Vergleichbarkeit von ergebnisorientiertem Pflegeassessment (ePA_AC) und Erweitertem Barthel Index (EBI)

Ziel: In der neurologischen Rehabilitationspflege der Schweiz kommt es, durch die Verwendung des EBI und des ePA_AC zur Erhebung der ATL’s beim Eintritt, zur Verlaufskontrolle und beim Austritt, zu erheblichen Doppelspurigkeiten, welche weder zeitlich noch inhaltlich sinnvoll erscheinen. Daher sollte mit dieser Untersuchung geprüft werden, ob sich der EBI Score aus dem ePA_AC, generieren lässt. Methode: In einer retrospektiven Studie wurden 220 anonymisierte Patientendaten zu ePA_AC und EBI beim Eintritt und beim Austritt untersucht. Zur Vorbereitung der statistischen Analyse wurde eine Itemanalyse und Reduktion der Anzahl Items durchgeführt und es wurden Konstrukte gebildet. Mit einer linearen Regressionsanalyse wurde geprüft, wie gut sich die Werte der Merkmale von ePA_AC durch die Werte der Merkmale von EBI vorhersagen lassen. Ergebnisse: Die Analyse zeigte, dass sich der EBI Score aus dem ePA_AC generieren lässt. In 9 von 10 Modellen, konnte die Varianz gut bis sehr gut erklärt werden. Die erklärte Varianz beim Messpunkt T0 lag zwischen 18,9% und 75,5%, beim Messpunkt T3 zwischen 14,1% und 84,6%. Die Effektstärken lagen zwischen 0,233 und 3,082 (Zeitpunkt T0) und zwischen 0,164 und 5,494 (Zeitpunkt T3). Das Modell mit dem Gesamtscore des ePA_AC (SPI) als abhängige Variable und dem Gesamtscore des EBI (Total EBI) als unabhängige Variable für den Zeitpunkt T0 war signifikant. Das Modell klärt 80,9% der Varianz. Das Modell für den Zeitpunkt T3 konnte nicht befriedigend geschätzt werden. Fazit: In der Praxis kann auf den EBI zugunsten des ePA_AC verzichtet werden. Allerdings kann der Selbstpflegeindex (SPI), generiert vom ePA_AC, nicht mit dem EBI Gesamtscore verglichen werden. Dies erfordert eine Berechnung mittels eines Algorithmus aus den 10 Konstrukten. Dies ist jedoch mit einem kleineren Aufwand verbunden als die Durchführung beider Instrumente bei den gleichen Patienten

Effects of orally administered fumonisin B1 (FB1), partially hydrolysed FB1, hydrolysed FB1 and N-(1-deoxy-D-fructos-1-yl) FB1 on the sphingolipid metabolism in rats

Fumonisin B1 (FB1) is a Fusarium mycotoxin frequently occurring in maize-based food and feed. Alkaline processing like nixtamalisation of maize generates partially and fully hydrolysed FB1 (pHFB1 and HFB1) and thermal treatment in the presence of reducing sugars leads to formation of N-(1-deoxy-D-fructos- 1-yl) fumonisin B1 (NDF). The toxicity of these metabolites, in particular their effect on the sphingolipid metabolism, is either unknown or discussed controversially.We produced high purity FB1, pHFB1a+b, HFB1 and NDF and fed them to male Sprague Dawley rats for three weeks. Once a week, urine and faeces samples were collected over 24 h and analysed for fumonisin metabolites as well as for the sphinganine (Sa) to sphingosine (So) ratio by validated LC–MS/MS based methods. While the latter was significantly increased in the FB1 positive control group, the Sa/So ratios of the partially and fully hydrolysed fumonisins were indifferent from the negative control group. Although NDF was partly cleaved during digestion, the liberated amounts of FB1 did not raise the Sa/So ratio. These results show that the investigated alkaline and thermal processing products of FB1 were, at the tested concentrations, non-toxic for rats, and suggest that according food processing can reduce fumonisin toxicity for humans

