Refine
Year of publication
Document Type
- Article (203)
- Preprint (38)
- Contribution to a Periodical (4)
Has Fulltext
- yes (245)
Is part of the Bibliography
- no (245)
Keywords
- SARS-CoV-2 (10)
- COVID-19 (5)
- Solution NMR-spectroscopy (4)
- COVID19-NMR (3)
- Covid19-NMR (3)
- Non-structural protein (3)
- risk factors (3)
- ACLF (2)
- Biomarkers (2)
- Collectivity (2)
Institute
Elliptic flow from nuclear collisions is a hadronic observable sensitive to the early stages of system evolution. We report first results on elliptic flow of charged particles at midrapidity in Au+Au collisions at sqrt(s_NN)=130 GeV using the STAR TPC at RHIC. The elliptic flow signal, v_2, averaged over transverse momentum, reaches values of about 6% for relatively peripheral collisions and decreases for the more central collisions. This can be interpreted as the observation of a higher degree of thermalization than at lower collision energies. Pseudorapidity and transverse momentum dependence of elliptic flow are also presented.
Background: Patients with liver cirrhosis have a highly elevated risk of developing bacterial infections that significantly decrease survival rates. One of the most relevant infections is spontaneous bacterial peritonitis (SBP). Recently, NOD2 germline variants were found to be potential predictors of the development of infectious complications and mortality in patients with cirrhosis. The aim of the INCA (Impact of NOD2 genotype-guided antibiotic prevention on survival in patients with liver Cirrhosis and Ascites) trial is to investigate whether survival of this genetically defined high-risk group of patients with cirrhosis defined by the presence of NOD2 variants is improved by primary antibiotic prophylaxis of SBP.
Methods/Design: The INCA trial is a double-blind, placebo-controlled clinical trial with two parallel treatment arms (arm 1: norfloxacin 400 mg once daily; arm 2: placebo once daily; 12-month treatment and observational period). Balanced randomization of 186 eligible patients with stratification for the protein content of the ascites (<15 versus ≥15 g/L) and the study site is planned. In this multicenter national study, patients are recruited in at least 13 centers throughout Germany. The key inclusion criterion is the presence of a NOD2 risk variant in patients with decompensated liver cirrhosis. The most important exclusion criteria are current SBP or previous history of SBP and any long-term antibiotic prophylaxis. The primary endpoint is overall survival after 12 months of treatment. Secondary objectives are to evaluate whether the frequencies of SBP and other clinically relevant infections necessitating antibiotic treatment, as well as the total duration of unplanned hospitalization due to cirrhosis, differ in both study arms. Recruitment started in February 2014.
Discussion: Preventive strategies are required to avoid life-threatening infections in patients with liver cirrhosis, but unselected use of antibiotics can trigger resistant bacteria and worsen outcome. Thus, individualized approaches that direct intervention only to patients with the highest risk are urgently needed. This trial meets this need by suggesting stratified prevention based on genetic risk assessment. To our knowledge, the INCA trial is first in the field of hepatology aimed at rapidly transferring and validating information on individual genetic risk into clinical decision algorithms.
Trial registrations: German Clinical Trials Register DRKS00005616. Registered 22 January 2014. EU Clinical Trials Register EudraCT 2013-001626-26. Registered 26 January 2015.
Overconsumption of carbohydrates and lipids are well known to cause nonalcoholic fatty liver disease (NAFLD), while the role of nutritional protein intake is less clear. In Western diet, meat and other animal products are the main protein source, with varying concentrations of specific amino acids. Whether the amount or composition of protein intake is associated with a higher risk for disease severity has not yet been examined. In this study, we investigated associations of dietary components with histological disease activity by analyzing detailed 14‐day food records in a cohort of 61 patients with biopsy‐proven NAFLD. Furthermore, we used 16S ribosomal RNA gene sequencing to detect associations with different abundances of the gut microbiota with dietary patterns. Patients with definite nonalcoholic steatohepatitis (NAFLD activity score of 5‐8 on liver biopsy) had a significantly higher daily relative intake of protein compared with patients with a NAFLD activity score of 0‐4 (18.0% vs. 15.8% of daily protein‐based calories, P = 0.018). After adjustment for several potentially confounding factors, a higher protein intake (≥17.3% of daily protein‐based calories) remained associated with definite nonalcoholic steatohepatitis, with an odds ratio of 5.09 (95% confidence interval 1.22‐21.25, P = 0.026). This association was driven primarily by serine, glycine, arginine, proline, phenylalanine, and methionine. A higher protein intake correlated with a lower Bacteroides abundance and an altered abundance of several other bacterial taxa. Conclusion: A high protein intake was independently associated with more active and severe histological disease activity in patients with NAFLD. Further studies are needed to investigate the potential harmful role of dietary amino acids on NAFLD, with special attention to meat as their major source.
