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The German Centre for Cardiovascular Research (DZHK) is one of the German Centres for Health Research and aims to conduct early and guideline-relevant studies to develop new therapies and diagnostics that impact the lives of people with cardiovascular disease. Therefore, DZHK members designed a collaboratively organised and integrated research platform connecting all sites and partners. The overarching objectives of the research platform are the standardisation of prospective data and biological sample collections among all studies and the development of a sustainable centrally standardised storage in compliance with general legal regulations and the FAIR principles. The main elements of the DZHK infrastructure are web-based and central units for data management, LIMS, IDMS, and transfer office, embedded in a framework consisting of the DZHK Use and Access Policy, and the Ethics and Data Protection Concept. This framework is characterised by a modular design allowing a high standardisation across all studies. For studies that require even tighter criteria additional quality levels are defined. In addition, the Public Open Data strategy is an important focus of DZHK. The DZHK operates as one legal entity holding all rights of data and biological sample usage, according to the DZHK Use and Access Policy. All DZHK studies collect a basic set of data and biosamples, accompanied by specific clinical and imaging data and biobanking. The DZHK infrastructure was constructed by scientists with the focus on the needs of scientists conducting clinical studies. Through this, the DZHK enables the interdisciplinary and multiple use of data and biological samples by scientists inside and outside the DZHK. So far, 27 DZHK studies recruited well over 11,200 participants suffering from major cardiovascular disorders such as myocardial infarction or heart failure. Currently, data and samples of five DZHK studies of the DZHK Heart Bank can be applied for.
The Study of Health in Pomerania (SHIP), a population-based study from a rural state in northeastern Germany with a relatively poor life expectancy, supplemented its comprehensive examination program in 2008 with whole-body MR imaging at 1.5 T (SHIP-MR). We reviewed more than 100 publications that used the SHIP-MR data and analyzed which sequences already produced fruitful scientific outputs and which manuscripts have been referenced frequently. Upon reviewing the publications about imaging sequences, those that used T1-weighted structured imaging of the brain and a gradient-echo sequence for R2* mapping obtained the highest scientific output; regarding specific body parts examined, most scientific publications focused on MR sequences involving the brain and the (upper) abdomen. We conclude that population-based MR imaging in cohort studies should define more precise goals when allocating imaging time. In addition, quality control measures might include recording the number and impact of published work, preferably on a bi-annual basis and starting 2 years after initiation of the study. Structured teaching courses may enhance the desired output in areas that appear underrepresented.
The Madden-Julian Oscillation (MJO) is a prominent feature of the intraseasonal variability of the atmosphere. The MJO strongly modulates tropical precipitation and has implications around the globe for weather, climate and basic atmospheric research. The time-dependent state of the MJO is described by MJO indices, which are calculated through sometimes complicated statistical approaches from meteorological variables. One of these indices is the OLR-based MJO Index (OMI; OLR stands for outgoing longwave radiation). The Python package mjoindices, which is described in this paper, provides the first open source implementation of the OMI algorithm, to our knowledge. The package meets state-of-the-art criteria for sustainable research software, like automated tests and a persistent archiving to aid the reproducibility of scientific results. The agreement of the OMI values calculated with this package and the original OMI values is also summarized here. There are several reuse scenarios; the most probable one is MJO-related research based on atmospheric models, since the index values have to be recalculated for each model run.