Exuberant fibroblast activity compromises lung function via ADAMTS4

© 2020, The Author(s), under exclusive licence to Springer Nature Limited. Severe respiratory infections can result in acute respiratory distress syndrome (ARDS)1. There are no effective pharmacological therapies that have been shown to improve outcomes for patients with ARDS. Although the host inflammatory response limits spread of and eventually clears the pathogen, immunopathology is a major contributor to tissue damage and ARDS1,2. Here we demonstrate that respiratory viral infection induces distinct fibroblast activation states, which we term extracellular matrix (ECM)-synthesizing, damage-responsive and interferon-responsive states. We provide evidence that excess activity of damage-responsive lung fibroblasts drives lethal immunopathology during severe influenza virus infection. By producing ECM-remodelling enzymes—in particular the ECM protease ADAMTS4—and inflammatory cytokines, damage-responsive fibroblasts modify the lung microenvironment to promote robust immune cell infiltration at the expense of lung function. In three cohorts of human participants, the levels of ADAMTS4 in the lower respiratory tract were associated with the severity of infection with seasonal or avian influenza virus. A therapeutic agent that targets the ECM protease activity of damage-responsive lung fibroblasts could provide a promising approach to preserving lung function and improving clinical outcomes following severe respiratory infections

Publisher Correction: Exuberant fibroblast activity compromises lung function via ADAMTS4 (Nature, (2020), 587, 7834, (466-471), 10.1038/s41586-020-2877-5)

© 2020, The Author(s), under exclusive licence to Springer Nature Limited. An amendment to this paper has been published and can be accessed via a link at the top of the paper

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Overview: On the transport and transformation of pollutants in the outflow of major population centres – observational data from the EMeRGe European intensive operational period in summer 2017

Megacities and other major population centres (MPCs) worldwide are major sources of air pollution, both locally as well as downwind. The overall assessment and prediction of the impact of MPC pollution on tropospheric chemistry are challenging. The present work provides an overview of the highlights of a major new contribution to the understanding of this issue based on the data and analysis of the EMeRGe (Effect of Megacities on the transport and transformation of pollutants on the Regional to Global scales) international project. EMeRGe focuses on atmospheric chemistry, dynamics, and transport of local and regional pollution originating in MPCs. Airborne measurements, taking advantage of the long range capabilities of the High Altitude and LOng Range Research Aircraft (HALO, https://www.halo-spp.de, last access: 22 March 2022), are a central part of the project. The synergistic use and consistent interpretation of observational data sets of different spatial and temporal resolution (e.g. from ground-based networks, airborne campaigns, and satellite measurements) supported by modelling within EMeRGe provide unique insight to test the current understanding of MPC pollution outflows. In order to obtain an adequate set of measurements at different spatial scales, two field experiments were positioned in time and space to contrast situations when the photochemical transformation of plumes emerging from MPCs is large. These experiments were conducted in summer 2017 over Europe and in the inter-monsoon period over Asia in spring 2018. The intensive observational periods (IOPs) involved HALO airborne measurements of ozone and its precursors, volatile organic compounds, aerosol particles, and related species as well as coordinated ground-based ancillary observations at different sites. Perfluorocarbon (PFC) tracer releases and model forecasts supported the flight planning, the identification of pollution plumes, and the analysis of chemical transformations during transport. This paper describes the experimental deployment and scientific questions of the IOP in Europe. The MPC targets – London (United Kingdom; UK), the Benelux/Ruhr area (Belgium, the Netherlands, Luxembourg and Germany), Paris (France), Rome and the Po Valley (Italy), and Madrid and Barcelona (Spain) – were investigated during seven HALO research flights with an aircraft base in Germany for a total of 53 flight hours. An in-flight comparison of HALO with the collaborating UK-airborne platform Facility for Airborne Atmospheric Measurements (FAAM) took place to assure accuracy and comparability of the instrumentation on board. Overall, EMeRGe unites measurements of near- and far-field emissions and hence deals with complex air masses of local and distant sources. Regional transport of several European MPC outflows was successfully identified and measured. Chemical processing of the MPC emissions was inferred from airborne observations of primary and secondary pollutants and the ratios between species having different chemical lifetimes. Photochemical processing of aerosol and secondary formation or organic acids was evident during the transport of MPC plumes. Urban plumes mix efficiently with natural sources as mineral dust and with biomass burning emissions from vegetation and forest fires. This confirms the importance of wildland fire emissions in Europe and indicates an important but discontinuous contribution to the European emission budget that might be of relevance in the design of efficient mitigation strategies. The present work provides an overview of the most salient results in the European context, with these being addressed in more detail within additional dedicated EMeRGe studies. The deployment and results obtained in Asia will be the subject of separate publications

Physical, emotional and sexual adolescent abuse victimisation in South Africa:Prevalence, incidence, perpetrators and locations