Investigators in the cognitive neurosciences have turned to Big Data to address persistent replication and reliability issues by increasing sample sizes, statistical power, and representativeness of data. While there is tremendous potential to advance science through open data sharing, these efforts unveil a host of new questions about how to integrate data arising from distinct sources and instruments. We focus on the most frequently assessed area of cognition - memory testing - and demonstrate a process for reliable data harmonization across three common measures. We aggregated raw data from 53 studies from around the world which measured at least one of three distinct verbal learning tasks, totaling N = 10,505 healthy and brain-injured individuals. A mega analysis was conducted using empirical bayes harmonization to isolate and remove site effects, followed by linear models which adjusted for common covariates. After corrections, a continuous item response theory (IRT) model estimated each individual subject’s latent verbal learning ability while accounting for item difficulties. Harmonization significantly reduced inter-site variance by 37% while preserving covariate effects. The effects of age, sex, and education on scores were found to be highly consistent across memory tests. IRT methods for equating scores across AVLTs agreed with held-out data of dually-administered tests, and these tools are made available for free online. This work demonstrates that large-scale data sharing and harmonization initiatives can offer opportunities to address reproducibility and integration challenges across the behavioral sciences.
Introduction: The Retro-IDEAL (ILUVIEN Implant for chronic DiabEtic MAcuLar edema) study is a retrospective study designed to assess real-world outcomes achieved with the ILUVIEN® (0.19 mg fluocinolone acetonide (FAc)) in patients with chronic diabetic macular edema (DME) in clinical practices in Germany.
Methods: This study was conducted across 16 sites in Germany and involved 81 eyes (63 patients) with persistent or recurrent DME and a prior suboptimal response to a first-line intravitreal therapy (primarily anti-VEGF intravitreal therapies).
Results: Patients were followed-up for 30.8 ± 11.3 months (mean ± standard deviation) and had a mean age of 68.0 ± 10.4 years. Best-recorded visual acuity (BRVA) improved by +5.5 letters at month 9 (P ⩽ 0.005, n=56; from a baseline of 49 letters) and this was maintained through to month 30 (P ⩽ 0.05, n = 42). There was a concurrent improvement in central macular thickness with a reduction from 502 µm at baseline to 338 µm at year 1 (P ⩽ 0.0001, n = 43). This effect was sustained to year 3 (i.e. 318 µm; P ⩽ 0.0001, n = 29). Mean intraocular pressure (IOP) remained constant between baseline and year 3 with a peak change of 1.9 mm Hg occurring at year 1. Elevated IOP was observed in a similar percentage of patients prior to (22.2% of cases) and following (27.2%) treatment with the FAc implant. In the majority of cases, these elevations were managed effectively with IOP medications.
Conclusions: Despite substantial amounts of prior intravitreal treatments – primarily with anti–vascular endothelial growth factor (VEGF) drugs – this real-world study showed that sustained structural and functional improvements can last for up to 3 years with a single FAc implant.
In den vorangehenden Kapiteln wurde die besondere Charakteristik sowie die bundes- und europaweite Bedeutung des Schutzgebietssystems um die Mansfelder Seen und vordringlich des ehemaligen Salzigen Sees herausgestellt. Es wurde ebenfalls deutlich, dass die Wiederentstehung des Salzigen Sees einen schwerwiegenden Eingriff in den bestehenden Gebietswasserhaushalt darstellt, dessen langfristige Konsequenzen noch nicht in allen Aspekten absehbar sind. Welche Auswirkungen kann dieses Vorhaben nun auf die hoch schutzwürdige Fauna und Flora haben und welche Vorkehrungen müssen getroffen werden, damit die Chancen für den Arten- und Biotopschutz, die der Wiederentstehung des Sees zweifellos innewohnen, zum Tragen kommen?
The Tarim River basin, located in Xinjiang, NW China, is the largest endorheic river basin in China and one of the largest in all of Central Asia. Due to the extremely arid climate, with an annual precipitation of less than 100 mm, the water supply along the Aksu and Tarim rivers solely depends on river water. This is linked to anthropogenic activities (e.g., agriculture) and natural and semi-natural ecosystems as both compete for water. The ongoing increase in water consumption by agriculture and other human activities in this region has been enhancing the competition for water between human needs and nature. Against this background, 11 German and 6 Chinese universities and research institutes have formed the consortium SuMaRiO (Sustainable Management of River Oases along the Tarim River; http://www.sumario.de), which aims to create a holistic picture of the availability of water resources in the Tarim River basin and the impacts on anthropogenic activities and natural ecosystems caused by the water distribution within the Tarim River basin. On the basis of the results from field studies and modeling approaches as well as from suggestions by the relevant regional stakeholders, a decision support tool (DST) will be implemented that will then assist stakeholders in balancing the competition for water, acknowledging the major external effects of water allocation to agriculture and to natural ecosystems. This consortium was formed in 2011 and is funded by the German Federal Ministry of Education and Research. As the data collection phase was finished this year, the paper presented here brings together the results from the fields from the disciplines of climate modeling, cryology, hydrology, agricultural sciences, ecology, geoinformatics, and social sciences in order to present a comprehensive picture of the effects of different water availability schemes on anthropogenic activities and natural ecosystems along the Tarim River. The second objective is to present the project structure of the whole consortium, the current status of work (i.e., major new results and findings), explain the foundation of the decision support tool as a key product of this project, and conclude with application recommendations for the region. The discharge of the Aksu River, which is the major tributary of the Tarim, has been increasing over the past 6 decades. From 1989 to 2011, agricultural area more than doubled: cotton became the major crop and there was a shift from small-scale to large-scale intensive farming. The ongoing increase in irrigated agricultural land leads to the increased threat of salinization and soil degradation caused by increased evapotranspiration. Aside from agricultural land, the major natural and semi-natural ecosystems are riparian (Tugai) forests, shrub vegetation, reed beds, and other grassland, as well as urban and peri-urban vegetation. Within the SuMaRiO cluster, focus has been set on the Tugai forests, with Populus euphratica as the dominant tree species, because these forests belong to the most productive and species-rich natural ecosystems of the Tarim River basin. At sites close to the groundwater, the annual stem diameter increments of Populus euphratica correlated with the river runoffs of the previous year. However, the natural river dynamics cease along the downstream course and thus hamper the recruitment of Populus euphratica. A study on the willingness to pay for the conservation of the natural ecosystems was conducted to estimate the concern of the people in the region and in China's capital. These household surveys revealed that there is a considerable willingness to pay for conservation of the natural ecosystems, with mitigation of dust and sandstorms considered the most important ecosystem service. Stakeholder dialogues contributed to creating a scientific basis for a sustainable management in the future.
