34 research outputs found

    Does Facemask Impact Diagnostic During Pulmonary Auscultation?

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    peer reviewedFacemasks have been widely used in hospitals, especially since the emergence of the coronavirus 2019 (COVID-19) pandemic, often severely affecting respiratory functions. Masks protect patients from contagious airborne transmission, and are thus more specifically important for chronic respiratory disease (CRD) patients. However, masks also increase air resistance and thus work of breathing, which may impact pulmonary auscultation and diagnostic acuity, the primary respiratory examination. This study is the first to assess the impact of facemasks on clinical auscultation diagnostic. Lung sounds from 29 patients were digitally recorded using an electronic stethoscope. For each patient, one recording was taken wearing a surgical mask and one without. Recorded signals were segmented in breath cycles using an autocorrelation algorithm. In total, 87 breath cycles were identified from sounds with mask, and 82 without mask. Time-frequency analysis of the signals was used to extract comparison features such as peak frequency, median frequency, band power, or spectral integration. All the features extracted in frequency content, its evolution, or power did not significantly differ between respiratory cycles with or without mask. This early stage study thus suggests minor impact on clinical diagnostic outcomes in pulmonary auscultation. However, further analysis is necessary such as on adventitious sounds characteristics differences with or without mask, to determine if facemask could lead to no discernible diagnostic outcome in clinical practice

    The SARS-CoV-2 viral load in COVID-19 patients is lower on face mask filters than on nasopharyngeal swabs.

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    Face masks and personal respirators are used to curb the transmission of SARS-CoV-2 in respiratory droplets; filters embedded in some personal protective equipment could be used as a non-invasive sample source for applications, including at-home testing, but information is needed about whether filters are suited to capture viral particles for SARS-CoV-2 detection. In this study, we generated inactivated virus-laden aerosols of 0.3-2 microns in diameter (0.9 µm mean diameter by mass) and dispersed the aerosolized viral particles onto electrostatic face mask filters. The limit of detection for inactivated coronaviruses SARS-CoV-2 and HCoV-NL63 extracted from filters was between 10 to 100 copies/filter for both viruses. Testing for SARS-CoV-2, using face mask filters and nasopharyngeal swabs collected from hospitalized COVID-19-patients, showed that filter samples offered reduced sensitivity (8.5% compared to nasopharyngeal swabs). The low concordance of SARS-CoV-2 detection between filters and nasopharyngeal swabs indicated that number of viral particles collected on the face mask filter was below the limit of detection for all patients but those with the highest viral loads. This indicated face masks are unsuitable to replace diagnostic nasopharyngeal swabs in COVID-19 diagnosis. The ability to detect nucleic acids on face mask filters may, however, find other uses worth future investigation

    New Trends in Beverage Packaging Systems: A Review

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    New trends in beverage packaging are focusing on the structure modification of packaging materials and the development of new active and/or intelligent systems, which can interact with the product or its environment, improving the conservation of beverages, such as wine, juice or beer, customer acceptability, and food security. In this paper, the main nutritional and organoleptic degradation processes of beverages, such as oxidative degradation or changes in the aromatic profiles, which influence their color and volatile composition are summarized. Finally, the description of the current situation of beverage packaging materials and new possible, emerging strategies to overcome some of the pending issues are discussed

    Can predicting COVID-19 mortality in a European cohort using only demographic and comorbidity data surpass age-based prediction: An externally validated study.

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    peer reviewedOBJECTIVE: To establish whether one can build a mortality prediction model for COVID-19 patients based solely on demographics and comorbidity data that outperforms age alone. Such a model could be a precursor to implementing smart lockdowns and vaccine distribution strategies. METHODS: The training cohort comprised 2337 COVID-19 inpatients from nine hospitals in The Netherlands. The clinical outcome was death within 21 days of being discharged. The features were derived from electronic health records collected during admission. Three feature selection methods were used: LASSO, univariate using a novel metric, and pairwise (age being half of each pair). 478 patients from Belgium were used to test the model. All modeling attempts were compared against an age-only model. RESULTS: In the training cohort, the mortality group's median age was 77 years (interquartile range = 70-83), higher than the non-mortality group (median = 65, IQR = 55-75). The incidence of former/active smokers, male gender, hypertension, diabetes, dementia, cancer, chronic obstructive pulmonary disease, chronic cardiac disease, chronic neurological disease, and chronic kidney disease was higher in the mortality group. All stated differences were statistically significant after Bonferroni correction. LASSO selected eight features, novel univariate chose five, and pairwise chose none. No model was able to surpass an age-only model in the external validation set, where age had an AUC of 0.85 and a balanced accuracy of 0.77. CONCLUSION: When applied to an external validation set, we found that an age-only mortality model outperformed all modeling attempts (curated on www.covid19risk.ai) using three feature selection methods on 22 demographic and comorbid features

