20 research outputs found
Soil pH effects on the comparative toxicity of dissolved zinc, non-nano and nano ZnO to the earthworm Eisenia fetida
To determine how soil properties influence nanoparticle (NP) fate, bioavailability and toxicity, this study compared the toxicity of nano zinc oxide (ZnO NPs), non-nano ZnO and ionic ZnCl2 to the earthworm Eisenia fetida in a natural soil at three pH levels. NP characterisation indicated that reaction with the soil media greatly controls ZnO properties. Three main conclusions were drawn. First that Zn toxicity, especially for reproduction, was influenced by pH for all Zn forms. This can be linked to the influence of pH on Zn dissolution. Secondly, that ZnO fate, toxicity and bioaccumulation were similar (including relationships with pH) for both ZnO forms, indicating the absence of NP-specific effects. Finally, earthworm Zn concentrations were higher in worms exposed to ZnO compared to ZnCl2, despite the greater toxicity of the ionic form. This observation suggests the importance of considering the relationship between uptake and toxicity in nanotoxicology studies
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Soil pH effects on the interactions between dissolved zinc, non-nano- and nano-ZnO with soil bacterial communities
Zinc oxide nanoparticles (ZnO NPs) are used in an array of products and processes, ranging from personal care products to antifouling paints, textiles, food additives, antibacterial agents and environmental remediation processes. Soils are an environment likely to be exposed to manmade nanoparticles due to the practice of applying sewage sludge as a fertiliser or as an organic soil improver. However, understanding on the interactions between soil properties, nanoparticles and the organisms that live within soil is lacking, especially with regards to soil bacterial communities. We studied the effects of nanoparticulate, non-nanoparticulate and ionic zinc (in the form of zinc chloride) on the composition of bacterial communities in soil with a modified pH range (from pH 4.5 to pH 7.2). We observed strong pH dependent effects on the interaction between bacterial communities and all forms of zinc, with the largest changes in bacterial community composition occurring in soils with low and medium pH levels (pH 4.8 and 5.9). The high pH soil (pH 7.2) was less susceptible to the effects of zinc exposure. At the highest doses of zinc (2500 mg/kg dw soil) both nano and non-nano particulate zinc applications elicited a similar response in the soil bacterial community, and this differed significantly to the ionic zinc salt treatment. The results highlight the importance of considering soil pH in nanotoxicology studies, although further work is needed to determine the exact mechanisms controlling the toxicity and fate and interactions of nanoparticles with soil microbial communities
Meeting the Needs for Released Nanomaterials Required for Further Testing—The SUN Approach
Detailed stratified GWAS analysis for severe COVID-19 in four European populations
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
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
Soil pH effects on the comparative toxicity of dissolved zinc, non-nano and nano ZnO to the earthworm Eisenia fetida
Search for dark matter in association with an energetic photon in pp collisions at s = 13 TeV with the ATLAS detector
Abstract: A search for dark matter is conducted in final states containing a photon and missing transverse momentum in proton-proton collisions at s = 13 TeV. The data, collected during 2015–2018 by the ATLAS experiment at the CERN LHC, correspond to an integrated luminosity of 139 fb−1. No deviations from the predictions of the Standard Model are observed and 95% confidence-level upper limits between 2.45 fb and 0.5 fb are set on the visible cross section for contributions from physics beyond the Standard Model, in different ranges of the missing transverse momentum. The results are interpreted as 95% confidence-level limits in models where weakly interacting dark-matter candidates are pair-produced via an s-channel axial-vector or vector mediator. Dark-matter candidates with masses up to 415 (580) GeV are excluded for axial-vector (vector) mediators, while the maximum excluded mass of the mediator is 1460 (1470) GeV. In addition, the results are expressed in terms of 95% confidence-level limits on the parameters of a model with an axion-like particle produced in association with a photon, and are used to constrain the coupling gaZγ of an axion-like particle to the electroweak gauge bosons
Observation of WWW Production in pp Collisions at √s = 13 TeV with the ATLAS Detector
This Letter reports the observation of
W
W
W
production and a measurement of its cross section using
139
fb
−
1
of proton-proton collision data recorded at a center-of-mass energy of 13 TeV by the ATLAS detector at the Large Hadron Collider. Events with two same-sign leptons (electrons or muons) and at least two jets, as well as events with three charged leptons, are selected. A multivariate technique is then used to discriminate between signal and background events. Events from
W
W
W
production are observed with a significance of 8.0 standard deviations, where the expectation is 5.4 standard deviations. The inclusive
W
W
W
production cross section is measured to be
820
±
100
(
stat
)
±
80
(
syst
)
fb
, approximately 2.6 standard deviations from the predicted cross section of
511
±
18
fb
calculated at next-to-leading-order QCD and leading-order electroweak accuracy
An international observational study to assess the impact of the Omicron variant emergence on the clinical epidemiology of COVID-19 in hospitalised patients
Background: Whilst timely clinical characterisation of infections caused by novel SARS-CoV-2 variants is necessary for evidence-based policy response, individual-level data on infecting variants are typically only available for a minority of patients and settings.
Methods: Here, we propose an innovative approach to study changes in COVID-19 hospital presentation and outcomes after the Omicron variant emergence using publicly available population-level data on variant relative frequency to infer SARS-CoV-2 variants likely responsible for clinical cases. We apply this method to data collected by a large international clinical consortium before and after the emergence of the Omicron variant in different countries.
Results: Our analysis, that includes more than 100,000 patients from 28 countries, suggests that in many settings patients hospitalised with Omicron variant infection less often presented with commonly reported symptoms compared to patients infected with pre-Omicron variants. Patients with COVID-19 admitted to hospital after Omicron variant emergence had lower mortality compared to patients admitted during the period when Omicron variant was responsible for only a minority of infections (odds ratio in a mixed-effects logistic regression adjusted for likely confounders, 0.67 [95% confidence interval 0.61-0.75]). Qualitatively similar findings were observed in sensitivity analyses with different assumptions on population-level Omicron variant relative frequencies, and in analyses using available individual-level data on infecting variant for a subset of the study population.
Conclusions: Although clinical studies with matching viral genomic information should remain a priority, our approach combining publicly available data on variant frequency and a multi-country clinical characterisation dataset with more than 100,000 records allowed analysis of data from a wide range of settings and novel insights on real-world heterogeneity of COVID-19 presentation and clinical outcome