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Institution

Leibniz Association

GovernmentBerlin, Germany
About: Leibniz Association is a government organization based out in Berlin, Germany. It is known for research contribution in the topics: Population & Aerosol. The organization has 16586 authors who have published 35691 publications receiving 1095107 citations. The organization is also known as: Leibniz-Gemeinschaft & Wissenschaftsgemeinschaft Gottfried Wilhelm Leibniz.
Topics: Population, Aerosol, Genome, Hordeum vulgare, Gene


Papers
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Journal ArticleDOI
Clotilde Théry1, Kenneth W. Witwer2, Elena Aikawa3, María José Alcaraz4  +414 moreInstitutions (209)
TL;DR: The MISEV2018 guidelines include tables and outlines of suggested protocols and steps to follow to document specific EV-associated functional activities, and a checklist is provided with summaries of key points.
Abstract: The last decade has seen a sharp increase in the number of scientific publications describing physiological and pathological functions of extracellular vesicles (EVs), a collective term covering various subtypes of cell-released, membranous structures, called exosomes, microvesicles, microparticles, ectosomes, oncosomes, apoptotic bodies, and many other names. However, specific issues arise when working with these entities, whose size and amount often make them difficult to obtain as relatively pure preparations, and to characterize properly. The International Society for Extracellular Vesicles (ISEV) proposed Minimal Information for Studies of Extracellular Vesicles (“MISEV”) guidelines for the field in 2014. We now update these “MISEV2014” guidelines based on evolution of the collective knowledge in the last four years. An important point to consider is that ascribing a specific function to EVs in general, or to subtypes of EVs, requires reporting of specific information beyond mere description of function in a crude, potentially contaminated, and heterogeneous preparation. For example, claims that exosomes are endowed with exquisite and specific activities remain difficult to support experimentally, given our still limited knowledge of their specific molecular machineries of biogenesis and release, as compared with other biophysically similar EVs. The MISEV2018 guidelines include tables and outlines of suggested protocols and steps to follow to document specific EV-associated functional activities. Finally, a checklist is provided with summaries of key points.

5,988 citations

Journal ArticleDOI
Mohsen Naghavi1, Haidong Wang1, Rafael Lozano1, Adrian Davis2  +728 moreInstitutions (294)
TL;DR: In the Global Burden of Disease Study 2013 (GBD 2013) as discussed by the authors, the authors used the GBD 2010 methods with some refinements to improve accuracy applied to an updated database of vital registration, survey, and census data.

5,792 citations

Journal ArticleDOI
Theo Vos1, Christine Allen1, Megha Arora1, Ryan M Barber1  +696 moreInstitutions (260)
TL;DR: The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015) as discussed by the authors was used to estimate the incidence, prevalence, and years lived with disability for diseases and injuries at the global, regional, and national scale over the period of 1990 to 2015.

5,050 citations

Journal ArticleDOI
Haidong Wang1, Mohsen Naghavi1, Christine Allen1, Ryan M Barber1  +841 moreInstitutions (293)
TL;DR: The Global Burden of Disease 2015 Study provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015, finding several countries in sub-Saharan Africa had very large gains in life expectancy, rebounding from an era of exceedingly high loss of life due to HIV/AIDS.

4,804 citations

Journal ArticleDOI
TL;DR: Despite the high accuracy of GBDP-based DDH prediction, inferences from limited empirical data are always associated with a certain degree of uncertainty, so it is crucial to enrich in-silico DDH replacements with confidence-interval estimation, enabling the user to statistically evaluate the outcomes.
Abstract: For the last 25 years species delimitation in prokaryotes (Archaea and Bacteria) was to a large extent based on DNA-DNA hybridization (DDH), a tedious lab procedure designed in the early 1970s that served its purpose astonishingly well in the absence of deciphered genome sequences. With the rapid progress in genome sequencing time has come to directly use the now available and easy to generate genome sequences for delimitation of species. GBDP (Genome Blast Distance Phylogeny) infers genome-to-genome distances between pairs of entirely or partially sequenced genomes, a digital, highly reliable estimator for the relatedness of genomes. Its application as an in-silico replacement for DDH was recently introduced. The main challenge in the implementation of such an application is to produce digital DDH values that must mimic the wet-lab DDH values as close as possible to ensure consistency in the Prokaryotic species concept. Correlation and regression analyses were used to determine the best-performing methods and the most influential parameters. GBDP was further enriched with a set of new features such as confidence intervals for intergenomic distances obtained via resampling or via the statistical models for DDH prediction and an additional family of distance functions. As in previous analyses, GBDP obtained the highest agreement with wet-lab DDH among all tested methods, but improved models led to a further increase in the accuracy of DDH prediction. Confidence intervals yielded stable results when inferred from the statistical models, whereas those obtained via resampling showed marked differences between the underlying distance functions. Despite the high accuracy of GBDP-based DDH prediction, inferences from limited empirical data are always associated with a certain degree of uncertainty. It is thus crucial to enrich in-silico DDH replacements with confidence-interval estimation, enabling the user to statistically evaluate the outcomes. Such methodological advancements, easily accessible through the web service at http://ggdc.dsmz.de , are crucial steps towards a consistent and truly genome sequence-based classification of microorganisms.

4,411 citations


Authors

Showing all 16595 results

NameH-indexPapersCitations
Helmut Sies13367078319
Mark Stitt13245660800
Norbert Schwarz11748871008
Matthias Beller11373346344
Matthias Steinmetz11246167802
Marten Scheffer11135073789
Erko Stackebrandt10663368201
Andreas Radbruch10448536872
Rajeev K. Varshney10270939796
Thomas J. Jentsch10123832810
Michael Schulz10075950719
Oliver G. Schmidt100108339988
Rainer Waser9992748315
Paul Knochel99237344786
Matthias Beller9790334480
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20232
202269
20213,517
20203,305
20192,981
20182,654