Tagungsbericht „Barocke Figuren. Zeit – Gestalt – Medien“

Typologisches Denken gerät im 17. Jahrhundert in Unordnung, wenn die Figuren des Barock, wie der Simplicissimus, nicht (länger) das erfüllen, was sie versprechen und zugleich andere Aspekte des Figurenbegriffs an Bedeutung gewinnen. An diesem Punkt setzte die Tagung „Barocke Figuren. Zeit – Gestalt – Medien“ (27.-29. Oktober 2010, Universität Konstanz) an. Sie untersuchte eben jene (atypischen) Figuren, die sich gegen eine strenge Typologisierung sperren, deren Umwege, Metamorphosen, Begegnungen und Konflikte es aber erlauben, die Frage, was im Barock eine Figur ausmacht, in begrifflich-analytischer Perspektive neu zu stellen

Surgical masks and filtering facepiece class 2 respirators (FFP2) have no major physiological effects at rest and during moderate exercise at 3000 m altitude. A randomised controlled trial

Background: During the COVID-19 pandemic, the use of face masks has been recommended or enforced in several situations, however their effects on physiological parameters and cognitive performance at high altitude are unknown. Methods: Eight healthy participants (four females) rested and exercised (cycling, 1 W/kg) while wearing no mask, a surgical mask, or a filtering facepiece class 2 respirator (FFP2), both in normoxia and hypobaric hypoxia corresponding to an altitude of 3000 m. Arterialised oxygen saturation (SaO2), partial pressure of oxygen (PaO2) and carbon dioxide (PaCO2), heart and respiratory rate, pulse oximetry (SpO2), cerebral oxygenation, visual analogue scales for dyspnoea and mask's discomfort were systematically investigated. Resting cognitive performance and exercising tympanic temperature were also assessed. Results: Mask use had a significant effect on PaCO2 (overall +1.2 ± 1.7 mmHg). There was no effect of mask use on all other investigated parameters except for dyspnoea and discomfort, which were highest with FFP2. Both masks were associated with a similar non-significant decrease in SaO2 during exercise in normoxia (-0.5% ± 0.4%) and, especially, in hypobaric hypoxia (-1.8% ± 1.5%), with similar trends for PaO2 and SpO2. Conclusions: Although mask use was associated with higher rates of dyspnoea, it had no clinically relevant impact on gas exchange at 3000 m at rest and during moderate exercise, and no detectable effect on resting cognitive performance. Wearing a surgical mask or an FFP2 can be considered safe for healthy people living, working, or spending their leisure time in mountains, high-altitude cities, or other hypobaric environments (e.g. aircrafts) up to an altitude of 3000 m

Epicardial adipose tissue dispersion at CT and recurrent atrial fibrillation after pulmonary vein isolation.

OBJECTIVES Epicardial adipose tissue (EAT) remodeling is associated with atrial fibrillation (AF). Left atrial (LA) EAT dispersion on cardiac CT is a non-invasive imaging biomarker reflecting EAT heterogeneity. We aimed to investigate the association of LA EAT dispersion with AF recurrence after pulmonary vein isolation (PVI). METHODS In a prospective registry of consecutive patients undergoing first PVI, mean EAT attenuation values were measured on contrast-enhanced cardiac CT scans in Hounsfield units (HU) within low (- 195 to - 45 HU) and high (- 44 to - 15 HU) threshold EAT compartments around the left atrium (LA). EAT dispersion was defined as the difference between the mean HU values within the two EAT compartments. Continuous variables were compared between groups using the Mann-Whitney U test and cox proportional hazard models were used to calculate hazard ratios of predictors of 1-year AF recurrence. RESULTS A total of 208 patients were included, 135 with paroxysmal AF and 73 with persistent AF. LA EAT dispersion was significantly larger in patients with persistent compared to paroxysmal AF (52.6 HU vs. 49.9 HU; p = 0.001). After 1 year of follow-up, LA EAT dispersion above the mean (> 50.8 HU) was associated with a higher risk of AF recurrence (HR 2.3, 95% CI 1.5-3.6; p < 0.001). It retained its predictive value when corrected for age, sex, body mass index, LA volume, and AF type (HR 2.8, 95% CI 1.6-4.6; p < 0.001). CONCLUSION A larger LA EAT dispersion on contrast-enhanced cardiac CT scans, reflecting EAT heterogeneity, is independently associated with AF recurrence after PVI. CLINICAL RELEVANCE STATEMENT Based on LA EAT dispersion assessment, a more accurate risk stratification and patient selection may be possible based on a pre-procedural cardiac CT when planning PVI. KEY POINTS • Epicardial adipose tissue (EAT) remodeling is associated with atrial fibrillation (AF). • A larger left atrial EAT dispersion in a pre-procedural cardiac CT was associated with a higher 1-year AF recurrence risk after pulmonary vein isolation. • A pre-procedural cardiac CT with left atrial EAT dispersion assessment may provide a more accurate risk stratification and patient selection for PVI

Differences in Atrial Remodeling in Hypertrophic Cardiomyopathy Compared to Hypertensive Heart Disease and Athletes’ Hearts.

