58 research outputs found

    Effect of feedback on delaying deterioration in quality of compressions during 2 minutes of continuous chest compressions: a randomized manikin study investigating performance with and without feedback

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>Good quality basic life support (BLS) improves outcome following cardiac arrest. As BLS performance deteriorates over time we performed a parallel group, superiority study to investigate the effect of feedback on quality of chest compression with the hypothesis that feedback delays deterioration of quality of compressions.</p> <p>Methods</p> <p>Participants attending a national one-day conference on cardiac arrest and CPR in Denmark were randomized to perform single-rescuer BLS with (n = 26) or without verbal and visual feedback (n = 28) on a manikin using a ZOLL AED plus. Data were analyzed using Rescuenet Code Review. Blinding of participants was not possible, but allocation concealment was performed. Primary outcome was the proportion of delivered compressions within target depth compared over a 2-minute period within the groups and between the groups. Secondary outcome was the proportion of delivered compressions within target rate compared over a 2-minute period within the groups and between the groups. Performance variables for 30-second intervals were analyzed and compared.</p> <p>Results</p> <p>24 (92%) and 23 (82%) had CPR experience in the group with and without feedback respectively. 14 (54%) were CPR instructors in the feedback group and 18 (64%) in the group without feedback. Data from 26 and 28 participants were analyzed respectively. Although median values for proportion of delivered compressions within target depth were higher in the feedback group (0-30 s: 54.0%; 30-60 s: 88.0%; 60-90 s: 72.6%; 90-120 s: 87.0%), no significant difference was found when compared to without feedback (0-30 s: 19.6%; 30-60 s: 33.1%; 60-90 s: 44.5%; 90-120 s: 32.7%) and no significant deteriorations over time were found within the groups. In the feedback group a significant improvement was found in the proportion of delivered compressions below target depth when the subsequent intervals were compared to the first 30 seconds (0-30 s: 3.9%; 30-60 s: 0.0%; 60-90 s: 0.0%; 90-120 s: 0.0%). Significant differences were not found in secondary outcome and in other performance variables between the groups and over time</p> <p>Conclusions</p> <p>Quality of CPR was maintained during 2 minutes of continuous compressions regardless of feedback in a group of trained rescuers.</p

    Characterizing correlations of flow oscillations at bottlenecks

    Full text link
    "Oscillations" occur in quite different kinds of many-particle-systems when two groups of particles with different directions of motion meet or intersect at a certain spot. We present a model of pedestrian motion that is able to reproduce oscillations with different characteristics. The Wald-Wolfowitz test and Gillis' correlated random walk are shown to hold observables that can be used to characterize different kinds of oscillations

    Association of Chronic Covert Cerebral Infarctions and White Matter Hyperintensities With Atrial Fibrillation Detection on Post-Stroke Cardiac Rhythm Monitoring: A Cohort Study.

    Get PDF
    Background This study was conducted to explore the association of different phenotypes, count, and location of chronic covert brain infarctions (CBIs) with detection of atrial fibrillation (AF) on prolonged post-stroke cardiac rhythm monitoring (PCM). Methods and Results We conducted a cohort single-center study of consecutive first-ever ischemic stroke or transient ischemic attack patients undergoing PCM between January 2015 and December 2017. We blindly rated CBI phenotypes according to established definitions and white matter hyperintensities (WMHs) according to the age-related white matter changes rating scale. We used (multiple) regression models to assess the association of the imaging biomarkers and incident AF on PCM. A total of 795 patients (median [interquartile range]) aged 69 (57-78) years, 41% women, median National Institutes of Health Stroke Scale score 2 (0-5), median PCM duration 14 (7-14) days, and AF detection in 61 patients (7.7%) were included. On univariate analysis, WMHs (per point odds ratio, 1.35 [95% CI, 1.03-1.78]) but not CBIs (odds ratio, 0.90 [95% CI, 0.52-1.56]) were associated with AF detection. Neither CBI phenotype, count, nor location were associated with AF detection. After adjustment for age, hypertension, and stroke severity, neither increasing WMHs (per point adjusted odds ratio, 0.85 [95% CI, 0.60-1.20]) nor CBIs (adjusted odds ratio, 0.60 [95% CI, 0.33-1.09]) were independently associated with AF detection. Conclusions Although WMHs and CBIs represent surrogate biomarkers of vascular risk factors, neither WMHs nor CBIs, including their phenotypes, count, and location, were independently associated with AF detection on PCM. In patients with manifest ischemic stroke or transient ischemic attack, the presence of imaging biomarkers of chronic ischemic injury does not seem promising to further refine prediction tools for AF detection on PCM

