@article{HeisselPietrekSchwefeletal.2020, author = {Heissel, Andreas and Pietrek, Anou F. and Schwefel, Melanie and Abula, Kahar and Wilbertz, Gregor and Heinzel, Stephan and Rapp, Michael A.}, title = {STEP.De study}, series = {BMJ open}, volume = {10}, journal = {BMJ open}, number = {4}, publisher = {BMJ Publishing Group}, address = {London}, issn = {2044-6055}, doi = {10.1136/bmjopen-2019-036287}, pages = {10}, year = {2020}, abstract = {Introduction Although exercise therapy has widely been shown to be an efficacious treatment modality for depression, evidence for its effectiveness and cost efficiency is lacking. The Sport/Exercise Therapy for Depression study is a multicentre cluster-randomised effectiveness trial that aims to compare the effectiveness and cost efficiency of exercise therapy and psychotherapy as antidepressant treatment.
Methods and analysis 480 patients (aged 18-65) with an International Classification of Diseases diagnosis associated with depressive symptoms are recruited. Up to 30 clusters (psychotherapists) are randomly assigned to allocate patients to either an exercise or a psychotherapy treatment as usual in a 2: 1 ratio. The primary outcome (depressive symptoms) and the secondary outcomes (work and social adjustment, quality of life) will be assessed at six measurement time points (t0: baseline, t1: 8 weeks after treatment initiation, t2: 16 weeks after treatment initiation, t3/ 4/5: 2, 6, 12 months after treatment). Linear regression analyses will be used for the primary endpoint data analysis. For the secondary endpoints, mixed linear and logistic regression models with fixed and random factors will be added. For the cost efficiency analysis, expenditures in the 12 months before and after the intervention and the outcome difference will be compared between groups in a multilevel model. Recruitment start date was 1 July 2018 and the planned recruitment end date is 31 December 2020.
Ethics and dissemination The study protocol was approved by the ethics committee of the University of Potsdam (No. 17/2018) and the Freie Universitat Berlin (No. 206/2018) and registered in the ISRCTN registry. Informed written consent will be obtained from all participants. The study will be reported in accordance with the Consolidated Standards of Reporting Trials and the Recommendations for Interventional Trials statements. The results will be published in peer-reviewed academic journals and disseminated to the public.}, language = {en} } @article{VaidSomaniRussaketal.2020, author = {Vaid, Akhil and Somani, Sulaiman and Russak, Adam J. and De Freitas, Jessica K. and Chaudhry, Fayzan F. and Paranjpe, Ishan and Johnson, Kipp W. and Lee, Samuel J. and Miotto, Riccardo and Richter, Felix and Zhao, Shan and Beckmann, Noam D. and Naik, Nidhi and Kia, Arash and Timsina, Prem and Lala, Anuradha and Paranjpe, Manish and Golden, Eddye and Danieletto, Matteo and Singh, Manbir and Meyer, Dara and O'Reilly, Paul F. and Huckins, Laura and Kovatch, Patricia and Finkelstein, Joseph and Freeman, Robert M. and Argulian, Edgar and Kasarskis, Andrew and Percha, Bethany and Aberg, Judith A. and Bagiella, Emilia and Horowitz, Carol R. and Murphy, Barbara and Nestler, Eric J. and Schadt, Eric E. and Cho, Judy H. and Cordon-Cardo, Carlos and Fuster, Valentin and Charney, Dennis S. and Reich, David L. and B{\"o}ttinger, Erwin and Levin, Matthew A. and Narula, Jagat and Fayad, Zahi A. and Just, Allan C. and Charney, Alexander W. and Nadkarni, Girish N. and Glicksberg, Benjamin S.}, title = {Machine learning to predict mortality and critical events in a cohort of patients with COVID-19 in New York City: model development and validation}, series = {Journal of medical internet research : international scientific journal for medical research, information and communication on the internet ; JMIR}, volume = {22}, journal = {Journal of medical internet research : international scientific journal for medical research, information and communication on the internet ; JMIR}, number = {11}, publisher = {Healthcare World}, address = {Richmond, Va.