Rosa × damascena Herrm. essential oil: anti-tyrosinase activity and phytochemical composition

Tyrosinase is a key enzyme in melanin synthesis, and its natural inhibitors are receiving increasing attention. Rosa × damascena Herrm. essential oil (RDEO), as important functional metabolites, was widely known due to its biological activities. But its tyrosinase inhibitory activity has not been detailed investigated. Therefore, in this paper, RDEO was comprehensively investigated the tyrosinase inhibitory, followed by the phytochemical composition analysis. Activity screening results showed that RDEO exhibited effective anti-tyrosinase activity and was a reversible and mixed-type inhibitor. CD assay results revealed that RDEO could affect the conformation of tyrosinase to reduce the activity. In B16F10 cells, RDEO (25–100 μg/mL) could inhibit intracellular tyrosinase activity and decrease melanin content. Finally, GC-MS analysis of RDEO found that citronellol (21.22%), geraniol (14.1%), eicosane (11.03%), heneicosane (6.65%) and 1-nonadecene (5.16%) were its main phytochemical compositions. This study provided data support for Rosa × damascena Herrm. essential oil as one potential natural tyrosinase inhibitor and its applications in cosmetics and medicine

A semi-quantitative upconversion nanoparticle-based immunochromatographic assay for SARS-CoV-2 antigen detection

The unprecedented public health and economic impact of the coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has been met with an equally unprecedented scientific response. Sensitive point-of-care methods to detect SARS-CoV-2 antigens in clinical specimens are urgently required for the rapid screening of individuals with viral infection. Here, we developed an upconversion nanoparticle-based lateral flow immunochromatographic assay (UCNP-LFIA) for the high-sensitivity detection of SARS-CoV-2 nucleocapsid (N) protein. A pair of rabbit SARS-CoV-2 N-specific monoclonal antibodies was conjugated to UCNPs, and the prepared UCNPs were then deposited into the LFIA test strips for detecting and capturing the N protein. Under the test conditions, the limit of detection (LOD) of UCNP-LFIA for the N protein was 3.59 pg/mL, with a linear range of 0.01–100 ng/mL. Compared with that of the current colloidal gold-based LFIA strips, the LOD of the UCNP-LFIA-based method was increased by 100-fold. The antigen recovery rate of the developed method in the simulated pharyngeal swab samples ranged from 91.1 to 117.3%. Furthermore, compared with the reverse transcription-polymerase chain reaction, the developed UCNP-LFIA method showed a sensitivity of 94.73% for 19 patients with COVID-19. Thus, the newly established platform could serve as a promising and convenient fluorescent immunological sensing approach for the efficient screening and diagnosis of COVID-19

Metabolic and transcriptomic responses of Taxus mairei to nano-pollutants: insights into AgNPs and PsNPs impact

There is a growing global concern regarding the pervasive issue of nano-pollutants. Typical nano-materials, such as polystyrene nanoplastics (PsNPs) and silver nanoparticles (AgNPs), pose significant risks to ecosystems and human health. Taxus mairei is a well-known gymnosperm widely planted in South China and has great medicinal qualities. However, the effects of nano pollutants on the primary and secondary metabolism of Taxus plants have not been sufficiently explored. We investigated the responses of T. mairei to different nano-pollutants via physiological, transcriptomic, and metabolomic analyses. AgNPs and PsNPs significantly affected several secondary and energy metabolism-related pathways, respectively. In T. mairei, AgNPs greatly impacted flavonoid metabolism by regulating the expression of the CHI gene, while PsNPs significantly impacted energy metabolism by regulating the expression of FRK genes. Furthermore, a transcriptional regulation network, including GATA (ctg10916_gene.2), bHLH (ctg495_gene.7), MYB (ctg18368_gene.1), and NAC (ctg8193_gene.1), was predicted to be associated with the responses of T. mairei to nano-pollutants. The present study elucidated a regulatory mechanism underlying the responses of T. mairei to nano-pollutants, which has the potential to aid in the breeding of Taxus species with high environmental adaptability

Rapidly developed, optimized, and applied wastewater surveillance system for real-time monitoring of low-incidence, high-impact MPOX outbreak