    Fast automated placement of polar hydrogen atoms in protein-ligand complexes

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>Hydrogen bonds play a major role in the stabilization of protein-ligand complexes. The ability of a functional group to form them depends on the position of its hydrogen atoms. An accurate knowledge of the positions of hydrogen atoms in proteins is therefore important to correctly identify hydrogen bonds and their properties. The high mobility of hydrogen atoms introduces several degrees of freedom: Tautomeric states, where a hydrogen atom alters its binding partner, torsional changes where the position of the hydrogen atom is rotated around the last heavy-atom bond in a residue, and protonation states, where the number of hydrogen atoms at a functional group may change. Also, side-chain flips in glutamine and asparagine and histidine residues, which are common crystallographic ambiguities must be identified before structure-based calculations can be conducted.</p> <p>Results</p> <p>We have implemented a method to determine the most probable hydrogen atom positions in a given protein-ligand complex. Optimality of hydrogen bond geometries is determined by an empirical scoring function which is used in molecular docking. This allows to evaluate protein-ligand interactions with an established model. Also, our method allows to resolve common crystallographic ambiguities such as as flipped amide groups and histidine residues. To ensure high speed, we make use of a dynamic programming approach.</p> <p>Conclusion</p> <p>Our results were checked against selected high-resolution structures from an external dataset, for which the positions of the hydrogen atoms have been validated manually. The quality of our results is comparable to that of other programs, with the advantage of being fast enough to be applied on-the-fly for interactive usage or during score evaluation.</p

    SUSTAIN drilling at Surtsey volcano, Iceland, tracks hydrothermal and microbiological interactions in basalt 50 years after eruption

    Get PDF
    The 2017 Surtsey Underwater volcanic System for Thermophiles, Alteration processes and INnovative concretes (SUSTAIN) drilling project at Surtsey volcano, sponsored in part by the International Continental Scientific Drilling Program (ICDP), provides precise observations of the hydrothermal, geochemical, geomagnetic, and microbiological changes that have occurred in basaltic tephra and minor intrusions since explosive and effusive eruptions produced the oceanic island in 1963–1967. Two vertically cored boreholes, to 152 and 192 m below the surface, were drilled using filtered, UV-sterilized seawater circulating fluid to minimize microbial contamination. These cores parallel a 181 m core drilled in 1979. Introductory investigations indicate changes in material properties and whole-rock compositions over the past 38 years. A Surtsey subsurface observatory installed to 181 m in one vertical borehole holds incubation experiments that monitor in situ mineralogical and microbial alteration processes at 25–124 ∘C. A third cored borehole, inclined 55∘ in a 264∘ azimuthal direction to 354 m measured depth, provides further insights into eruption processes, including the presence of a diatreme that extends at least 100 m into the seafloor beneath the Surtur crater. The SUSTAIN project provides the first time-lapse drilling record into a very young oceanic basaltic volcano over a range of temperatures, 25–141 ∘C from 1979 to 2017, and subaerial and submarine hydrothermal fluid compositions. Rigorous procedures undertaken during the drilling operation protected the sensitive environment of the Surtsey Natural Preserve

    Synthesis of 5-Hydroxyectoine from Ectoine: Crystal Structure of the Non-Heme Iron(II) and 2-Oxoglutarate-Dependent Dioxygenase EctD