Background: Physical, emotional and sexual abuse of children is a major problem in South Africa, with severe negative outcomes for survivors. To date, no known studies have used data directly obtained from community-based samples of children to investigate prevalence, incidence, locations and perpetrators of child abuse victimisation. This study aims to investigate prevalence and incidence, perpetrators, and locations of child abuse victimisation in South Africa using a multicommunity sample. Methods: 3515 children aged 10-17 years (56.6% female) were interviewed from all households in randomly selected census enumeration areas in two South African provinces. Child self-report questionnaires were completed at baseline and at 1-year follow-up (96.7% retention). Results: Prevalence was 56.3% for lifetime physical abuse (18.2% past-year incidence), 35.5% for lifetime emotional abuse (12.1% incidence) and 9% for lifetime sexual abuse (5.3% incidence). 68.9% of children reported any type of lifetime victimisation and 27.1% reported lifetime multiple abuse victimisation. Main perpetrators of abuse were reported: for physical abuse, primary caregivers and teachers; for emotional abuse, primary caregivers and relatives; and for sexual abuse, girlfriend/boyfriends or other peers. Conclusions: This is the first study assessing current self-reported child abuse through a large, community based sample in South Africa. Findings of high rates of physical, emotional and sexual abuse demonstrate the need for targeted and effective interventions to prevent incidence and re-victimisation

The TESS Grand Unified Hot Jupiter Survey. II. Twenty New Giant Planets

NASA's Transiting Exoplanet Survey Satellite (TESS) mission promises to improve our understanding of hot Jupiters by providing an all-sky, magnitude-limited sample of transiting hot Jupiters suitable for population studies. Assembling such a sample requires confirming hundreds of planet candidates with additional follow-up observations. Here, we present twenty hot Jupiters that were detected using TESS data and confirmed to be planets through photometric, spectroscopic, and imaging observations coordinated by the TESS Follow-up Observing Program (TFOP). These twenty planets have orbital periods shorter than 7 days and orbit relatively bright FGK stars ($10.9 < G < 13.0$). Most of the planets are comparable in mass to Jupiter, although there are four planets with masses less than that of Saturn. TOI-3976 b, the longest period planet in our sample ($P = 6.6$ days), may be on a moderately eccentric orbit ($e = 0.18\pm0.06$), while observations of the other targets are consistent with them being on circular orbits. We measured the projected stellar obliquity of TOI-1937A b, a hot Jupiter on a 22.4 hour orbit with the Rossiter-McLaughlin effect, finding the planet's orbit to be well-aligned with the stellar spin axis ($|\lambda| = 4.0\pm3.5^\circ$). We also investigated the possibility that TOI-1937 is a member of the NGC 2516 open cluster, but ultimately found the evidence for cluster membership to be ambiguous. These objects are part of a larger effort to build a complete sample of hot Jupiters to be used for future demographic and detailed characterization work.Comment: 67 pages, 11 tables, 13 figures, 2 figure sets. Resubmitted to ApJS after revision

The cross-sectional GRAS sample: A comprehensive phenotypical data collection of schizophrenic patients

<p>Abstract</p> <p>Background</p> <p>Schizophrenia is the collective term for an exclusively clinically diagnosed, heterogeneous group of mental disorders with still obscure biological roots. Based on the assumption that valuable information about relevant genetic and environmental disease mechanisms can be obtained by association studies on patient cohorts of ≥ 1000 patients, if performed on detailed clinical datasets and quantifiable biological readouts, we generated a new schizophrenia data base, the GRAS (Göttingen Research Association for Schizophrenia) data collection. GRAS is the necessary ground to study genetic causes of the schizophrenic phenotype in a 'phenotype-based genetic association study' (PGAS). This approach is different from and complementary to the genome-wide association studies (GWAS) on schizophrenia.</p> <p>Methods</p> <p>For this purpose, 1085 patients were recruited between 2005 and 2010 by an invariable team of traveling investigators in a cross-sectional field study that comprised 23 German psychiatric hospitals. Additionally, chart records and discharge letters of all patients were collected.</p> <p>Results</p> <p>The corresponding dataset extracted and presented in form of an overview here, comprises biographic information, disease history, medication including side effects, and results of comprehensive cross-sectional psychopathological, neuropsychological, and neurological examinations. With >3000 data points per schizophrenic subject, this data base of living patients, who are also accessible for follow-up studies, provides a wide-ranging and standardized phenotype characterization of as yet unprecedented detail.</p> <p>Conclusions</p> <p>The GRAS data base will serve as prerequisite for PGAS, a novel approach to better understanding 'the schizophrenias' through exploring the contribution of genetic variation to the schizophrenic phenotypes.</p

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks