New molecular methods to assess biodiversity. Potentials and pitfalls of DNA metabarcoding: a workshop report

This report presents the outcome of the joint work of PhD students and senior researchers working with DNA-based biodiversity assessment approaches with the goal to facilitate others the access to definitions and explanations about novel DNA-based methods. The work was performed during a PhD course (SLU PNS0169) at the Swedish University of Agricultural Sciences (SLU) in Uppsala, Sweden. The course was co-organized by the EU COST research network DNAqua-Net and the SLU Research Schools Focus on Soils and Water (FoSW) and Ecology - basics and applications. DNAqua-Net (COST Action CA15219, 2016-2020) is a network connecting researchers, water managers, politicians and other stakeholders with the aim to develop new genetic tools for bioassessment of aquatic ecosystems in Europe and beyond. The PhD course offered a comprehensive overview of the paradigm shift from traditional morphology-based species identification to novel identification approaches based on molecular markers. We covered the use of molecular tools in both basic research and applied use with a focus on aquatic ecosystem assessment, from species collection to the use of diversity in environmental legislation. The focus of the course was on DNA (meta)barcoding and aquatic organisms. The knowledge gained was shared with the general public by creating Wikipedia pages and through this collaborative Open Access publication, co-authored by all course participants

The value of open-source clinical science in pandemic response: lessons from ISARIC

International audienc

ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19

The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use