    Get PDF
    As a response to high osmolality, many microorganisms synthesize various types of compatible solutes. These organic osmolytes aid in offsetting the detrimental effects of low water activity on cell physiology. One of these compatible solutes is ectoine. A sub-group of the ectoine producer's enzymatically convert this tetrahydropyrimidine into a hydroxylated derivative, 5-hydroxyectoine. This compound also functions as an effective osmostress protectant and compatible solute but it possesses properties that differ in several aspects from those of ectoine. The enzyme responsible for ectoine hydroxylation (EctD) is a member of the non-heme iron(II)-containing and 2-oxoglutarate-dependent dioxygenases (EC 1.14.11). These enzymes couple the decarboxylation of 2-oxoglutarate with the formation of a high-energy ferryl-oxo intermediate to catalyze the oxidation of the bound organic substrate. We report here the crystal structure of the ectoine hydroxylase EctD from the moderate halophile Virgibacillus salexigens in complex with Fe3+ at a resolution of 1.85 Å. Like other non-heme iron(II) and 2-oxoglutarate dependent dioxygenases, the core of the EctD structure consists of a double-stranded β-helix forming the main portion of the active-site of the enzyme. The positioning of the iron ligand in the active-site of EctD is mediated by an evolutionarily conserved 2-His-1-carboxylate iron-binding motif. The side chains of the three residues forming this iron-binding site protrude into a deep cavity in the EctD structure that also harbours the 2-oxoglutarate co-substrate-binding site. Database searches revealed a widespread occurrence of EctD-type proteins in members of the Bacteria but only in a single representative of the Archaea, the marine crenarchaeon Nitrosopumilus maritimus. The EctD crystal structure reported here can serve as a template to guide further biochemical and structural studies of this biotechnologically interesting enzyme family

    Detailed stratified GWAS analysis for severe COVID-19 in four European populations

