Suchergebnisse

Während Klimaforschung lange als rein naturwissenschaftliches Unterfangen galt, wird sie seit den 2010er Jahren zunehmend auch in den Sozialwissenschaften betrieben. Die Popularisierung in und außerhalb der Wissenschaft hat dabei nicht nur zu neuen Problembezügen geführt, sondern auch eine wachsende Unübersichtlichkeit produziert: Es ist ein Bedarf entstanden, disziplinäre Einstiegspunkte, interdisziplinäre Anschlussmöglichkeiten und transdisziplinäre Austauschgelegenheiten zu sondieren. Die Beiträger*innen des Bandes rezensieren zentrale Schlüsselwerke der sozialwissenschaftlichen Klimaforschung und ermöglichen so einen ersten Zugang zum sowie eine Orientierung im Forschungsfeld

Fast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine(1,2). Patients with leukaemia can be identified using machine learning on the basis of their blood transcriptomes(3). However, there is an increasing divide between what is technically possible and what is allowed, because of privacy legislation(4,5). Here, to facilitate the integration of any medical data from any data owner worldwide without violating privacy laws, we introduce Swarm Learning-a decentralized machine-learning approach that unites edge computing, blockchain-based peer-to-peer networking and coordination while maintaining confidentiality without the need for a central coordinator, thereby going beyond federated learning. To illustrate the feasibility of using Swarm Learning to develop disease classifiers using distributed data, we chose four use cases of heterogeneous diseases (COVID-19, tuberculosis, leukaemia and lung pathologies). With more than 16,400 blood transcriptomes derived from 127 clinical studies with non-uniform distributions of cases and controls and substantial study biases, as well as more than 95,000 chest X-ray images, we show that Swarm Learning classifiers outperform those developed at individual sites. In addition, Swarm Learning completely fulfils local confidentiality regulations by design. We believe that this approach will notably accelerate the introduction of precision medicine.

We report the period, eccentricity, and mass determination for the Transiting Exoplanet Survey Satellite (TESS) single-transit event candidate TOI-222, which displayed a single 3000 ppm transit in the TESS 2-min cadence data from Sector 2. We determine the orbital period via radial velocity measurements (P = 33.9 d), which allowed for ground-based photometric detection of two subsequent transits. Our data show that the companion to TOI-222 is a low-mass star, with a radius of 0.18(-0.10)(+0.39) R-circle dot and a mass of 0.23 +/- 0.01 M-circle dot. This discovery showcases the ability to efficiently discover long-period systems from TESS single-transit events using a combination of radial velocity monitoring coupled with high-precision ground-based photometry. ; Swiss National Science Foundation (SNSF) Geneva University Swiss National Science Foundation (SNSF) Science & Technology Facilities Council (STFC) ST/M001962/1 ST/S002642/1 Science & Technology Facilities Council (STFC) ST/L000733/1 ST/P000495/1 ST/N000757/1 ST/P000312/1 1226157 STFC via an Ernest Rutherford Fellowship ST/R00384X/1 MIT's Kavli Institute Austrian Research Promotion Agency (FFG) 859724 Comisión Nacional de Investigación Científica y Tecnológica (CONICYT) PB06 CONICYT-PFCHA, Chile 21191829 Millennium Institute of Astrophysics (MAS) Comisión Nacional de Investigación Científica y Tecnológica (CONICYT) CONICYT FONDECYT 1161218 3180246 1171208 Ministry for the Economy, Development, and Tourism's Programa Iniciativa Científica Milenio IC120009 European Research Council (ERC) 681601 ERC under the European Union 320964 Australian Research Council LE160100001 DP180100972 Mount Cuba Astronomical Foundation University of Texas at Austin UNSW Australia MIT Nanjing University George Mason University University of Louisville University of California System University of Florida NASA's Science Mission directorate University of Southern Queensland