The Madden–Julian oscillation (MJO) is a major
source of intraseasonal variability in the troposphere. Recently, studies have indicated that also the solar 27-day variability could cause variability in the troposphere. Furthermore, it has been indicated that both sources could be linked, and particularly that the occurrence of strong MJO events could be modulated by the solar 27-day cycle. In this paper, we analyze whether the temporal evolution of the MJO phases could also be linked to the solar 27-day cycle. We basically count the occurrences of particular MJO phases as a function of time lag after the solar 27-day extrema in about 38 years of MJO data. Furthermore, we develop a quantification approach to measure the strength of such a possible relationship and use this to compare the behavior
for different atmospheric conditions and different datasets, among others. The significance of the results is estimated based on different variants of the Monte Carlo approach, which are also compared. We find indications for a synchronization between the MJO phase evolution and the solar 27-day cycle, which are most notable under certain conditions: MJO events with a strength greater than 0.5, during the easterly phase of the quasi-biennial oscillation, and during boreal winter. The MJO appears to cycle through its eight phases within two solar 27-day cycles. The phase relation between the MJO and the solar variation appears to be such that the MJO predominantly transitions from phase 8 to 1 or from phase 4 and 5 during the solar 27-day minimum. These results strongly depend on the MJO index used such that the synchronization is most clearly seen when using univariate indices like the OLR-based MJO index (OMI) in the analysis but can hardly be seen with multivariate indices like the real-time multivariate MJO index (RMM). One possible explanation could be that the synchronization pattern is encoded particularly in the underlying outgoing longwave radiation (OLR) data. A weaker dependence of the results on the underlying solar proxy is also observed but not further investigated. Although we think that these initial indications are already worth noting, we do not claim to unambiguously prove this relationship in the present study, neither in a statistical nor in a causal sense. Instead, we challenge these initial findings
ourselves in detail by varying underlying datasets and methods and critically discuss resulting open questions to lay a solid foundation for further research.
This study aims to describe social network and social participation and to assess associations with depressive symptoms in older persons with increased risk for dementia in Germany. We conducted a cross-sectional observational study in primary care patients (aged 60–77) as part of a multicenter cluster-randomized controlled trial (AgeWell.de). We present descriptive and multivariate analyses for social networks (Lubben Social Network Scale and subscales) and social participation (item list of social activities) and analyze associations of these variables with depressive symptoms (Geriatric Depression Scale). Of 1030 included patients, 17.2% were at risk for social isolation (Lubben Social Network Scale < 12). Looking at the subscales, a reduced non-family network was found almost twice as often as a reduced family network. Patients with depressive symptoms had significantly smaller social networks than patients without depression (p < 0.001). They rather engaged in social activities of low involvement level or no weekly social activity at all (p < 0.001). The study shows associations of depressive symptoms with a decreased social network and less social participation in elderly participants. Sufficient non-family contacts and weekly social activities seem to play an important role in mental health and should be encouraged in elderly primary care patients.
The influence of the Madden–Julian oscillation (MJO) on the middle atmosphere (MA) and particularly on MA temperature is of interest for both the understanding of MJO-induced teleconnections and research on the variability of the MA. We analyze statistically the connection of the MJO and the MA zonal mean temperature based on observations by the Microwave Limb Sounder (MLS) satellite instrument. We consider all eight MJO phases, different seasons and the state of the quasi-biennial oscillation (QBO). We show that MA temperature anomalies are significantly related to the MJO and its temporal development. The MJO signal in the zonal mean MA temperature is characterized by a particular spatial pattern in the MA, which we link to the interhemispheric coupling (IHC) mechanism, as a major outcome of this study. The signal with the largest magnitude is found in the polar MA during boreal winter with temperature deviations on the order of ±10 K when the QBO at 50 hPa is in its easterly phase. Other atmospheric conditions and locations also exhibit temperature signals, which are, however, weaker or noisier. We also analyze the change in the temperature signal while the MJO progresses from one phase to the next. We find a gradual altitude shift in parts of the IHC pattern, which can be seen more or less clearly depending on the atmospheric conditions.
The statistical link between the MJO and the MA temperature highlights illustratively the far-reaching connections across different atmospheric layers and geographical regions in the atmosphere. Additionally, it highlights close linkages of known dynamical features of the atmosphere, particularly the MJO, the IHC, the QBO and sudden stratospheric warmings (SSWs). Because of the wide coverage of atmospheric regions and included dynamical features, the results might help to further constrain the underlying dynamical mechanisms and could be used as a benchmark for the representation of atmospheric couplings on the intraseasonal timescale in atmospheric models.