    Get PDF
    Given the highly variable clinical phenotype of Coronavirus disease 2019 (COVID-19), a deeper analysis of the host genetic contribution to severe COVID-19 is important to improve our understanding of underlying disease mechanisms. Here, we describe an extended genome-wide association meta-analysis of a well-characterized cohort of 3255 COVID-19 patients with respiratory failure and 12 488 population controls from Italy, Spain, Norway and Germany/Austria, including stratified analyses based on age, sex and disease severity, as well as targeted analyses of chromosome Y haplotypes, the human leukocyte antigen region and the SARS-CoV-2 peptidome. By inversion imputation, we traced a reported association at 17q21.31 to a ~0.9-Mb inversion polymorphism that creates two highly differentiated haplotypes and characterized the potential effects of the inversion in detail. Our data, together with the 5th release of summary statistics from the COVID-19 Host Genetics Initiative including non-Caucasian individuals, also identified a new locus at 19q13.33, including NAPSA, a gene which is expressed primarily in alveolar cells responsible for gas exchange in the lung.S.E.H. and C.A.S. partially supported genotyping through a philanthropic donation. A.F. and D.E. were supported by a grant from the German Federal Ministry of Education and COVID-19 grant Research (BMBF; ID:01KI20197); A.F., D.E. and F.D. were supported by the Deutsche Forschungsgemeinschaft Cluster of Excellence ‘Precision Medicine in Chronic Inflammation’ (EXC2167). D.E. was supported by the German Federal Ministry of Education and Research (BMBF) within the framework of the Computational Life Sciences funding concept (CompLS grant 031L0165). D.E., K.B. and S.B. acknowledge the Novo Nordisk Foundation (NNF14CC0001 and NNF17OC0027594). T.L.L., A.T. and O.Ö. were funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), project numbers 279645989; 433116033; 437857095. M.W. and H.E. are supported by the German Research Foundation (DFG) through the Research Training Group 1743, ‘Genes, Environment and Inflammation’. L.V. received funding from: Ricerca Finalizzata Ministero della Salute (RF-2016-02364358), Italian Ministry of Health ‘CV PREVITAL’—strategie di prevenzione primaria cardiovascolare primaria nella popolazione italiana; The European Union (EU) Programme Horizon 2020 (under grant agreement No. 777377) for the project LITMUS- and for the project ‘REVEAL’; Fondazione IRCCS Ca’ Granda ‘Ricerca corrente’, Fondazione Sviluppo Ca’ Granda ‘Liver-BIBLE’ (PR-0391), Fondazione IRCCS Ca’ Granda ‘5permille’ ‘COVID-19 Biobank’ (RC100017A). A.B. was supported by a grant from Fondazione Cariplo to Fondazione Tettamanti: ‘Bio-banking of Covid-19 patient samples to support national and international research (Covid-Bank). This research was partly funded by an MIUR grant to the Department of Medical Sciences, under the program ‘Dipartimenti di Eccellenza 2018–2022’. This study makes use of data generated by the GCAT-Genomes for Life. Cohort study of the Genomes of Catalonia, Fundació IGTP (The Institute for Health Science Research Germans Trias i Pujol) IGTP is part of the CERCA Program/Generalitat de Catalunya. GCAT is supported by Acción de Dinamización del ISCIII-MINECO and the Ministry of Health of the Generalitat of Catalunya (ADE 10/00026); the Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR) (2017-SGR 529). M.M. received research funding from grant PI19/00335 Acción Estratégica en Salud, integrated in the Spanish National RDI Plan and financed by ISCIII-Subdirección General de Evaluación and the Fondo Europeo de Desarrollo Regional (European Regional Development Fund (FEDER)-Una manera de hacer Europa’). B.C. is supported by national grants PI18/01512. X.F. is supported by the VEIS project (001-P-001647) (co-funded by the European Regional Development Fund (ERDF), ‘A way to build Europe’). Additional data included in this study were obtained in part by the COVICAT Study Group (Cohort Covid de Catalunya) supported by IsGlobal and IGTP, European Institute of Innovation & Technology (EIT), a body of the European Union, COVID-19 Rapid Response activity 73A and SR20-01024 La Caixa Foundation. A.J. and S.M. were supported by the Spanish Ministry of Economy and Competitiveness (grant numbers: PSE-010000-2006-6 and IPT-010000-2010-36). A.J. was also supported by national grant PI17/00019 from the Acción Estratégica en Salud (ISCIII) and the European Regional Development Fund (FEDER). The Basque Biobank, a hospital-related platform that also involves all Osakidetza health centres, the Basque government’s Department of Health and Onkologikoa, is operated by the Basque Foundation for Health Innovation and Research-BIOEF. M.C. received Grants BFU2016-77244-R and PID2019-107836RB-I00 funded by the Agencia Estatal de Investigación (AEI, Spain) and the European Regional Development Fund (FEDER, EU). M.R.G., J.A.H., R.G.D. and D.M.M. are supported by the ‘Spanish Ministry of Economy, Innovation and Competition, the Instituto de Salud Carlos III’ (PI19/01404, PI16/01842, PI19/00589, PI17/00535 and GLD19/00100) and by the Andalussian government (Proyectos Estratégicos-Fondos Feder PE-0451-2018, COVID-Premed, COVID GWAs). The position held by Itziar de Rojas Salarich is funded by grant FI20/00215, PFIS Contratos Predoctorales de Formación en Investigación en Salud. Enrique Calderón’s team is supported by CIBER of Epidemiology and Public Health (CIBERESP), ‘Instituto de Salud Carlos III’. J.C.H. reports grants from Research Council of Norway grant no 312780 during the conduct of the study. E.S. reports grants from Research Council of Norway grant no. 312769. The BioMaterialBank Nord is supported by the German Center for Lung Research (DZL), Airway Research Center North (ARCN). The BioMaterialBank Nord is member of popgen 2.0 network (P2N). P.K. Bergisch Gladbach, Germany and the Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany. He is supported by the German Federal Ministry of Education and Research (BMBF). O.A.C. is supported by the German Federal Ministry of Research and Education and is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy—CECAD, EXC 2030–390661388. The COMRI cohort is funded by Technical University of Munich, Munich, Germany. This work was supported by grants of the Rolf M. Schwiete Stiftung, the Saarland University, BMBF and The States of Saarland and Lower Saxony. K.U.L. is supported by the German Research Foundation (DFG, LU-1944/3-1). Genotyping for the BoSCO study is funded by the Institute of Human Genetics, University Hospital Bonn. F.H. was supported by the Bavarian State Ministry for Science and Arts. Part of the genotyping was supported by a grant to A.R. from the German Federal Ministry of Education and Research (BMBF, grant: 01ED1619A, European Alzheimer DNA BioBank, EADB) within the context of the EU Joint Programme—Neurodegenerative Disease Research (JPND). Additional funding was derived from the German Research Foundation (DFG) grant: RA 1971/6-1 to A.R. P.R. is supported by the DFG (CCGA Sequencing Centre and DFG ExC2167 PMI and by SH state funds for COVID19 research). F.T. is supported by the Clinician Scientist Program of the Deutsche Forschungsgemeinschaft Cluster of Excellence ‘Precision Medicine in Chronic Inflammation’ (EXC2167). C.L. and J.H. are supported by the German Center for Infection Research (DZIF). T.B., M.M.B., O.W. und A.H. are supported by the Stiftung Universitätsmedizin Essen. M.A.-H. was supported by Juan de la Cierva Incorporacion program, grant IJC2018-035131-I funded by MCIN/AEI/10.13039/501100011033. E.C.S. is supported by the Deutsche Forschungsgemeinschaft (DFG; SCHU 2419/2-1).Peer reviewe