Recent MPOX viral resurgences have mobilized public health agencies around the world. Recognizing the significant risk of MPOX outbreaks, large-scale human testing, and immunization campaigns have been initiated by local, national, and global public health authorities. Recently, traditional clinical surveillance campaigns for MPOX have been complemented with wastewater surveillance (WWS), building on the effectiveness of existing wastewater programs that were built to monitor SARS-CoV-2 and recently expanded to include influenza and respiratory syncytial virus surveillance in wastewaters. In the present study, we demonstrate and further support the finding that MPOX viral fragments agglomerate in the wastewater solids fraction. Furthermore, this study demonstrates that the current, most commonly used MPOX assays are equally effective at detecting low titers of MPOX viral signal in wastewaters. Finally, MPOX WWS is shown to be more effective at passively tracking outbreaks and/or resurgences of the disease than clinical testing alone in smaller communities with low human clinical case counts of MPOX

Rapidly developed, optimized, and applied wastewater surveillance system for real-time monitoring of low-incidence, high-impact MPOX outbreak

Recent MPOX viral resurgences have mobilized public health agencies around the world. Recognizing the significant risk of MPOX outbreaks, large-scale human testing, and immunization campaigns have been initiated by local, national, and global public health authorities. Recently, traditional clinical surveillance campaigns for MPOX have been complemented with wastewater surveillance (WWS), building on the effectiveness of existing wastewater programs that were built to monitor SARS-CoV-2 and recently expanded to include influenza and respiratory syncytial virus surveillance in wastewaters. In the present study, we demonstrate and further support the finding that MPOX viral fragments agglomerate in the wastewater solids fraction. Furthermore, this study demonstrates that the current, most commonly used MPOX assays are equally effective at detecting low titers of MPOX viral signal in wastewaters. Finally, MPOX WWS is shown to be more effective at passively tracking outbreaks and/or resurgences of the disease than clinical testing alone in smaller communities with low human clinical case counts of MPOX

Multi-dimensional epidemiology and informatics data on COVID-19 wave at the end of zero COVID policy in China

BackgroundChina exited strict Zero-COVID policy with a surge in Omicron variant infections in December 2022. Given China’s pandemic policy and population immunity, employing Baidu Index (BDI) to analyze the evolving disease landscape and estimate the nationwide pneumonia hospitalizations in the post Zero COVID period, validated by hospital data, holds informative potential for future outbreaks.MethodsRetrospective observational analyses were conducted at the conclusion of the Zero-COVID policy, integrating internet search data alongside offline records. Methodologies employed were multidimensional, encompassing lagged Spearman correlation analysis, growth rate assessments, independent sample T-tests, Granger causality examinations, and Bayesian structural time series (BSTS) models for comprehensive data scrutiny.ResultsVarious diseases exhibited a notable upsurge in the BDI after the policy change, consistent with the broader trajectory of the COVID-19 pandemic. Robust connections emerged between COVID-19 and diverse health conditions, predominantly impacting the respiratory, circulatory, ophthalmological, and neurological domains. Notably, 34 diseases displayed a relatively high correlation (r > 0.5) with COVID-19. Among these, 12 exhibited a growth rate exceeding 50% post-policy transition, with myocarditis escalating by 1,708% and pneumonia by 1,332%. In these 34 diseases, causal relationships have been confirmed for 23 of them, while 28 garnered validation from hospital-based evidence. Notably, 19 diseases obtained concurrent validation from both Granger causality and hospital-based data. Finally, the BSTS models approximated approximately 4,332,655 inpatients diagnosed with pneumonia nationwide during the 2 months subsequent to the policy relaxation.ConclusionThis investigation elucidated substantial associations between COVID-19 and respiratory, circulatory, ophthalmological, and neurological disorders. The outcomes from comprehensive multi-dimensional cross-over studies notably augmented the robustness of our comprehension of COVID-19’s disease spectrum, advocating for the prospective utility of internet-derived data. Our research highlights the potential of Internet behavior in predicting pandemic-related syndromes, emphasizing its importance for public health strategies, resource allocation, and preparedness for future outbreaks

Interethnic analyses of blood pressure loci in populations of East Asian and European descent