BACKGROUND: Hypertrophic cardiomyopathy (HCM), hypertensive heart disease (HHD) and athletes' heart share an increased prevalence of atrial fibrillation. Atrial cardiomyopathy in these patients may have different characteristics and help to distinguish these conditions. METHODS: In this single-center study, we prospectively collected and analyzed electrocardiographic (12-lead ECG, signal-averaged ECG (SAECG), 24 h Holter ECG) and echocardiographic data in patients with HCM and HHD and in endurance athletes. Patients with atrial fibrillation were excluded. RESULTS: We compared data of 27 patients with HCM (70% males, mean age 50 +/- 14 years), 324 patients with HHD (52% males, mean age 75 +/- 5.5 years), and 215 endurance athletes (72% males, mean age 42 +/- 7.5 years). HCM patients had significantly longer filtered P-wave duration (153 +/- 26 ms) and PR interval (191 +/- 48 ms) compared to HHD patients (144 +/- 16 ms, p = 0.012 and 178 +/- 31, p = 0.034, respectively) and athletes (134 +/- 14 ms, p = 0.001 and 165 +/- 26 ms, both p &lt; 0.001, respectively). HCM patients had a mean of 4.9 +/- 16 premature atrial complexes per hour. Premature atrial complexes per hour were significantly more frequent in HHD patients (27 +/- 86, p &lt; 0.001), but not in athletes (2.7 +/- 23, p = 0.639). Left atrial volume index (LAVI) was 43 +/- 14 mL/m(2) in HCM patients and significantly larger than age- and sex-corrected LAVI in HHD patients 30 +/- 10 mL/m(2); p &lt; 0.001) and athletes (31 +/- 9.5 mL/m(2); p &lt; 0.001). A borderline interventricular septum thickness >/=13 mm and </=15 mm was found in 114 (35%) HHD patients, 12 (6%) athletes and 3 (11%) HCM patients. CONCLUSIONS: Structural and electrical atrial remodeling is more advanced in HCM patients compared to HHD patients and athletes

Extending Hyperspectral Imaging for Plant Phenotyping to the UV-Range

Previous plant phenotyping studies have focused on the visible (VIS, 400–700 nm), near-infrared (NIR, 700–1000 nm) and short-wave infrared (SWIR, 1000–2500 nm) range. The ultraviolet range (UV, 200–380 nm) has not yet been used in plant phenotyping even though a number of plant molecules like flavones and phenol feature absorption maxima in this range. In this study an imaging UV line scanner in the range of 250–430 nm is introduced to investigate crop plants for plant phenotyping. Observing plants in the UV-range can provide information about important changes of plant substances. To record reliable and reproducible time series results, measurement conditions were defined that exclude phototoxic effects of UV-illumination in the plant tissue. The measurement quality of the UV-camera has been assessed by comparing it to a non-imaging UV-spectrometer by measuring six different plant-based substances. Given the findings of these preliminary studies, an experiment has been defined and performed monitoring the stress response of barley leaves to salt stress. The aim was to visualize the effects of abiotic stress within the UV-range to provide new insights into the stress response of plants. Our study demonstrated the first use of a hyperspectral sensor in the UV-range for stress detection in plant phenotyping

Modelling the monthly abundance of Culicoides biting midges in nine European countries using Random Forests machine learning

Background: Culicoides biting midges transmit viruses resulting in disease in ruminants and equids such as bluetongue, Schmallenberg disease and African horse sickness. In the past decades, these diseases have led to important economic losses for farmers in Europe. Vector abundance is a key factor in determining the risk of vector-borne disease spread and it is, therefore, important to predict the abundance of Culicoides species involved in the transmission of these pathogens. The objectives of this study were to model and map the monthly abundances of Culicoides in Europe. Methods: We obtained entomological data from 904 farms in nine European countries (Spain, France, Germany, Switzerland, Austria, Poland, Denmark, Sweden and Norway) from 2007 to 2013. Using environmental and climatic predictors from satellite imagery and the machine learning technique Random Forests, we predicted the monthly average abundance at a 1 km2 resolution. We used independent test sets for validation and to assess model performance. Results: The predictive power of the resulting models varied according to month and the Culicoides species/ensembles predicted. Model performance was lower for winter months. Performance was higher for the Obsoletus ensemble, followed by the Pulicaris ensemble, while the model for Culicoides imicola showed a poor performance. Distribution and abundance patterns corresponded well with the known distributions in Europe. The Random Forests model approach was able to distinguish differences in abundance between countries but was not able to predict vector abundance at individual farm level. Conclusions: The models and maps presented here represent an initial attempt to capture large scale geographical and temporal variations in Culicoides abundance. The models are a first step towards producing abundance inputs for R0 modelling of Culicoides-borne infections at a continental scale