    Detailed stratified GWAS analysis for severe COVID-19 in four European populations

    Get PDF
    Given the highly variable clinical phenotype of Coronavirus disease 2019 (COVID-19), a deeper analysis of the host genetic contribution to severe COVID-19 is important to improve our understanding of underlying disease mechanisms. Here, we describe an extended GWAS meta-analysis of a well-characterized cohort of 3,260 COVID-19 patients with respiratory failure and 12,483 population controls from Italy, Spain, Norway and Germany/Austria, including stratified analyses based on age, sex and disease severity, as well as targeted analyses of chromosome Y haplotypes, the human leukocyte antigen (HLA) region and the SARS-CoV-2 peptidome. By inversion imputation, we traced a reported association at 17q21.31 to a highly pleiotropic ∼0.9-Mb inversion polymorphism and characterized the potential effects of the inversion in detail. Our data, together with the 5th release of summary statistics from the COVID-19 Host Genetics Initiative, also identified a new locus at 19q13.33, including NAPSA, a gene which is expressed primarily in alveolar cells responsible for gas exchange in the lung.Andre Franke and David Ellinghaus were supported by a grant from the German Federal Ministry of Education and Research (01KI20197), Andre Franke, David Ellinghaus and Frauke Degenhardt were supported by the Deutsche Forschungsgemeinschaft Cluster of Excellence “Precision Medicine in Chronic Inflammation” (EXC2167). David Ellinghaus was supported by the German Federal Ministry of Education and Research (BMBF) within the framework of the Computational Life Sciences funding concept (CompLS grant 031L0165). David Ellinghaus, Karina Banasik and Søren Brunak acknowledge the Novo Nordisk Foundation (grant NNF14CC0001 and NNF17OC0027594). Tobias L. Lenz, Ana Teles and Onur Özer were funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation), project numbers 279645989; 433116033; 437857095. Mareike Wendorff and Hesham ElAbd are supported by the German Research Foundation (DFG) through the Research Training Group 1743, "Genes, Environment and Inflammation". This project was supported by a Covid-19 grant from the German Federal Ministry of Education and Research (BMBF; ID: 01KI20197). Luca Valenti received funding from: Ricerca Finalizzata Ministero della Salute RF2016-02364358, Italian Ministry of Health ""CV PREVITAL – strategie di prevenzione primaria cardiovascolare primaria nella popolazione italiana; The European Union (EU) Programme Horizon 2020 (under grant agreement No. 777377) for the project LITMUS- and for the project ""REVEAL""; Fondazione IRCCS Ca' Granda ""Ricerca corrente"", Fondazione Sviluppo Ca' Granda ""Liver-BIBLE"" (PR-0391), Fondazione IRCCS Ca' Granda ""5permille"" ""COVID-19 Biobank"" (RC100017A). Andrea Biondi was supported by the grant from Fondazione Cariplo to Fondazione Tettamanti: "Biobanking of Covid-19 patient samples to support national and international research (Covid-Bank). This research was partly funded by a MIUR grant to the Department of Medical Sciences, under the program "Dipartimenti di Eccellenza 2018–2022". This study makes use of data generated by the GCAT-Genomes for Life. Cohort study of the Genomes of Catalonia, Fundació IGTP. IGTP is part of the CERCA Program / Generalitat de Catalunya. GCAT is supported by Acción de Dinamización del ISCIIIMINECO and the Ministry of Health of the Generalitat of Catalunya (ADE 10/00026); the Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR) (2017-SGR 529). Marta Marquié received research funding from ant PI19/00335 Acción Estratégica en Salud, integrated in the Spanish National RDI Plan and financed by ISCIIISubdirección General de Evaluación and the Fondo Europeo de Desarrollo Regional (FEDER-Una manera de hacer Europa").Beatriz Cortes is supported by national grants PI18/01512. Xavier Farre is supported by VEIS project (001-P-001647) (cofunded by European Regional Development Fund (ERDF), “A way to build Europe”). Additional data included in this study was obtained in part by the COVICAT Study Group (Cohort Covid de