}, issn = {1439-4456}, doi = {10.2196/24018}, pages = {19}, year = {2020}, abstract = {Background: COVID-19 has infected millions of people worldwide and is responsible for several hundred thousand fatalities. The COVID-19 pandemic has necessitated thoughtful resource allocation and early identification of high-risk patients. However, effective methods to meet these needs are lacking. Objective: The aims of this study were to analyze the electronic health records (EHRs) of patients who tested positive for COVID-19 and were admitted to hospitals in the Mount Sinai Health System in New York City; to develop machine learning models for making predictions about the hospital course of the patients over clinically meaningful time horizons based on patient characteristics at admission; and to assess the performance of these models at multiple hospitals and time points. Methods: We used Extreme Gradient Boosting (XGBoost) and baseline comparator models to predict in-hospital mortality and critical events at time windows of 3, 5, 7, and 10 days from admission. Our study population included harmonized EHR data from five hospitals in New York City for 4098 COVID-19-positive patients admitted from March 15 to May 22, 2020. The models were first trained on patients from a single hospital (n=1514) before or on May 1, externally validated on patients from four other hospitals (n=2201) before or on May 1, and prospectively validated on all patients after May 1 (n=383). Finally, we established model interpretability to identify and rank variables that drive model predictions. Results: Upon cross-validation, the XGBoost classifier outperformed baseline models, with an area under the receiver operating characteristic curve (AUC-ROC) for mortality of 0.89 at 3 days, 0.85 at 5 and 7 days, and 0.84 at 10 days. XGBoost also performed well for critical event prediction, with an AUC-ROC of 0.80 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. In external validation, XGBoost achieved an AUC-ROC of 0.88 at 3 days, 0.86 at 5 days, 0.86 at 7 days, and 0.84 at 10 days for mortality prediction. Similarly, the unimputed XGBoost model achieved an AUC-ROC of 0.78 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. Trends in performance on prospective validation sets were similar. At 7 days, acute kidney injury on admission, elevated LDH, tachypnea, and hyperglycemia were the strongest drivers of critical event prediction, while higher age, anion gap, and C-reactive protein were the strongest drivers of mortality prediction. Conclusions: We externally and prospectively trained and validated machine learning models for mortality and critical events for patients with COVID-19 at different time horizons. These models identified at-risk patients and uncovered underlying relationships that predicted outcomes.}, language = {en} } @article{AlbrechtWinkelmannLevermann2020, author = {Albrecht, Torsten and Winkelmann, Ricarda and Levermann, Anders}, title = {Glacial-cycle simulations of the Antarctic Ice Sheet with the Parallel Ice Sheet Model (PISM)}, series = {The Cryosphere : TC ; an interactive open access journal of the European Geosciences Union}, volume = {14}, journal = {The Cryosphere : TC ; an interactive open access journal of the European Geosciences Union}, number = {2}, publisher = {Copernicus}, address = {G{\"o}ttingen}, issn = {1994-0416}, doi = {10.5194/tc-14-599-2020}, pages = {599 -- 632}, year = {2020}, abstract = {Simulations of the glacial-interglacial history of the Antarctic Ice Sheet provide insights into dynamic threshold behavior and estimates of the ice sheet's contributions to global sea-level changes for the past, present and future. However, boundary conditions are weakly constrained, in particular at the interface of the ice sheet and the bedrock. Also climatic forcing covering the last glacial cycles is uncertain, as it is based on sparse proxy data.
We use the Parallel Ice Sheet Model (PISM) to investigate the dynamic effects of different choices of input data, e.g., for modern basal heat flux or reconstructions of past changes of sea level and surface temperature. As computational resources are limited, glacial-cycle simulations are performed using a comparably coarse model grid of 16 km and various parameterizations, e.g., for basal sliding, iceberg calving, or for past variations in precipitation and ocean temperatures. In this study we evaluate the model's transient sensitivity to corresponding parameter choices and to different boundary conditions over the last two glacial cycles and provide estimates of involved uncertainties. We also discuss isolated and combined effects of climate and sea-level forcing. Hence, this study serves as a "cookbook" for the growing community of PISM users and paleo-ice sheet modelers in general.