In the past 5–10 years, Venezuela has faced a severe economic crisis, precipitated by political instability and declining oil revenue. Public health provision has been affected particularly. In this Review, we assess the impact of Venezuela's health-care crisis on vector-borne diseases, and the spillover into neighbouring countries. Between 2000 and 2015, Venezuela witnessed a 359% increase in malaria cases, followed by a 71% increase in 2017 (411 586 cases) compared with 2016 (240 613). Neighbouring countries, such as Brazil, have reported an escalating trend of imported malaria cases from Venezuela, from 1538 in 2014 to 3129 in 2017. In Venezuela, active Chagas disease transmission has been reported, with seroprevalence in children ( less than 10 years), estimated to be as high as 12·5% in one community tested (n=64). Dengue incidence increased by more than four times between 1990 and 2016. The estimated incidence of chikungunya during its epidemic peak is 6975 cases per 100 000 people and that of Zika virus is 2057 cases per 100 000 people. The re-emergence of many vector-borne diseases represents a public health crisis in Venezuela and has the possibility of severely undermining regional disease elimination efforts. National, regional, and global authorities must take action to address these worsening epidemics and prevent their expansion beyond Venezuelan borders. © 2019 Elsevier Ltd

A new introduction to a timeless dynamic: how the movement of humans affects health everywhere. International migrants compose more than three percent of the world's population, and internal migrants—those migrating within countries—are more than triple that number. Population migration has long been, and remains today, one of the central demographic shifts shaping the world around us. The world's history—and its health—is shaped and colored by stories of migration patterns, the policies and political events that drive these movements, and narratives of individual migrants. Migration and Health offers the most expansive framework to date for understanding and reckoning with human migration's implications for public health and its determinants. It interrogates this complex relationship by considering not only the welfare of migrants, but also that of the source, destination, and ensuing-generation populations. The result is an elevated, interdisciplinary resource for understanding what is known—and the considerable territory of what is not known—at an intersection that promises to grow in importance and influence as the century unfolds

A key objective in the field of translational psychiatry over the past few decades has been to identify the brain correlates of major depressive disorder (MDD). Identifying measurable indicators of brain processes associated with MDD could facilitate the detection of individuals at risk, and the development of novel treatments, the monitoring of treatment effects, and predicting who might benefit most from treatments that target specific brain mechanisms. However, despite intensive neuroimaging research towards this effort, underpowered studies and a lack of reproducible findings have hindered progress. Here, we discuss the work of the ENIGMA Major Depressive Disorder (MDD) Consortium, which was established to address issues of poor replication, unreliable results, and overestimation of effect sizes in previous studies. The ENIGMA MDD Consortium currently includes data from 45 MDD study cohorts from 14 countries across six continents. The primary aim of ENIGMA MDD is to identify structural and functional brain alterations associated with MDD that can be reliably detected and replicated across cohorts worldwide. A secondary goal is to investigate how demographic, genetic, clinical, psychological, and environmental factors affect these associations. In this review, we summarize findings of the ENIGMA MDD disease working group to date and discuss future directions. We also highlight the challenges and benefits of large-scale data sharing for mental health research. ; ENIGMA MDD work is supported by NIH grants U54 EB020403 (Thompson), R01 MH116147 (Thompson), and R01 MH117601 (Jahanshad & Schmaal). LS was supported by an NHMRC Career Development Fellowship (1140764). AFFDIS cohort: this study was funded by the University Medical Center Goettingen (UMG Startfoerderung) and the research team is supported by German Federal Ministry of Education and Research (Bundesministerium fuer Bildung und Forschung, BMBF: 01 ZX 1507, "PreNeSt - e:Med"). Barcelona cohort: MJP is funded by the Ministerio de Ciencia e Innovación