Catalunya) supported by IsGlobal and IGTP, EIT COVID-19 Rapid Response activity 73A and SR20-01024 La Caixa Foundation. Antonio Julià and Sara Marsal were supported by the Spanish Ministry of Economy and Competitiveness (grant numbers: PSE-010000-2006-6 and IPT-010000-2010-36). Antonio Julià was also supported the by national grant PI17/00019 from the Acción Estratégica en Salud (ISCIII) and the FEDER. The Basque Biobank is a hospitalrelated platform that also involves all Osakidetza health centres, the Basque government's Department of Health and Onkologikoa, is operated by the Basque Foundation for Health Innovation and Research-BIOEF. Mario Cáceres received Grants BFU2016-77244-R and PID2019-107836RB-I00 funded by the Agencia Estatal de Investigación (AEI, Spain) and the European Regional Development Fund (FEDER, EU). Manuel Romero Gómez, Javier Ampuero Herrojo, Rocío Gallego Durán and Douglas Maya Miles are supported by the “Spanish Ministry of Economy, Innovation and Competition, the Instituto de Salud Carlos III” (PI19/01404, PI16/01842, PI19/00589, PI17/00535 and GLD19/00100), and by the Andalussian government (Proyectos Estratégicos-Fondos Feder PE-0451-2018, COVID-Premed, COVID GWAs). The position held by Itziar de Rojas Salarich is funded by grant FI20/00215, PFIS Contratos Predoctorales de Formación en Investigación en Salud. Enrique Calderón's team is supported by CIBER of Epidemiology and Public Health (CIBERESP), "Instituto de Salud Carlos III". Jan Cato Holter reports grants from Research Council of Norway grant no 312780 during the conduct of the study. Dr. Solligård: reports grants from Research Council of Norway grant no 312769. The BioMaterialBank Nord is supported by the German Center for Lung Research (DZL), Airway Research Center North (ARCN). The BioMaterialBank Nord is member of popgen 2.0 network (P2N). Philipp Koehler has received non-financial scientific grants from Miltenyi Biotec GmbH, Bergisch Gladbach, Germany, and the Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases, University of Cologne, Cologne, Germany. He is supported by the German Federal Ministry of Education and Research (BMBF).Oliver A. Cornely is supported by the German Federal Ministry of Research and Education and is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy – CECAD, EXC 2030 – 390661388. The COMRI cohort is funded by Technical University of Munich, Munich, Germany. Genotyping was performed by the Genotyping laboratory of Institute for Molecular Medicine Finland FIMM Technology Centre, University of Helsinki. This work was supported by grants of the Rolf M. Schwiete Stiftung, the Saarland University, BMBF and The States of Saarland and Lower Saxony. Kerstin U. Ludwig is supported by the German Research Foundation (DFG, LU-1944/3-1). Genotyping for the BoSCO study is funded by the Institute of Human Genetics, University Hospital Bonn. Frank Hanses was supported by the Bavarian State Ministry for Science and Arts. Part of the genotyping was supported by a grant to Alfredo Ramirez from the German Federal Ministry of Education and Research (BMBF, grant: 01ED1619A, European Alzheimer DNA BioBank, EADB) within the context of the EU Joint Programme – Neurodegenerative Disease Research (JPND). Additional funding was derived from the German Research Foundation (DFG) grant: RA 1971/6-1 to Alfredo Ramirez. Philip Rosenstiel is supported by the DFG (CCGA Sequencing Centre and DFG ExC2167 PMI and by SH state funds for COVID19 research). Florian Tran is supported by the Clinician Scientist Program of the Deutsche Forschungsgemeinschaft Cluster of Excellence “Precision Medicine in Chronic Inflammation” (EXC2167). Christoph Lange and Jan Heyckendorf are supported by the German Center for Infection Research (DZIF). Thorsen Brenner, Marc M Berger, Oliver Witzke und Anke Hinney are supported by the Stiftung Universitätsmedizin Essen. Marialbert Acosta-Herrera was supported by Juan de la Cierva Incorporacion program, grant IJC2018-035131-I funded by MCIN/AEI/10.13039/501100011033. Eva C Schulte is supported by the Deutsche Forschungsgemeinschaft (DFG; SCHU 2419/2-1).N
    corecore