    Age-dependent impact of the major common genetic risk factor for COVID-19 on severity and mortality

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    AG has received support by NordForsk Nordic Trial Alliance (NTA) grant, by Academy of Finland Fellow grant N. 323116 and the Academy of Finland for PREDICT consortium N. 340541. The Richards research group is supported by the Canadian Institutes of Health Research (CIHR) (365825 and 409511), the Lady Davis Institute of the Jewish General Hospital, the Canadian Foundation for Innovation (CFI), the NIH Foundation, Cancer Research UK, Genome Québec, the Public Health Agency of Canada, the McGill Interdisciplinary Initiative in Infection and Immunity and the Fonds de Recherche Québec Santé (FRQS). TN is supported by a research fellowship of the Japan Society for the Promotion of Science for Young Scientists. GBL is supported by a CIHR scholarship and a joint FRQS and Québec Ministry of Health and Social Services scholarship. JBR is supported by an FRQS Clinical Research Scholarship. Support from Calcul Québec and Compute Canada is acknowledged. TwinsUK is funded by the Welcome Trust, the Medical Research Council, the European Union, the National Institute for Health Research-funded BioResource and the Clinical Research Facility and Biomedical Research Centre based at Guy’s and St. Thomas’ NHS Foundation Trust in partnership with King’s College London. The Biobanque Québec COVID19 is funded by FRQS, Genome Québec and the Public Health Agency of Canada, the McGill Interdisciplinary Initiative in Infection and Immunity and the Fonds de Recherche Québec Santé. These funding agencies had no role in the design, implementation or interpretation of this study. The COVID19-Host(a)ge study received infrastructure support from the DFG Cluster of Excellence 2167 “Precision Medicine in Chronic Inflammation (PMI)” (DFG Grant: “EXC2167”). The COVID19-Host(a)ge study 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). Genotyping in COVID19-Host(a)ge was supported by a philantropic donation from Stein Erik Hagen. The COVID GWAs, Premed COVID-19 study (COVID19-Host(a)ge_3) was supported by "Grupo de Trabajo en Medicina Personalizada contra el COVID-19 de Andalucia"and also by the Instituto de Salud Carlos III (CIBERehd and CIBERER). Funding comes from COVID-19-GWAS, COVID-PREMED initiatives. Both of them are supported by "Consejeria de Salud y Familias" of the Andalusian Government. DMM is currently funded by the the Andalussian government (Proyectos Estratégicos-Fondos Feder PE-0451-2018). The Columbia University Biobank was supported by Columbia University and the National Center for Advancing Translational Sciences, NIH, through Grant Number UL1TR001873. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH or Columbia University. The SPGRX study was supported by the Consejería de Economía, Conocimiento, Empresas y Universidad #CV20-10150. The GEN-COVID study was funded by: the MIUR grant “Dipartimenti di Eccellenza 2018-2020” to the Department of Medical Biotechnologies University of Siena, Italy; the “Intesa San Paolo 2020 charity fund” dedicated to the project NB/2020/0119; and philanthropic donations to the Department of Medical Biotechnologies, University of Siena for the COVID-19 host genetics research project (D.L n.18 of March 17, 2020). Part of this research project is also funded by Tuscany Region “Bando Ricerca COVID-19 Toscana” grant to the Azienda Ospedaliero Universitaria Senese (CUP I49C20000280002). Authors are grateful to: the CINECA consortium for providing computational resources; the Network for Italian Genomes (NIG) (http://www.nig.cineca.it) for its support; the COVID-19 Host Genetics Initiative (https://www.covid19hg.org/); the Genetic Biobank of Siena, member of BBMRI-IT, Telethon Network of Genetic Biobanks (project no. GTB18001), EuroBioBank, and RD-Connect, for managing specimens. Genetics against coronavirus (GENIUS), Humanitas University (COVID19-Host(a)ge_4) was supported by Ricerca Corrente (Italian Ministry of Health), intramural funding (Fondazione Humanitas per la Ricerca). The generous