of the Spanish Government and by the Instituto de Salud Carlos III through a 'Miguel Servet' research contract (CP16–0020); National Research Plan (Plan Estatal de I + D + I 2016–2019); and co-financed by the European Regional Development Fund (ERDF). BRC DeCC cohort: CHYF is supported by NIHR BRC. Calgary cohort: supported by Canadian Institutes for Health Research, Branch Out Neurological Foundation. Cardiff cohort: supported by the Medical Research Council (grant G 1100629) and the National Center for Mental Health (NCMH), funded by Health Research Wales (HS/14/20). CLING cohort: this study was partially supported by the Deutsche Forschungsgemeinschaft (DFG) via grants to OG (GR1950/5–1 and GR1950/10–1). CODE cohort: Henrik Walter is supported by a grant of the Deutsche Forschungsgemeinschaft (WA 1539/4–1). The CODE cohort was collected from studies funded by Lundbeck and the German Research Foundation (WA 1539/4–1, SCHN 1205/3–1, SCHR443/11–1). DIP-Groningen cohort: this study was supported by the Gratama Foundation, the Netherlands (2012/35 to NG). Edinburgh cohort: The research leading to these results was supported by IMAGEMEND, which received funding from the European Community's Seventh Framework Programme (FP7/2007–2013) under grant agreement no. 602450. This paper reflects only the author's views and the European Union is not liable for any use that may be made of the information contained therein. This work was also supported by a Wellcome Trust Strategic Award 104036/Z/14/Z. FOR2107-Marburg cohort: funded by the German Research Foundation (DFG, grant FOR2107 KR 3822/7–2 to AK; FOR2107 KI 588/14–2 to TK and FOR2107 JA 1890/7–2 to AJ). Houston cohorts: supported in part by NIMH grant R01 085667 and the Dunn Research Foundation. JCS is supported by the Pat Rutherford, Jr. Endowed Chair in Psychiatry. IMH Study cohort: supported by funding from NHG (SIG/15012) and NMRC CISSP (2018). Melbourne cohort: funded by National Health and Medical Research Council of Australia (NHMRC) Project Grants 1064643 (Principal Investigator BJH) and 1024570 (Principal Investigator CGD). Minnesota cohort: the study was funded by the National Institute of Mental Health (K23MH090421; Dr. Cullen) and Biotechnology Research Center (P41 RR008079; Center for Magnetic Resonance Research), the National Alliance for Research on Schizophrenia and Depression, the University of Minnesota Graduate School, and the Minnesota Medical Foundation. This work was carried out in part using computing resources at the University of Minnesota Supercomputing Institute. Münster cohort: funded by the German Research Foundation (DFG, grant FOR2107 DA1151/5–1 and DA1151/5–2 to UD; SFB-TRR58, Projects C09 and Z02 to UD) and the Interdisciplinary Center for Clinical Research (IZKF) of the medical faculty of Münster (grant Dan3/012/17 to UD). NESDA cohort: The infrastructure for the NESDA study (www.nesda.nl) is funded through the Geestkracht program of the Netherlands Organisation for Health Research and Development (Zon-Mw, grant number 10–000–1002) and is supported by participating universities (VU University Medical Center, GGZ inGeest, Arkin, Leiden University Medical Center, GGZ Rivierduinen, University Medical Center Groningen) and mental health care organizations, see www.nesda.nl. Pharmo cohort: supported by ERA-NET PRIOMEDCHILD FP 6 (EU) grant 11.32050.26. PSYABM-NORMENT: supported by the Research Council of Norway (project number 229135). The South East Norway Health Authority Research Funding (project number 2015052). The Department of Psychology, University of Oslo, Norway. San Francisco cohort: supported by NIH/NCCIH 1R61AT009864–01A1. NIMH R01MH085734. SHIP and SHIP-trend cohorts: SHIP is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (grants no. 01ZZ9603, 01ZZ0103, and 01ZZ0403), the Ministry of Cultural Affairs and the Social Ministry of the Federal State of Mecklenburg-West Pomerania. MRI scans in SHIP and SHIP-TREND have been supported by a joint grant from Siemens Healthineers, Erlangen, Germany and the Federal State of Mecklenburg-West Pomerania. Stanford cohorts: this work was supported by NIH grant R37 MH101495. The BiDirect Study was supported by grants from the German Federal Ministry of Education and Research (BMBF; grants FKZ-01ER0816 and FKZ-01ER1506). MDS is partially supported by an award funded by the Phyllis and Jerome Lyle Rappaport Foundation. TCH is supported by NIMH grant 5K01MH117442. EJWVS, JL, and TFB are supported by European Research Council grant no. ERC-ADG-2014–671084 INSOMNIA. TFB is supported by a VU University Amsterdam University Research Fellowship 2016–2017. JL is supported by a VU University Amsterdam University Research Fellowship 2017–2018. ; publishedVersion