For each of the different model uncertainties with regard to climatic forcing, ice and Earth dynamics, and basal processes, we select one representative model parameter that captures relevant uncertainties and motivates corresponding parameter ranges that bound the observed ice volume at present. The four selected parameters are systematically varied in a parameter ensemble analysis, which is described in a companion paper.}, language = {en} } @article{AlbrechtWinkelmannLevermann2020, author = {Albrecht, Torsten and Winkelmann, Ricarda and Levermann, Anders}, title = {Glacial-cycle simulations of the Antarctic Ice Sheet with the Parallel Ice Sheet Model (PISM)}, series = {The Cryosphere : TC ; an interactive open access journal of the European Geosciences Union}, volume = {14}, journal = {The Cryosphere : TC ; an interactive open access journal of the European Geosciences Union}, number = {2}, publisher = {Copernicus Publ.}, address = {G{\"o}ttingen}, issn = {1994-0416}, doi = {10.5194/tc-14-633-2020}, pages = {633 -- 656}, year = {2020}, abstract = {The Parallel Ice Sheet Model (PISM) is applied to the Antarctic Ice Sheet over the last two glacial cycles (approximate to 210 000 years) with a resolution of 16 km. An ensemble of 256 model runs is analyzed in which four relevant model parameters have been systematically varied using full-factorial parameter sampling. Parameters and plausible parameter ranges have been identified in a companion paper (Albrecht et al., 2020) and are associated with ice dynamics, climatic forcing, basal sliding and bed deformation and represent distinct classes of model uncertainties. The model is scored against both modern and geologic data, including reconstructed grounding-line locations, elevation-age data, ice thickness, surface velocities and uplift rates. An aggregated score is computed for each ensemble member that measures the overall model-data misfit, including measurement uncertainty in terms of a Gaussian error model (Briggs and Tarasov, 2013). The statistical method used to analyze the ensemble simulation results follows closely the simple averaging method described in Pollard et al. (2016). This analysis reveals clusters of best-fit parameter combinations, and hence a likely range of relevant model and boundary parameters, rather than individual best-fit parameters. The ensemble of reconstructed histories of Antarctic Ice Sheet volumes provides a score-weighted likely range of sea-level contributions since the Last Glacial Maximum (LGM) of 9.4 +/- 4.1m (or 6.5 +/- 2.0 x 10(6) km(3)), which is at the upper range of most previous studies. The last deglaciation occurs in all ensemble simulations after around 12 000 years before present and hence after the meltwater pulse 1A (MWP1a). Our ensemble analysis also provides an estimate of parametric uncertainty bounds for the present-day state that can be used for PISM projections of future sea-level contributions from the Antarctic Ice Sheet.}, language = {en} } @article{WunderlingWilleitDongesetal.2020, author = {Wunderling, Nico and Willeit, Matteo and Donges, Jonathan and Winkelmann, Ricarda}, title = {Global warming due to loss of large ice masses and Arctic summer sea ice}, series = {Nature Communications}, volume = {11}, journal = {Nature Communications}, number = {1}, publisher = {Nature Publishing Group}, address = {Berlin}, issn = {2041-1723}, doi = {10.1038/s41467-020-18934-3}, pages = {14}, year = {2020}, abstract = {Several large-scale cryosphere elements such as the Arctic summer sea ice, the mountain glaciers, the Greenland and West Antarctic Ice Sheet have changed substantially during the last century due to anthropogenic global warming. However, the impacts of their possible future disintegration on global mean temperature (GMT) and climate feedbacks have not yet been comprehensively evaluated. Here, we quantify this response using an Earth system model of intermediate complexity. Overall, we find a median additional global warming of 0.43 degrees C (interquartile range: 0.39-0.46 degrees C) at a CO2 concentration of 400 ppm. Most of this response (55\%) is caused by albedo changes, but lapse rate together with water vapour (30\%) and cloud feedbacks (15\%) also contribute significantly. While a decay of the ice sheets would occur on centennial to millennial time scales, the Arctic might become ice-free during summer within the 21st century. Our findings imply an additional increase of the GMT on intermediate to long time scales. The disintegration of cryosphere elements such as the Arctic summer sea ice, mountain glaciers, Greenland and West Antarctica is associated with temperature and radiative feedbacks. In this work, the authors quantify these feedbacks and find an additional global warming of 0.43 degrees C.