Objectives: An increasing number of treatment-determining biomarkers has been identified in non-small cell lung cancer (NSCLC) and molecular testing is recommended to enable optimal individualized treatment. However, data on implementation of these recommendations in the “real-world” setting are scarce. This study presents comprehensive details on the frequency, methodology and results of biomarker testing of advanced NSCLC in Germany.
Patients and methods: This analysis included 3,717 patients with advanced NSCLC (2,921 non-squamous; 796 squamous), recruited into the CRISP registry at start of systemic therapy by 150 German sites between December 2015 and June 2019. Evaluated were the molecular biomarkers EGFR, ALK, ROS1, BRAF, KRAS, MET, TP53, RET, HER2, as well as expression of PD-L1.
Results: In total, 90.5 % of the patients were tested for biomarkers. Testing rates were 92.2 % (non-squamous), 70.7 % (squamous) and increased from 83.2 % in 2015/16 to 94.2% in 2019. Overall testing rates for EGFR, ALK, ROS1, and BRAF were 72.5 %, 74.5 %, 66.1 %, and 53.0 %, respectively (non-squamous). Testing rates for PD-L1 expression were 64.5 % (non-squamous), and 58.5 % (squamous). The most common testing methods were immunohistochemistry (68.5 % non-squamous, 58.3 % squamous), and next-generation sequencing (38.7 % non-squamous, 14.4 % squamous). Reasons for not testing were insufficient tumor material or lack of guideline recommendations (squamous). No alteration was found in 37.8 % (non-squamous), and 57.9 % (squamous), respectively. Most common alterations in non-squamous tumors (all patients/all patients tested for the respective biomarker): KRAS (17.3 %/39.2 %), TP53 (14.1 %/51.4 %), and EGFR (11.0 %/15.1 %); in squamous tumors: TP53 (7.0 %/69.1 %), MET (1.5 %/11.1 %), and EGFR (1.1 %/4.4 %). Median PFS (non-squamous) was 8.7 months (95 % CI 7.4–10.4) with druggable EGFR mutation, and 8.0 months (95 % CI 3.9–9.2) with druggable ALK alterations.
Conclusion: Testing rates in Germany are high nationwide and acceptable in international comparison, but still leave out a significant portion of patients, who could potentially benefit. Thus, specific measures are needed to increase implementation.
Purpose: While more advanced COVID-19 necessitates medical interventions and hospitalization, patients with mild COVID-19 do not require this. Identifying patients at risk of progressing to advanced COVID-19 might guide treatment decisions, particularly for better prioritizing patients in need for hospitalization.
Methods: We developed a machine learning-based predictor for deriving a clinical score identifying patients with asymptomatic/mild COVID-19 at risk of progressing to advanced COVID-19. Clinical data from SARS-CoV-2 positive patients from the multicenter Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS) were used for discovery (2020-03-16 to 2020-07-14) and validation (data from 2020-07-15 to 2021-02-16).
Results: The LEOSS dataset contains 473 baseline patient parameters measured at the first patient contact. After training the predictor model on a training dataset comprising 1233 patients, 20 of the 473 parameters were selected for the predictor model. From the predictor model, we delineated a composite predictive score (SACOV-19, Score for the prediction of an Advanced stage of COVID-19) with eleven variables. In the validation cohort (n = 2264 patients), we observed good prediction performance with an area under the curve (AUC) of 0.73 ± 0.01. Besides temperature, age, body mass index and smoking habit, variables indicating pulmonary involvement (respiration rate, oxygen saturation, dyspnea), inflammation (CRP, LDH, lymphocyte counts), and acute kidney injury at diagnosis were identified. For better interpretability, the predictor was translated into a web interface.
Conclusion: We present a machine learning-based predictor model and a clinical score for identifying patients at risk of developing advanced COVID-19.