Special Feature: The Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC).-- 42 pages, 16 figures, 3 tables, supplemental files https://doi.org/10.1525/elementa.2021.000046.-- Data accessibility statement: All data in this manuscript are publicly available from online repositories. Note that most data sets contain raw or preliminary data, while advanced versions will become available in future. The data may be found under the following references: drift track data (Figure 1, Nicolaus et al., doi:10.1594/PANGAEA.937204), observational dates (Figure 4, Nicolaus et al., doi:10.5281/zenodo.5898517), panorama photographs (Figure 5, Nicolaus et al., doi:10.1594/PANGAEA.938534), TLS data (Figure 6, Clemens-Sewall et al., doi:10.18739/A27S7HT3B), ROV radiation data (Figure 7, Nicolaus et al., doi:10.1594/PANGAEA.935688), surface albedo data on ground (Figure 8, Smith et al., broadband data under doi:10.18739/A2KK94D36 and spectral data under doi:10.18739/A2FT8DK8Z) and from the HELiX drone (Figure 8, Calmer et al., doi:10.18739/A2GH9BB0Q), on-ice RS data (Figure 10, Spreen et al., doi:10.5281/zenodo.5725870), surface images from thermal infrared and true color (Figure 11, Thielke et al, doi:10.1594/PANGAEA.934666), drift speed data from Polarstern (Figure 12, Nicolaus et al., doi:10.1594/PANGAEA.937204), deformation data from SAR (Figure 13, von Albedyll et al, doi:10.5281/zenodo.5195366), sea ice thickness and snow depth distribution (Figure 14, Hendricks et al., doi:10.5281/zenodo.5155244), sea ice physical properties (Figure 15, in Tables S2 and S3) with a sea ice core overview (Granskog et al., doi:10.5281/zenodo.4719905), snow pack properties (Figure 16, Macfarlane et al., doi:10.1594/PANGAEA.935934), and ship radar video sequence (Jäkel et al., doi:10.5446/52953) ; Year-round observations of the physical snow and ice properties and processes that govern the ice pack evolution and its interaction with the atmosphere and the ocean were conducted during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition of the research vessel Polarstern in the Arctic Ocean from October 2019 to September 2020. This work was embedded into the interdisciplinary design of the 5 MOSAiC teams, studying the atmosphere, the sea ice, the ocean, the ecosystem, and biogeochemical processes. The overall aim of the snow and sea ice observations during MOSAiC was to characterize the physical properties of the snow and ice cover comprehensively in the central Arctic over an entire annual cycle. This objective was achieved by detailed observations of physical properties and of energy and mass balance of snow and ice. By studying snow and sea ice dynamics over nested spatial scales from centimeters to tens of kilometers, the variability across scales can be considered. On-ice observations of in situ and remote sensing properties of the different surface types over all seasons will help to improve numerical process and climate models and to establish and validate novel satellite remote sensing methods; the linkages to accompanying airborne measurements, satellite observations, and results of numerical models are discussed. We found large spatial variabilities of snow metamorphism and thermal regimes impacting sea ice growth. We conclude that the highly variable snow cover needs to be considered in more detail (in observations, remote sensing, and models) to better understand snow-related feedback processes. The ice pack revealed rapid transformations and motions along the drift in all seasons. The number of coupled ice–ocean interface processes observed in detail are expected to guide upcoming research with respect to the changing Arctic sea ice ; This work was funded by the following: – the German Federal Ministry of Education and Research (BMBF) through financing the Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung (AWI) and the Polarstern