Monthly variation in the probability of presence of adult Culicoides populations in nine European countries and the implications for targeted surveillance

Background: Biting midges of the genus Culicoides (Diptera: Ceratopogonidae) are small hematophagous insects responsible for the transmission of bluetongue virus, Schmallenberg virus and African horse sickness virus to wild and domestic ruminants and equids. Outbreaks of these viruses have caused economic damage within the European Union. The spatio-temporal distribution of biting midges is a key factor in identifying areas with the potential for disease spread. The aim of this study was to identify and map areas of neglectable adult activity for each month in an average year. Average monthly risk maps can be used as a tool when allocating resources for surveillance and control programs within Europe. Methods : We modelled the occurrence of C. imicola and the Obsoletus and Pulicaris ensembles using existing entomological surveillance data from Spain, France, Germany, Switzerland, Austria, Denmark, Sweden, Norway and Poland. The monthly probability of each vector species and ensembles being present in Europe based on climatic and environmental input variables was estimated with the machine learning technique Random Forest. Subsequently, the monthly probability was classified into three classes: Absence, Presence and Uncertain status. These three classes are useful for mapping areas of no risk, areas of high-risk targeted for animal movement restrictions, and areas with an uncertain status that need active entomological surveillance to determine whether or not vectors are present. Results: The distribution of Culicoides species ensembles were in agreement with their previously reported distribution in Europe. The Random Forest models were very accurate in predicting the probability of presence for C. imicola (mean AUC = 0.95), less accurate for the Obsoletus ensemble (mean AUC = 0.84), while the lowest accuracy was found for the Pulicaris ensemble (mean AUC = 0.71). The most important environmental variables in the models were related to temperature and precipitation for all three groups. Conclusions: The duration periods with low or null adult activity can be derived from the associated monthly distribution maps, and it was also possible to identify and map areas with uncertain predictions. In the absence of ongoing vector surveillance, these maps can be used by veterinary authorities to classify areas as likely vector-free or as likely risk areas from southern Spain to northern Sweden with acceptable precision. The maps can also focus costly entomological surveillance to seasons and areas where the predictions and vector-free status remain uncertain

Introducing BASE: the Biomes of Australian Soil Environments soil microbial diversity database

Background: Microbial inhabitants of soils are important to ecosystem and planetary functions, yet there are large gaps in our knowledge of their diversity and ecology. The 'Biomes of Australian Soil Environments' (BASE) project has generated a database of microbial diversity with associated metadata across extensive environmental gradients at continental scale. As the characterisation of microbes rapidly expands, the BASE database provides an evolving platform for interrogating and integrating microbial diversity and function. Findings: BASE currently provides amplicon sequences and associated contextual data for over 900 sites encompassing all Australian states and territories, a wide variety of bioregions, vegetation and land-use types. Amplicons target bacteria, archaea and general and fungal-specific eukaryotes. The growing database will soon include metagenomics data. Data are provided in both raw sequence (FASTQ) and analysed OTU table formats and are accessed via the project's data portal, which provides a user-friendly search tool to quickly identify samples of interest. Processed data can be visually interrogated and intersected with other Australian diversity and environmental data using tools developed by the 'Atlas of Living Australia'. Conclusions: Developed within an open data framework, the BASE project is the first Australian soil microbial diversity database. The database will grow and link to other global efforts to explore microbial, plant, animal, and marine biodiversity. Its design and open access nature ensures that BASE will evolve as a valuable tool for documenting an often overlooked component of biodiversity and the many microbe-driven processes that are essential to sustain soil function and ecosystem services

Introducing BASE: the Biomes of Australian Soil Environments soil microbial diversity database

Microbial inhabitants of soils are important to ecosystem and planetary functions, yet there are large gaps in our knowledge of their diversity and ecology. The ‘Biomes of Australian Soil Environments’ (BASE) project has generated a database of microbial diversity with associated metadata across extensive environmental gradients at continental scale. As the characterisation of microbes rapidly expands, the BASE database provides an evolving platform for interrogating and integrating microbial diversity and function