}, language = {en} } @misc{MorenoRomeroProbstTrindadeetal.2020, author = {Moreno-Romero, Jordi and Probst, Aline V. and Trindade, In{\^e}s and Kalyanikrishna, and Engelhorn, Julia and Farrona, Sara}, title = {Looking At the Past and Heading to the Future}, series = {Frontiers in Plant Science}, volume = {10}, journal = {Frontiers in Plant Science}, number = {1795}, publisher = {Frontiers Media}, address = {Lausanne}, issn = {1664-462X}, doi = {10.3389/fpls.2019.01795}, pages = {1 -- 12}, year = {2020}, abstract = {In June 2019, more than a hundred plant researchers met in Cologne, Germany, for the 6th European Workshop on Plant Chromatin (EWPC). This conference brought together a highly dynamic community of researchers with the common aim to understand how chromatin organization controls gene expression, development, and plant responses to the environment. New evidence showing how epigenetic states are set, perpetuated, and inherited were presented, and novel data related to the three-dimensional organization of chromatin within the nucleus were discussed. At the level of the nucleosome, its composition by different histone variants and their specialized histone deposition complexes were addressed as well as the mechanisms involved in histone post-translational modifications and their role in gene expression. The keynote lecture on plant DNA methylation by Julie Law (SALK Institute) and the tribute session to Lars Hennig, honoring the memory of one of the founders of the EWPC who contributed to promote the plant chromatin and epigenetic field in Europe, added a very special note to this gathering. In this perspective article we summarize some of the most outstanding data and advances on plant chromatin research presented at this workshop.}, language = {en} } @article{PangDietrichTewsetal.2020, author = {Pang, Peter Tsun Ho and Dietrich, Tim and Tews, Ingo and Van Den Broeck, Chris}, title = {Parameter estimation for strong phase transitions in supranuclear matter using gravitational-wave astronomy}, series = {Physical review research}, volume = {2}, journal = {Physical review research}, number = {3}, publisher = {American Physical Society}, address = {College Park}, issn = {2643-1564}, doi = {10.1103/PhysRevResearch.2.033514}, pages = {17}, year = {2020}, abstract = {At supranuclear densities, explored in the core of neutron stars, a strong phase transition from hadronic matter to more exotic forms of matter might be present. To test this hypothesis, binary neutron-star mergers offer a unique possibility to probe matter at densities that we cannot create in any existing terrestrial experiment. In this work, we show that, if present, strong phase transitions can have a measurable imprint on the binary neutron-star coalescence and the emitted gravitational-wave signal. We construct a new parametrization of the supranuclear equation of state that allows us to test for the existence of a strong phase transition and extract its characteristic properties purely from the gravitational-wave signal of the inspiraling neutron stars. We test our approach using a Bayesian inference study simulating 600 signals with three different equations of state and find that for current gravitational-wave detector networks already 12 events might be sufficient to verify the presence of a strong phase transition. Finally, we use our methodology to analyze GW170817 and GW190425 but do not find any indication that a strong phase transition is present at densities probed during the inspiral.}, language = {en} } @article{XiaoLiuWangetal.2020, author = {Xiao, Shangbin and Liu, Liu and Wang, Wei and Lorke, Andreas and Woodhouse, Jason Nicholas and Grossart, Hans-Peter}, title = {A Fast-Response Automated Gas Equilibrator (FaRAGE) for continuous in situ measurement of CH4 and CO2 dissolved in water}, series = {Hydrology and earth system sciences : HESS}, volume = {24}, journal = {Hydrology and earth system sciences : HESS}, number = {7}, publisher = {European Geosciences Union (EGU) ; Copernicus}, address = {Munich}, issn = {1027-5606}, doi = {10.5194/hess-24-3871-2020}, pages = {3871 -- 3880}, year = {2020}, abstract = {Biogenic greenhouse gas emissions, e.g., of methane (CH4) and carbon dioxide (CO2) from inland waters, contribute