expedition PS122 under the grant N-2014-H-060_Dethloff, – the AWI through its projects: AWI_ROV, AWI_ICE, AWI_SNOW, AWI_ECO. The AWI buoy program and ROV work were funded by the Helmholtz strategic investment Frontiers in Arctic Marine Monitoring (FRAM), – the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) through the Transregional Collaborative Research Centre TRR-172 "ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes, and Feedback Mechanisms (AC)3" (grant 268020496), the International Research Training Group 1904 ArcTrain (grant 221211316), the MOSAiCmicrowaveRS project (grant 420499875), the HELiPOD grant (LA 2907/11-1), and the SCASI (NI 1096/5-1 and KA 2694/7-1) and SnowCast (AR1236/1) projects, – the BMBF through the projects Diatom-ARCTIC (03F0810A), IceSense (BMBF 03F0866A and 03F0866B), MOSAiC3-IceScan (BMBF 03F0916A), NiceLABpro (BMBF 03F0867A), SSIP (01LN1701A), and SIDFExplore (03F0868A), – the German Federal Ministry for Economic Affairs and Energy through the project ArcticSense (BMWi 50EE1917A), – the US National Science Foundation (NSF) through the project PROMIS (OPP-1724467, OPP-1724540, and OPP-1724748), the buoy work (OPP-1723400), the MiSNOW (OPP-1820927), the snow transect work (OPP-1820927), the sea ice coring work (OPP-1735862), the HELiX drone operations (OPP-1805569), surface energy fluxes (OPP-1724551), Climate Active Trace Gases (OPP-1807496), and Reactive Gas Chemistry (OPP-1914781). The last 4 of these were also supported by the NOAA Physical Sciences Laboratory, – the European Union's Horizon 2020 research and innovation program projects ARICE (grant 730965) for berth fees associated with the participation of the DEARice team and INTAROS (grant 727890) supporting the drone and albedo measurements, – the US Department of Energy Atmospheric Radiation Measurement (ARM) and Atmospheric System Research (ASR) programs (DE-SC0019251, DE-SC0021341), – the National Aeronautics and Space Administration (NASA) project 80NSSC20K0658, – the European Space Agency (ESA) MOSAiC microwave radiometer (EMIRAD2, ELBARA, HUTRAD), (EMIRAD2, ELBARA, HUTRAD), CIMRex (contract 4000125503/18/NL/FF/gp) and GNSS-R (P.O. 5001025474, C.N. 4000128320/19/NL/FF/ab) GNSS-R (contracts P.O. 5001025474 and C.N. 4000128320/19/NL/FF/ab) projects, – the Canadian Space Agency FAST project (grant no. 19FACALB08), – EUMETSAT support for microwave scatterometer measurements, – the Research Council of Norway through the projects HAVOC (grant no. 280292), SIDRiFT (grant no. 287871), and CAATEX (grant no. 280531), – the Fram Centre (Tromsø, Norway), from its flagship program on Arctic Ocean through the PHOTA project, – the UKRI Natural Environment Research Council (NERC) and BMBF, who jointly funded the Changing Arctic Ocean program (project Diatom Arctic, NE/R012849/1 and 03F0810A), – the UK Natural Environment Research Council (project SSAASI-CLIM grant NE/S00257X/1), – the Agencia Estatal de Investigación AEI of Spain (grant no. PCI2019-111844-2, RTI2018-099008-B-C22), – the Swedish Research Council (VR, grant no. 2018-03859), – the Swedish Polar Research Secretariat for berth fees for MOSAiC, – the Swiss Polar Institute project SnowMOSAiC, – the Werner-Petersen-Foundation for the development of a remotely operated floating platform (grant no. FKZ 2019/610). ; Peer reviewed

[This corrects the article DOI: 10.1371/journal.pone.0256740.].

We report the discovery of a warm Neptune and a hot sub-Neptune transiting TOI-421 (BD-14 1137, TIC 94986319), a bright (V = 9.9) G9 dwarf star in a visual binary system observed by the Transiting Exoplanet Survey Satellite (TESS) space mission in Sectors 5 and 6. We performed ground-based follow-up observations-comprised of Las Cumbres Observatory Global Telescope transit photometry, NIRC2 adaptive optics imaging, and FIbre-fed Echelle Spectrograph, CORALIE, High Accuracy Radial velocity Planet Searcher, High Resolution echelle Spectrometer, and Planet Finder Spectrograph high-precision Doppler measurements-and confirmed the planetary nature of the 16 day transiting candidate announced by the TESS team. We discovered an additional radial velocity signal with a period of five days induced by the presence of a second planet in the system, which we also found to transit its host star. We found that the inner mini-Neptune, TOI-421 