Teachers' emotional well-being during the SARS-CoV-2 pandemic with long school closures: a large-scale cross-sectional survey in Northern Italy

Objectives: This study aimed to evaluate the magnitude of emotional burden on teaching staff during the SARS-CoV-2 pandemic in a significantly impacted region. In addition, the correlates of emotional burden were analysed to enable the design of targeted interventions. Study design: This study was a cross-sectional survey. Methods: An electronic survey was administered to the teaching staff at public schools and kindergartens in a specific geographical area. Cross-sectional assessments of pandemic-specific variables were performed using the Pandemic Fatigue Scale, the Depression Anxiety Stress Scale (DASS)-21, the Satisfaction with Life Scale, and the Resilient Coping Scale. DASS-21 results were compared with results from a parallel survey that was representative of the local general population. Results: In total, 3251 teaching staff members participated in the survey. Teachers showed a higher emotional burden for depression, anxiety and stress than the general population during the pandemic. According to a linear regression model, this burden is correlated with the language in which the questionnaires were answered, mistrust towards institutions, specific SARS-CoV-2 anxiety, past infection with SARS-CoV-2, avoidance of information about the pandemic and pandemic fatigue; emotional burden was negatively correlated with measures for life satisfaction, resilience and team atmosphere. Some independent variables were shown to contribute differentially to the variance of depression, anxiety or stress. Conclusions: Emotional distress during the pandemic among teachers is higher than in the general population and correlates with variables that could, at least in principle, be targeted for specific interventions

Earth system modeling with endogenous and dynamic human societies: the copan:CORE open World-Earth modeling framework

Analysis of Earth system dynamics in the Anthropocene requires explicitly taking into account the increasing magnitude of processes operating in human societies, their cultures, economies and technosphere and their growing feedback entanglement with those in the physical, chemical and biological systems of the planet. However, current state-of-the-art Earth system models do not represent dynamic human societies and their feedback interactions with the biogeophysical Earth system and macroeconomic integrated assessment models typically do so only with limited scope. This paper (i) proposes design principles for constructing world-Earth models (WEMs) for Earth system analysis of the Anthropocene, i.e., models of social (world)-ecological (Earth) coevolution on up to planetary scales, and (ii) presents the copan:CORE open simulation modeling framework for developing, composing and analyzing such WEMs based on the proposed principles. The framework provides a modular structure to flexibly construct and study WEMs. These can contain biophysical (e.g., carbon cycle dynamics), socio-metabolic or economic (e.g., economic growth or energy system changes), and sociocultural processes (e.g., voting on climate policies or changing social norms) and their feedback interactions, and they are based on elementary entity types, e.g., grid cells and social systems. Thereby, copan:CORE enables the epistemic flexibility needed for contributions towards Earth system analysis of the Anthropocene given the large diversity of competing theories and methodologies used for describing socio-metabolic or economic and sociocultural processes in the Earth system by various fields and schools of thought. To illustrate the capabilities of the framework, we present an exemplary and highly stylized WEM implemented in copan:CORE that illustrates how endogenizing sociocultural processes and feedbacks such as voting on climate policies based on socially learned environmental awareness could fundamentally change macroscopic model outcomes

Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package

We introduce the \texttt{pyunicorn} (Pythonic unified complex network and recurrence analysis toolbox) open source software package for applying and combining modern methods of data analysis and modeling from complex network theory and nonlinear time series analysis. \texttt{pyunicorn} is a fully object-oriented and easily parallelizable package written in the language Python. It allows for the construction of functional networks such as climate networks in climatology or functional brain networks in neuroscience representing the structure of statistical interrelationships in large data sets of time series and, subsequently, investigating this structure using advanced methods of complex network theory such as measures and models for spatial networks, networks of interacting networks, node-weighted statistics or network surrogates. Additionally, \texttt{pyunicorn} provides insights into the nonlinear dynamics of complex systems as recorded in uni- and multivariate time series from a non-traditional perspective by means of recurrence quantification analysis (RQA), recurrence networks, visibility graphs and construction of surrogate time series. The range of possible applications of the library is outlined, drawing on several examples mainly from the field of climatology.Comment: 28 pages, 17 figure

Earth system modeling with endogenous and dynamic human societies: the copan:CORE open World-Earth modeling framework