The idea of estimating stratospheric aerosol optical thickness from the twilight colours in historic paintings – particularly under conditions of volcanically enhanced stratospheric aerosol loading – is very tantalizing because it would provide information on the stratospheric aerosol loading over a period of several centuries. This idea has in fact been applied in a few studies in order to provide quantitative estimates of the aerosol optical depth after some of the major volcanic eruptions that occurred during the past 500 years. In this study we critically review this approach and come to the conclusion that the uncertainties in the estimated aerosol optical depths are so large that the values have to be considered questionable. We show that several auxiliary parameters – which are typically poorly known for historic eruptions – can have a similar effect on the red–green colour ratio as a change in optical depth typically associated with eruptions such as, for example, Tambora in 1815 or Krakatoa in 1883. Among the effects considered here, uncertainties in the aerosol particle size distribution have the largest impact on the colour ratios and hence the aerosol optical depth estimate. For solar zenith angles exceeding 80∘, uncertainties in the stratospheric ozone amount can also have a significant impact on the colour ratios. In addition, for solar zenith angles exceeding 90∘ the colour ratios exhibit a dramatic dependence on solar zenith angle, rendering the estimation of aerosol optical depth highly challenging. A quantitative determination of the aerosol optical depth may be possible for individual paintings for which all relevant parameters are sufficiently well constrained in order to reduce the related errors.
The Mt. Pinatubo eruption in 1991 had a severe impact on the Earth system, with a well-documented warming of the tropical lower stratosphere and a general cooling of the surface. This study focuses on the impact of this event on the mesosphere by analyzing solar occultation temperature data from the Halogen Occultation Experiment (HALOE) instrument on the Upper Atmosphere Research Satellite (UARS). Previous analyses of lidar temperature data found positive temperature anomalies of up to 12.9 K in the upper mesosphere that peaked in 1993 and were attributed to the Pinatubo eruption. Fitting the HALOE data according to a previously published method indicates a maximum warming of the mesosphere region of 4.1 ± 1.4 K and does not confirm significantly higher values reported for that lidar time series. An alternative fit is proposed that assumes a more rapid response of the mesosphere to the volcanic event and approximates the signature of the Pinatubo with an exponential decay function having an e-folding time of 6 months. It suggests a maximum warming of 5.4 ± 3.0 K, if the mesospheric perturbation is assumed to reach its peak 4 months after the eruption. We conclude that the HALOE time series probably captures the decay of a Pinatubo-induced mesospheric warming at the beginning of its measurement period.
Course of disease and risk factors for hospitalization in outpatients with a SARS-CoV-2 infection
(2022)
We analyzed symptoms and comorbidities as predictors of hospitalization in 710 outpatients in North-East Germany with PCR-confirmed SARS-CoV-2 infection. During the first 3 days of infection, commonly reported symptoms were fatigue (71.8%), arthralgia/myalgia (56.8%), headache (55.1%), and dry cough (51.8%). Loss of smell (anosmia), loss of taste (ageusia), dyspnea, and productive cough were reported with an onset of 4 days. Anosmia or ageusia were reported by only 18% of the participants at day one, but up to 49% between days 7 and 9. Not all participants who reported ageusia also reported anosmia. Individuals suffering from ageusia without anosmia were at highest risk of hospitalization (OR 6.8, 95% CI 2.5–18.1). They also experienced more commonly dyspnea and nausea (OR of 3.0, 2.9, respectively) suggesting pathophysiological connections between these symptoms. Other symptoms significantly associated with increased risk of hospitalization were dyspnea, vomiting, and fever. Among basic parameters and comorbidities, age > 60 years, COPD, prior stroke, diabetes, kidney and cardiac diseases were also associated with increased risk of hospitalization. In conclusion, due to the delayed onset, ageusia and anosmia may be of limited use in differential diagnosis of SARS-CoV-2. However, differentiation between ageusia and anosmia may be useful for evaluating risk for hospitalization.