b, has an orbital period of P-b = 5.19672 +/- 0.00049 days, a mass of M-b = 7.17 +/- 0.66 M-circle plus, and a radius of R-b = R-circle plus, whereas the outer warm Neptune, TOI-421 c, has a period of P-c = 16.06819 +/- 0.00035 days, a mass of M-c = 16.42(-1.04)(+1.06)M(circle plus), a radius of R-c = 5.09(-0.15)(+0.16)R(circle plus), and a density of rho(c) = 0.685(-0.072)(+0.080) cm(-3). With its characteristics, the outer planet (rho(c) = 0.685(-0.0072)(+0.080) cm(-3)) is placed in the intriguing class of the super-puffy mini-Neptunes. TOI-421 b and TOI-421 c are found to be well-suited for atmospheric characterization. Our atmospheric simulations predict significant Ly alpha transit absorption, due to strong hydrogen escape in both planets, as well as the presence of detectable CH4 in the atmosphere of TOI-421 c if equilibrium chemistry is assumed. ; KESPRINT collaboration, an international consortium devoted to the characterization and research of exoplanets discovered with space-based missions NASA's Science Mission directorate NASA High-End Computing (HEC) Program through the NASA Advanced Supercomputing (NAS) Division at Ames Research Center National Aeronautics & Space Administration (NASA) European Research Council (ERC) 817540 European Research Council under the European Union's Horizon 2020 research and innovation program 832428 CRT foundation 2018.2323 Comision Nacional de Investigacion Cientifica y Tecnologica (CONICYT) CONICYT FONDECYT 3180246 Millennium Science Initiative, Chilean Ministry of Economy IC120009 Comision Nacional de Investigacion Cientifica y Tecnologica (CONICYT) CONICYT FONDECYT 1171208 Irish Research Council for Science, Engineering and Technology GOIPD/2018/659 Swedish National Space Agency DNR 65/19 136/13 Australian Research Council 170100521 NASA through Caltech/JPL grant RSA-1006130 NASA through TESS Guest Investigator Program 80NSSC19K1727 Alfred P. Sloan Foundation National Aeronautics & Space Administration (NASA) 80NSSC18K1585 80NSSC19K0379 National Science Foundation (NSF) AST1717000 Spanish Government RYC-2015-17697 FPI-SO from the Spanish Ministry of Economy and Competitiveness (MINECO) SEV-2015-0548-17-2 BES-2017-082610 National Aeronautics & Space Administration (NASA) NNX17AF27G HeisingSimons foundation PLATO grant GOLF CNES grant CONICYT-PFCHA/Doctorado Nacional, Chile 21140646 German Research Foundation (DFG) PA525/18-1 PA525/19-1 PA525/20-1 HA3279/12-1 RA714/14-1 National Aeronautics & Space Administration (NASA)

Introduction: The German PID-NET registry was founded in 2009, serving as the first national registry of patients with primary immunodeficiencies (PID) in Germany. It is part of the European Society for Immunodeficiencies (ESID) registry. The primary purpose of the registry is to gather data on the epidemiology, diagnostic delay, diagnosis, and treatment of PIDs. Methods: Clinical and laboratory data was collected from 2,453 patients from 36 German PID centres in an online registry. Data was analysed with the software Stata® and Excel. Results: The minimum prevalence of PID in Germany is 2.72 per 100,000 inhabitants. Among patients aged 1-25, there was a clear predominance of males. The median age of living patients ranged between 7 and 40 years, depending on the respective PID. Predominantly antibody disorders were the most prevalent group with 57% of all 2,453 PID patients (including 728 CVID patients). A gene defect was identified in 36% of patients. Familial cases were observed in 21% of patients. The age of onset for presenting symptoms ranged from birth to late adulthood (range 0-88 years). Presenting symptoms comprised infections (74%) and immune dysregulation (22%). Ninety-three patients were diagnosed without prior clinical symptoms. Regarding the general and clinical diagnostic delay, no PID had undergone a slight decrease within the last decade. However, both, SCID and hyper IgE- syndrome showed a substantial improvement in shortening the time between onset of symptoms and genetic diagnosis. Regarding treatment, 49% of all patients received immunoglobulin G (IgG) substitution (70%-subcutaneous; 29%-intravenous; 1%-unknown). Three-hundred patients underwent at least one hematopoietic stem cell transplantation (HSCT). Five patients had gene therapy. Conclusion: The German PID-NET registry is a precious tool for physicians, researchers, the pharmaceutical industry, politicians, and ultimately the patients, for whom the outcomes will eventually lead to a more timely diagnosis and better treatment. ; peerReviewed

