mice but remained stable in control mice. Intravenous injection of ferric carboxymaltose replenished cardiac iron stores, restored mitochondrial respiratory capacity and inotropic reserve, and attenuated adverse remodelling after myocardial infarction in Irp-targeted mice but not in control mice. As shown by electrophoretic mobility shift assays, IRP activity was significantly reduced in LV tissue samples from patients with advanced HF and reduced LV tissue iron content. Conclusions ID in cardiomyocytes impairs mitochondrial respiration and adaptation to acute and chronic increases in workload. Iron supplementation restores cardiac energy reserve and function in iron-deficient hearts.

Face masks: benefits and risks during the COVID-19 crisis.

Abstract: The German government has made it mandatory to wear respiratory masks covering mouth and nose (MNC) as an effective strategy to fight SARS-CoV-2 infections. In many countries, this directive has been extended on shopping malls or public transportation. The aim of this paper is to critically analyze the statutory regulation to wear protective masks during the COVID-19 crisis from a medical standpoint. We performed an extensive query of the most recent publications addressing the prevention of viral infections including the use of face masks in the community as a method to prevent the spread of the infection. We addressed the issues of practicability, professional use, and acceptability based on the community and the environment where the user resided. Upon our critical review of the available literature, we found only weak evidence for wearing a face mask as an efficient hygienic tool to prevent the spread of a viral infection. However, the use of MNC seems to be linked to relevant protection during close contact scenarios by limiting pathogen-containing aerosol and liquid droplet dissemination. Importantly, we found evidence for significant respiratory compromise in patients with severe obstructive pulmonary disease, secondary to the development of hypercapnia. This could also happen in patients with lung infections, with or without SARS-CoV-2. Epidemiologists currently emphasize that wearing MNC will effectively interrupt airborne infections in the community. The government and the politicians have followed these recommendations and used them to both advise and, in some cases, mandate the general population to wear MNC in public locations. Overall, the results seem to suggest that there are some clinically relevant scenarios where the use of MNC necessitates more defined recommendations. Our critical evaluation of the literature both highlights the protective effects of certain types of face masks in defined risk groups, and emphasizes their potential risks.

Transmission Electron Microscopy Study of Ba0.5Sr0.5Co0.8Fe0.2O3−δ Perovskite Decomposition at Intermediate Temperatures

Abstract: The cubic perovskite Ba0.5Sr0.5Co0.8Fe0.2O3−δ (denoted BSCF) is the state-of-the-art ceramic membrane material used for oxygen separation technologies above 1150 K. BSCF is a mixed oxygen-ion and electron conductor (MIEC) and exhibits one of the highest oxygen permeabilities reported so far for dense oxides. Additionally, it has excellent phase stability above 1150 K. In the intermediate temperature range (750−1100 K), however, BSCF suffers from a slow decomposition of the cubic perovskite into variants with hexagonal stacking that are barriers to oxygen transport. To elucidate details of the decomposition process, both sintered BSCF ceramic and powder were annealed for 180−240 h in ambient air at temperatures below 1123 K and analyzed by different transmission electron microscopy techniques. Aside from hexagonal perovskite Ba0.6Sr0.4CoO3−δ, the formation of lamellar noncubic phases was observed in the quenched samples. The structure of the lamellae with the previously unknown composition Ba1−xSrxCo2−yFey...

Introduction to the special section on twitter and microblogging services

Abstract: Welcome to this special section on Twitter and Microblogging Services, which features five articles on different aspects of microblogging and related topics. We are putting forward this special section because, in recent years, we have witnessed a dramatic increase in the amount of research done on Twitter and other microblogging services, and we believe that a special journal section on this topic is timely and will serve our community well. The special section comes out with high-quality selected articles that were originally presented in various top international conferences. These articles have been expanded and extended with more detailed contents from the authors to ensure a deeper understanding of their respective work. A brief introduction of the five articles follows. A Content-Driven Framework for Geolocating Microblog Users by Zhiyuan Cheng, James Caverlee, and Kyumin Lee investigates the use of a probabilistic framework for estimating a microblogger’s location based on the content of the microblog. The framework has to overcome the geodata sparsity problem and is capable of estimating the user’s location within a radius. The second article is Named Entity Recognition for Tweets by Xiaohua Liu, Furu Wei, Shaodian Zhang, and Ming Zhou. Named Entity Recognition (NER) is an active and challenging research topic in microblogging due to insufficient content and lack of training data. This article proposes a combination of machine learning techniques to tackle this problem with good and effective results. In the third article, Improving Recency Ranking Using Twitter Data, Yi Chang, Anlei Dong, Pranam Kolari, Ruiqiang Zhang, Yoshiyuki Inagaki, Fernando Diaz, Hongyuan Zha, and Yan Liu examine the use of Recency ranking, which incorporates relevancy and freshness in overcoming the lack of in-links and click information issue. Their approach utilizes Twitter TinyURL to detect fresh and high-quality tweets for generating ranking. Lexical Normalization for Social Media Text by Bo Han, Paul Cook, and Timothy Baldwin targets out-of-vocabulary words in tweets in order to tackle word noise in brief messages. Based on morphophonemic similarity, their approach detects lexical variants in order to generate the correct candidates for correcting words. The final article is Reorder User’s Tweets by Keyi Shen, Jianmin Wu, Ya Zhang, Yiping Han, Xiaokang Yang, Li Song, and Xiao Gu. Typically microblogs are displayed in a reversed chronological order. This article proposes a supervised learning method for personalized tweens reordering based on users’ preferences and interests by minimizing the pairwise loss of relevant and irrelevant tweets. The guest editors would like to thank all the authors and the reviewers for their contributions to this special section. Special thanks go to Weike Pan and Xiaofeng Yu for their administrative assistances. Finally, we would like to thank ACM TIST and

The Stata command felsdvreg to fit a linear model with two high-dimensional fixed effects

Abstract: This article proposes a memory-saving decomposition of the design matrix to facilitate the estimation of a linear model with two high-dimensional fixed effects. A common way to fit such a model is to take into account one of the effects by including dummy variables and to sweep out the other effect by the within transformation (fixed-effects transformation). If the number of panel units is high, creating and storing the dummy variables can involve prohibitively large computer-memory requirements. The memory-saving procedure to set up the moment matrices for estimation presented in this article can reduce the memory requirements considerably. The companion Stata ado-file felsdvreg implements the estimation method, takes care of identification issues, and provides useful summary statistics.