contribution of Banca Intesa San Paolo and of the Dolce&Gabbana Fashion Firm is gratefully acknowledged. Data acquisition and sample processing was supported by COVID-19 Biobank, Fondazione IRCCS Cà Granda Milano; LV group was supported by MyFirst Grant AIRC n.16888, Ricerca Finalizzata Ministero della Salute RF-2016-02364358, Ricerca corrente Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, the European Union (EU) Programme Horizon 2020 (under grant agreement No. 777377) for the project LITMUS- “Liver Investigation: Testing Marker Utility in Steatohepatitis”, Programme “Photonics” under grant agreement “101016726” for the project “REVEAL: Neuronal microscopy for cell behavioural examination and manipulation”, Fondazione Patrimonio Ca’ Granda “Liver Bible” PR-0361. DP was supported by Ricerca corrente Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, CV PREVITAL “Strategie di prevenzione primaria nella popolazione Italiana” Ministero della Salute, and Associazione Italiana per la Prevenzione dell’Epatite Virale (COPEV). Genetic modifiers for COVID-19 related illness (BeLCovid_1) was supported by the "Fonds Erasme". The Host genetics and immune response in SARS-Cov-2 infection (BelCovid_2) study was supported by grants from Fondation Léon Fredericq and from Fonds de la Recherche Scientifique (FNRS). The INMUNGEN-CoV2 study was funded by the Consejo Superior de Investigaciones Científicas. KUL is supported by the German Research Foundation (LU 1944/3-1) SweCovid is funded by the SciLifeLab/KAW national COVID-19 research program project grant to Michael Hultström (KAW 2020.0182) and the Swedish Research Council to Robert Frithiof (2014-02569 and 2014-07606). HZ is supported by Jeansson Stiftelser, Magnus Bergvalls Stiftelse. The COMRI cohort is funded by Technical University of Munich, Munich, Germany. Genotyping for the COMRI cohort was performed and funded by the Genotyping Laboratory of Institute for Molecular Medicine Finland FIMM Technology Centre, University of Helsinki, Helsinki, Finland. These funding agencies had no role in the design, implementation or interpretation of this study.Background: There is considerable variability in COVID-19 outcomes amongst younger adults—and some of this variation may be due to genetic predisposition. We characterized the clinical implications of the major genetic risk factor for COVID-19 severity, and its age-dependent effect, using individual-level data in a large international multi-centre consortium. Method: The major common COVID-19 genetic risk factor is a chromosome 3 locus, tagged by the marker rs10490770. We combined individual level data for 13,424 COVID-19 positive patients (N=6,689 hospitalized) from 17 cohorts in nine countries to assess the association of this genetic marker with mortality, COVID-19-related complications and laboratory values. We next examined if the magnitude of these associations varied by age and were independent from known clinical COVID-19 risk factors. Findings: We found that rs10490770 risk allele carriers experienced an increased risk of all-cause mortality (hazard ratio [HR] 1·4, 95% confidence interval [CI] 1·2–1·6) and COVID-19 related mortality (HR 1·5, 95%CI 1·3–1·8). Risk allele carriers had increased odds of several COVID-19 complications: severe respiratory failure (odds ratio [OR] 2·0, 95%CI 1·6-2·6), venous thromboembolism (OR 1·7, 95%CI 1·2-2·4), and hepatic injury (OR 1·6, 95%CI 1·2-2·0). Risk allele carriers ≤ 60 years had higher odds of death or severe respiratory failure (OR 2·6, 95%CI 1·8-3·9) compared to those > 60 years OR 1·5 (95%CI 1·3-1·9, interaction p-value=0·04). Amongst individuals ≤ 60 years who died or experienced severe respiratory COVID-19 outcome, we found that 31·8% (95%CI 27·6-36·2) were risk variant carriers, compared to 13·9% (95%CI 12·6-15·2%) of those not experiencing these outcomes. Prediction of death or severe respiratory failure among those ≤ 60 years improved when including the risk allele (AUC 0·82 vs 0·84, p=0·016) and the prediction ability of rs10490770 risk allele was similar to, or better than, most established clinical risk