substantially to global warming. In aquatic systems, dissolved greenhouse gases are highly heterogeneous in both space and time. To better understand the biological and physical processes that affect sources and sinks of both CH4 and CO2, their dissolved concentrations need to be measured with high spatial and temporal resolution. To achieve this goal, we developed the Fast-Response Automated Gas Equilibrator (FaRAGE) for real-time in situ measurement of dissolved CH4 and CO2 concentrations at the water surface and in the water column. FaRAGE can achieve an exceptionally short response time (t(95\%) = 12 s when including the response time of the gas analyzer) while retaining an equilibration ratio of 62.6\% and a measurement accuracy of 0.5\% for CH4. A similar performance was observed for dissolved CO2 (t(95\%) = 10 s, equilibration ratio 67.1 \%). An equilibration ratio as high as 91.8\% can be reached at the cost of a slightly increased response time (16 s). The FaRAGE is capable of continuously measuring dissolved CO2 and CH4 concentrations in the nM-to-submM (10(-9)-10(-3) mol L-1) range with a detection limit of subnM (10(-10) mol L-1), when coupling with a cavity ring-down greenhouse gas analyzer (Picarro GasScouter). FaRAGE allows for the possibility of mapping dissolved concentration in a "quasi" three-dimensional manner in lakes and provides an inexpensive alternative to other commercial gas equilibrators. It is simple to operate and suitable for continuous monitoring with a strong tolerance for suspended particles. While the FaRAGE is developed for inland waters, it can be also applied to ocean waters by tuning the gas-water mixing ratio. The FaRAGE is easily adapted to suit other gas analyzers expanding the range of potential applications, including nitrous oxide and isotopic composition of the gases.}, language = {en} } @article{SchellenbergReichertHardtetal.2020, author = {Schellenberg, Johannes and Reichert, Jessica and Hardt, Martin and Klingelh{\"o}fer, Ines and Morlock, Gertrud and Schubert, Patrick and Bižić, Mina and Grossart, Hans-Peter and K{\"a}mpfer, Peter and Wilke, Thomas and Glaeser, Stefanie P.}, title = {The bacterial microbiome of the long-term aquarium cultured high-microbial abundance sponge Haliclona cnidata}, series = {Frontiers in Marine Science}, volume = {7}, journal = {Frontiers in Marine Science}, publisher = {Frontiers Media}, address = {Lausanne}, issn = {2296-7745}, doi = {10.3389/fmars.2020.00266}, pages = {20}, year = {2020}, abstract = {Marine sponges host highly diverse but specific bacterial communities that provide essential functions for the sponge holobiont, including antimicrobial defense. Here, we characterized the bacterial microbiome of the marine sponge Haliclona cnidata that has been in culture in an artificial marine aquarium system. We tested the hypotheses (1) that the long-term aquarium cultured sponge H. cnidata is tightly associated with a typical sponge bacterial microbiota and (2) that the symbiotic Bacteria sustain bioactivity under harmful environmental conditions to facilitate holobiont survival by preventing pathogen invasion. Microscopic and phylogenetic analyses of the bacterial microbiota revealed that H. cnidata represents a high microbial abundance (HMA) sponge with a temporally stable bacterial community that significantly shifts with changing aquarium conditions. A 4-week incubation experiment was performed in small closed aquarium systems with antibiotic and/or light exclusion treatments to reduce the total bacterial and photosynthetically active sponge-associated microbiota to a treatment-specific resilient community. While the holobiont was severely affected by the experimental treatment (i.e., bleaching of the sponge, reduced bacterial abundance, shifted bacterial community composition), the biological defense and bacterial community interactions (i.e., quorum sensing activity) remained intact. 16S rRNA gene amplicon sequencing revealed a resilient community of 105 bacterial taxa, which remained in the treated sponges. These 105 taxa accounted for a relative abundance of 72-83\% of the bacterial sponge microbiota of non-treated sponge fragments that have been cultured under the same conditions. We conclude that a sponge-specific resilient community stays biologically active under harmful environmental conditions, facilitating the resilience of the holobiont. In H. cnidata, bacteria are located in bacteriocytes, which may have contributed to the observed phenomenon.}, language = {en} }