Introduction: The German PID-NET registry was founded in 2009, serving as the first national registry of patients with primary immunodeficiencies (PID) in Germany. It is part of the European Society for Immunodeficiencies (ESID) registry. The primary purpose of the registry is to gather data on the epidemiology, diagnostic delay, diagnosis, and treatment of PIDs. Methods: Clinical and laboratory data was collected from 2,453 patients from 36 German PID centres in an online registry. Data was analysed with the software Stata® and Excel. Results: The minimum prevalence of PID in Germany is 2.72 per 100,000 inhabitants. Among patients aged 1–25, there was a clear predominance of males. The median age of living patients ranged between 7 and 40 years, depending on the respective PID. Predominantly antibody disorders were the most prevalent group with 57% of all 2,453 PID patients (including 728 CVID patients). A gene defect was identified in 36% of patients. Familial cases were observed in 21% of patients. The age of onset for presenting symptoms ranged from birth to late adulthood (range 0–88 years). Presenting symptoms comprised infections (74%) and immune dysregulation (22%). Ninety-three patients were diagnosed without prior clinical symptoms. Regarding the general and clinical diagnostic delay, no PID had undergone a slight decrease within the last decade. However, both, SCID and hyper IgE- syndrome showed a substantial improvement in shortening the time between onset of symptoms and genetic diagnosis. Regarding treatment, 49% of all patients received immunoglobulin G (IgG) substitution (70%—subcutaneous; 29%—intravenous; 1%—unknown). Three-hundred patients underwent at least one hematopoietic stem cell transplantation (HSCT). Five patients had gene therapy. Conclusion: The German PID-NET registry is a precious tool for physicians, researchers, the pharmaceutical industry, politicians, and ultimately the patients, for whom the outcomes will eventually lead to a more timely diagnosis and better treatment.

Introduction: The German PID-NET registry was founded in 2009, serving as the first national registry of patients with primary immunodeficiencies (PID) in Germany. It is part of the European Society for Immunodeficiencies (ESID) registry. The primary purpose of the registry is to gather data on the epidemiology, diagnostic delay, diagnosis, and treatment of PIDs. Methods: Clinical and laboratory data was collected from 2,453 patients from 36 German PID centres in an online registry. Data was analysed with the software Stata((R)) and Excel. Results: The minimum prevalence of PID in Germany is 2.72 per 100,000 inhabitants. Among patients aged 1-25, there was a clear predominance of males. The median age of living patients ranged between 7 and 40 years, depending on the respective PID. Predominantly antibody disorders were the most prevalent group with 57% of all 2,453 PID patients (including 728 CVID patients). A gene defect was identified in 36% of patients. Familial cases were observed in 21% of patients. The age of onset for presenting symptoms ranged from birth to late adulthood (range 0-88 years). Presenting symptoms comprised infections (74%) and immune dysregulation (22%). Ninety-three patients were diagnosed without prior clinical symptoms. Regarding the general and clinical diagnostic delay, no PID had undergone a slight decrease within the last decade. However, both, SCID and hyper IgE-syndrome showed a substantial improvement in shortening the time between onset of symptoms and genetic diagnosis. Regarding treatment, 49% of all patients received immunoglobulin G (IgG) substitution (70%-subcutaneous; 29%-intravenous; 1%-unknown). Three-hundred patients underwent at least one hematopoietic stem cell transplantation (HSCT). Five patients had gene therapy. Conclusion: The German PID-NET registry is a precious tool for physicians, researchers, the pharmaceutical industry, politicians, and ultimately the patients, for whom the outcomes will eventually lead to a more timely diagnosis and better treatment.