factors. Interpretation: The major common COVID-19 risk locus on chromosome 3 is associated with increased risks of morbidity and mortality—and these are more pronounced amongst individuals ≤ 60 years. The effect on COVID-19 severity was similar to, or larger than most established risk factors, suggesting potential implications for clinical risk management.Academy of Finland Fellow grant N. 323116Academy of Finland for PREDICT consortium N. 340541.Canadian Institutes of Health Research (CIHR) (365825 and 409511)Lady Davis Institute of the Jewish General HospitalCanadian Foundation for Innovation (CFI)NIH FoundationCancer Research UKGenome QuébecPublic Health Agency of CanadaMcGill Interdisciplinary Initiative in Infection and Immunity and the Fonds de Recherche Québec Santé (FRQS)Japan Society for the Promotion of Science for Young ScientistsCIHR scholarship and a joint FRQS and Québec Ministry of Health and Social Services scholarshipFRQS Clinical Research ScholarshipCalcul QuébecCompute CanadaWelcome TrustMedical Research CouncEuropean UnionNational Institute for Health Research-funded BioResourceClinical Research Facility and Biomedical Research Centre based at Guy’s and St. Thomas’ NHS Foundation TrustKing’s College LondonGenome QuébecPublic Health Agency of CanadaMcGill Interdisciplinary Initiative in Infection and ImmunityFonds de Recherche Québec Santé(DFG Grant: “EXC2167”)(CompLS grant 031L0165)Stein Erik Hagen"Grupo de Trabajo en Medicina Personalizada contra el COVID-19 de Andalucia"Instituto de Salud Carlos III (CIBERehd and CIBERER)COVID-19-GWASCOVID-PREMED initiatives"Consejeria de Salud y Familias" of the Andalusian GovernmentAndalusian government (Proyectos Estratégicos-Fondos Feder PE-0451-2018)Columbia UniversityNational Center for Advancing Translational SciencesNIH Grant Number UL1TR001873Consejería de Economía, Conocimiento, Empresas y Universidad #CV20-10150MIUR grant “Dipartimenti di Eccellenza 2018-2020”“Intesa San Paolo 2020 charity fund” dedicated to the project NB/2020/0119Tuscany Region “Bando Ricerca COVID-19 Toscana”CINECA consortiumNetwork for Italian Genomes (NIG)COVID-19 Host Genetics InitiativeGenetic Biobank of SienaEuroBioBankRD-ConnectRicerca Corrente (Italian Ministry of Health)Fondazione Humanitas per la RicercaBanca Intesa San PaoloDolce&Gabbana Fashion FirmCOVID-19 BiobankFondazione IRCCS Cà Granda MilanoMyFirst Grant AIRC n.16888Ricerca Finalizzata Ministero della Salute RF-2016-02364358Ricerca corrente Fondazione IRCCS Ca’ Granda Ospedale Maggiore PoliclinicoEuropean Union (EU) Programme Horizon 2020 (under grant agreement No. 777377)“Photonics” “101016726”Fondazione Patrimonio Ca’ Granda “Liver Bible” PR-0361CV PREVITAL “Strategie di prevenzione primaria nella popolazione Italiana” Ministero della Salute, and Associazione Italiana per la Prevenzione dell’Epatite Virale (COPEV)"Fonds Erasme"Fondation Léon FredericqFonds de la Recherche Scientifique (FNRS)Consejo Superior de Investigaciones CientíficasGerman Research Foundation (LU 1944/3-1)SciLifeLab/KAW national COVID-19 research program project (KAW 2020.0182)Swedish Research Council (2014-02569 and 2014-07606)Jeansson Stiftelser, Magnus Bergvalls StiftelseTechnical University of Munich, Munich, GermanyGenotyping Laboratory of Institute for Molecular Medicine Finland FIMM Technology Centre, University of Helsinki, Helsinki, Finlan

    SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

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    Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

    Riociguat treatment in patients with chronic thromboembolic pulmonary hypertension: Final safety data from the EXPERT registry

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    Objective: The soluble guanylate cyclase stimulator riociguat is approved for the treatment of adult patients with pulmonary arterial hypertension (PAH) and inoperable or persistent/recurrent chronic thromboembolic pulmonary hypertension (CTEPH) following Phase

    A first update on mapping the human genetic architecture of COVID-19

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