Analysis of Earth system dynamics in the Anthropocene requires to explicitly take into account the increasing magnitude of processes operating in human societies, their cultures, economies and technosphere and their growing feedback entanglement with those in the physical, chemical and biological systems of the planet. However, current state-of-the-art Earth System Models do not represent dynamic human societies and their feedback interactions with the biogeophysical Earth system and macroeconomic Integrated Assessment Models typically do so only with limited scope. This paper (i) proposes design principles for constructing World-Earth Models (WEM) for Earth system analysis of the Anthropocene, i.e., models of social (World) - ecological (Earth) co-evolution on up to planetary scales, and (ii) presents the copan:CORE open simulation modeling framework for developing, composing and analyzing such WEMs based on the proposed principles. The framework provides a modular structure to flexibly construct and study WEMs. These can contain biophysical (e.g. carbon cycle dynamics), socio-metabolic/economic (e.g. economic growth) and socio-cultural processes (e.g. voting on climate policies or changing social norms) and their feedback interactions, and are based on elementary entity types, e.g., grid cells and social systems. Thereby, copan:CORE enables the epistemic flexibility needed for contributions towards Earth system analysis of the Anthropocene given the large diversity of competing theories and methodologies used for describing socio-metabolic/economic and socio-cultural processes in the Earth system by various fields and schools of thought. To illustrate the capabilities of the framework, we present an exemplary and highly stylized WEM implemented in copan:CORE that illustrates how endogenizing socio-cultural processes and feedbacks could fundamentally change macroscopic model outcomes

Quark-Gluon Matter

A concise review of the experimental and phenomenological progress in high-energy heavy-ion physics over the past few years is presented. Emphasis is put on measurements at BNL-RHIC and CERN-SPS which provide information on fundamental properties of QCD matter at extreme values of temperature, density and low-x. The new opportunities accessible at the LHC, which may help clarify some of the current open issues, are also outlined.Comment: Minor changes to text. New refs. included. Updated figures with final dat

Stem Cell Mediation of Functional Recovery after Stroke in the Rat

This is an open-access article distributed under the terms of the Creative Commons Attribution License.[Background]: Regenerative strategies of stem cell grafting have been demonstrated to be effective in animal models of stroke. In those studies, the effectiveness of stem cells promoting functional recovery was assessed by behavioral testing. These behavioral studies do, however, not provide access to the understanding of the mechanisms underlying the observed functional outcome improvement. [Methodology/Principal Findings]: In order to address the underlying mechanisms of stem cell mediated functional improvement, this functional improvement after stroke in the rat was investigated for six months after stroke by use of fMRI, somatosensory evoked potentials by electrophysiology, and sensorimotor behavior testing. Stem cells were grafted ipsilateral to the ischemic lesion. Rigorous exclusion of spontaneous recovery as confounding factor permitted to observe graft-related functional improvement beginning after 7 weeks and continuously increasing during the 6-month observation period. The major findings were i) functional improvement causally related to the stem cells grafting; ii) tissue replacement can be excluded as dominant factor for stem cell mediated functional improvement; iii) functional improvement occurs by exclusive restitution of the function in the original representation field, without clear contributions from reorganization processes, and iv) stem cells were not detectable any longer after six months. [Conclusions/Significance]: A delayed functional improvement due to stem cell implantation has been documented by electrophysiology, fMRI and behavioral testing. This functional improvement occurred without cells acting as a tissue replacement for the necrotic tissue after the ischemic event. Combination of disappearance of grafted cells after six months on histological sections with persistent functional recovery was interpreted as paracrine effects by the grafted stem cells being the dominant mechanism of cell activity underlying the observed functional restitution of the original activation sites. Future studies will have to investigate whether the stem cell mediated improvement reactivates the original representation target field by using original connectivity pathways or by generating/activating new ones for the stimulus.Financial support from the Hertie Foundation (Germany), and EU grants of the FP-6: DiMI (LSHB-CT-2005-512146), EMIL (LSHC-CT-2004-503569) and Stem Stroke (LSHB-CT-2006-037526) are gratefully acknowledged.Peer Reviewe

Genome-wide association analysis and fine mapping of NT-proBNP level provide novel insight into the role of the MTHFR-CLCN6-NPPA-NPPB gene cluster

High blood concentration of the N-terminal cleavage product of the B-type natriuretic peptide (NT-proBNP) is strongly associated with cardiac dysfunction and is increasingly used for heart failure diagnosis. To identify genetic variants associated with NT-proBNP level, we performed a genome-wide association analysis in 1325 individuals from South Tyrol, Italy, and followed up the most significant results in 1746 individuals from two German population-based studies. A genome-wide significant signal in the MTHFR-CLCN6-NPPA-NPPB gene cluster was replicated, after correction for multiple testing (replication one-sided P-value = 8.4 × 10−10). A conditional regression analysis of 128 single-nucleotide polymorphisms in the region of interest identified novel variants in the CLCN6 gene as independently associated with NT-proBNP. In this locus, four haplotypes were associated with increased NT-proBNP levels (haplotype-specific combined P-values from 8.3 × 10−03 to 9.3 × 10−11). The observed increase in the NT-proBNP level was proportional to the number of haplotype copies present (i.e. dosage effect), with an increase associated with two copies that varied between 20 and 100 pg/ml across populations. The identification of novel variants in the MTHFR-CLCN6-NPPA-NPPB cluster provides new insights into the biological mechanisms of cardiac dysfunction