Domestication of horses fundamentally transformed long-range mobility and warfare. However, modern domesticated breeds do not descend from the earliest domestic horse lineage associated with archaeological evidence of bridling, milking and corralling at Botai, Central Asia around 3500 bc3. Other longstanding candidate regions for horse domestication, such as Iberia and Anatolia, have also recently been challenged. Thus, the genetic, geographic and temporal origins of modern domestic horses have remained unknown. Here we pinpoint the Western Eurasian steppes, especially the lower Volga-Don region, as the homeland of modern domestic horses. Furthermore, we map the population changes accompanying domestication from 273 ancient horse genomes. This reveals that modern domestic horses ultimately replaced almost all other local populations as they expanded rapidly across Eurasia from about 2000 bc, synchronously with equestrian material culture, including Sintashta spoke-wheeled chariots. We find that equestrianism involved strong selection for critical locomotor and behavioural adaptations at the GSDMC and ZFPM1 genes. Our results reject the commonly held association between horseback riding and the massive expansion of Yamnaya steppe pastoralists into Europe around 3000 bc driving the spread of Indo-European languages. This contrasts with the scenario in Asia where Indo-Iranian languages, chariots and horses spread together, following the early second millennium bc Sintashta culture. ; The work by G. Boeskorov is done on state assignment of DPMGI SB RAS. This project was supported by the University Paul Sabatier IDEX Chaire d'Excellence (OURASI); Villum Funden miGENEPI research programme; the CNRS 'Programme de Recherche Conjoint' (PRC); the CNRS International Research Project (IRP AMADEUS); the France Génomique Appel à Grand Projet (ANR-10-INBS-09-08, BUCEPHALE project); IB10131 and IB18060, both funded by Junta de Extremadura (Spain) and European Regional Development Fund; Czech Academy of Sciences (RVO:67985912); the Zoological Institute ZIN RAS (АААА-А19-119032590102-7); and King Saud University Researchers Supporting Project (NSRSP–2020/2). The research was carried out with the financial support of the Russian Foundation for Basic Research (19-59-15001 and 20-04-00213), the Russian Science Foundation (16-18-10265, 20-78-10151, and 21-18-00457), the Government of the Russian Federation (FENU-2020-0021), the Estonian Research Council (PRG29), the Estonian Ministry of Education and Research (PRG1209), the Hungarian Scientific Research Fund (Project NF 104792), the Hungarian Academy of Sciences (Momentum Mobility Research Project of the Institute of Archaeology, Research Centre for the Humanities); and the Polish National Science Centre (2013/11/B/HS3/03822). This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie (grant agreement 797449). This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreements 681605, 716732 and 834616). ; Peer reviewed

Hepatitis B virus (HBV) has been infecting humans for millennia and remains a global health problem, but its past diversity and dispersal routes are largely unknown. We generated HBV genomic data from 137 Eurasians and Native Americans dated between ~10,500 and ~400 years ago. We date the most recent common ancestor of all HBV lineages to between ~20,000 and 12,000 years ago, with the virus present in European and South American hunter-gatherers during the early Holocene. After the European Neolithic transition, Mesolithic HBV strains were replaced by a lineage likely disseminated by early farmers that prevailed throughout western Eurasia for ~4000 years, declining around the end of the 2nd millennium BCE. The only remnant of this prehistoric HBV diversity is the rare genotype G, which appears to have reemerged during the HIV pandemic. ; The research was funded by the Max Planck Society, the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (771234–PALEoRIDER, to W.H.; 805268–CoDisEASe to K. Bos; 834616–ARCHCAUCASUS to S.H.), the Slovak Academy of Sciences and the European Union's Seventh Framework Programme and Marie Curie Actions under the Programme SASPRO (1340/03/03 to P.C.R.), the ERA.NET RUS Plus–S&T programm of the European Union's Seventh Framework Programme (277–BIOARCCAUCASUS to S.Re. and S.H.), the Werner Siemens Stiftung ("Paleobiochemistry", to CW), the Award Praemium Academiae of the Czech Academy of Sciences (to M.E.), the Institute of Archaeology of the Czech Academy of Sciences (RVO 67985912, to M.Dobe.), the Russian Foundation for Basic Research (19-09-00354a, to M.K.K. and V.V.K.; 19-78-10053 to SSh), the German Research Foundation (DFG-HA-5407/4-1–INTERACT to W.H. and RE2688/2 to S.Re.), the French National Research Agency (ANR-17-FRAL-0010–INTERACT, to M.F.D., M.Ri., S.Ro., S.Sai., D.Bi., and P.Le.), the Wenner-Gren Dissertation Fieldwork Grant (9558 to S.Sab.), and the Ministry of Education and Science of the Republic of Kazakhstan (AP08856654 to L.B.D., L.M., and E.Kh. and AP08857177 to A.Z.B.).