AbstractBlood pressure (BP) is a major risk factor for cardiovascular disease and more than 200 genetic loci associated with BP are known. Here, we perform a multi-stage genome-wide association study for BP (max N = 289,038) principally in East Asians and meta-analysis in East Asians and Europeans. We report 19 new genetic loci and ancestry-specific BP variants, conforming to a common ancestry-specific variant association model. At 10 unique loci, distinct non-rare ancestry-specific variants colocalize within the same linkage disequilibrium block despite the significantly discordant effects for the proxy shared variants between the ethnic groups. The genome-wide transethnic correlation of causal-variant effect-sizes is 0.898 and 0.851 for systolic and diastolic BP, respectively. Some of the ancestry-specific association signals are also influenced by a selective sweep. Our results provide new evidence for the role of common ancestry-specific variants and natural selection in ethnic differences in complex traits such as BP.AcknowledgementsMarie Loh71,72 (Institute of Health Sciences, University of Oulu, P.O.Box 5000FI-90014 Oulu, Finland and Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK),Niek Verweij73 (Department of Cardiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, Netherlands),Weihua Zhang72,74 (Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK and Ealing Hospital NHS Trust, Middlesex UB1 3HW, UK),Benjamin Lehne72 (Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK),Irene Mateo Leach73 (Department of Cardiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, Netherlands),Alexander Drong75 (Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK),James Abbott76 (Bioinformatics Support Service, Imperial College London, South Kensington, London SW7 2AZ, UK),Sian-Tsung Tan74,77 (Ealing Hospital NHS Trust, Middlesex UB1 3HW, UK and National Heart and Lung Institute, Imperial College London, London W12 0NN, UK),William R. Scott72,77 (Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK and Lung Institute, Imperial College London, London W12 0NN, UK),Gianluca Campanella72 (Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK),Marc Chadeau-Hyam72 (Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK),Uzma Afzal72,74 (Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK and Ealing Hospital NHS Trust, Middlesex UB1 3HW, UK),Tõnu Esko78,79,80,81 (Estonian Genome Center, University of Tartu, Riia 23c, 51010 Tartu, Estonia and Division of Endocrinology, Children’s Hospital Boston, Longwood 300, Boston, MA 02115, USA and Department of Genetics, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA and Program in Medical and Population Genetics, Broad Institute, 7 Cambridge Center, Cambridge, MA 02142, USA),Sarah E. Harris82,83 (Medical Genetics Section, University of Edinburgh Molecular Medicine Centre and MRC Institute of Genetics and Molecular Medicine, Western General Hospital, Crewe Road, Edinburgh EH4 2XU, UK and Centre for Cognitive Aging and Cognitive Epidemiology, University of Edinburgh, Edinburgh EH8 9JZ, UK),Jaana Hartiala84,85 (Department of Preventive Medicine, USC Keck School of Medicine, Los Angeles, CA 90033, USA and Institute for Genetic Medicine, USC Keck School of Medicine, Los Angeles, CA 90033, USA),Marcus E. Kleber86 (Medical Clinic V, Mannheim Medical Faculty, University of Heidelberg, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany),Richa Saxena87 (Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA),Alexandre F.R. Stewart88,89 (University of Ottawa Heart Institute, Cardiovascular Research Methods Centre, Ontario K1Y 4W7, Canada and Ruddy Canadian Cardiovascular Genetics Centre, Ontario K1Y 4W7, Canada),Tarunveer S. Ahluwalia90 (Novo Nordisk Foundation Centre for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, 2100 Copenhagen, Denmark),Imke Aits91 (Institute of Epidemiology and Biobank Popgen, Christian-Albrechts-University of Kiel, 24105 Kiel, Germany),Alexessander Da Silva Couto Alves92 (Department of Epidemiology and Biostatistics, MRC Health Protection Agency (HPE) Centre for Environment and Health, School of Public Health, Imperial College London, London SW7 2AZ, UK),Shikta Das92 (Department of Epidemiology and Biostatistics, MRC Health Protection Agency (HPE) Centre for Environment and Health, School of Public Health, Imperial College London, London SW7 2AZ, UK),Jemma C. Hopewell93 (Clinical Trial Service Unit & Epidemiological Studies Unit, University of Oxford, Richard Doll Building, Old Road Campus, Roosevelt Drive, Oxford OX3 7LF, UK),Robert W. Koivula94 (Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Skåne University Hospital Malmö, SE-205 02 Malmö, Sweden),Leo-Pekka Lyytikäinen95,96 (Department of Clinical Chemistry, Fimlab Laboratories, FI-33520 Tampere, Finland and Department of Clinical Chemistry, University of Tampere School of Medicine, FI-33014 Tampere, Finland),Iris Postmus97,98 (Department of Gerontology and Geriatrics, Leiden University Medical Center, 2300 RC Leiden, Netherlands and Netherlands Consortium for Healthy Ageing, Leiden 2333 ZC, Netherlands),Olli T. Raitakari99,100 (Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, FI-20521 Turku, Finland and Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, FI-20520 Turku, Finland),Robert A. Scott101 (MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge CB2 0QQ, UK),Rossella Sorice102 (Institute of Genetics and Biophysics A. Buzzati-Traverso, CNR, 80131 Naples, Italy),Vinicius Tragante103 (Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, 3508 GA Utrecht, Netherlands),Michela Traglia104,105 (Division of Genetics and Cell Biology, San Raffaele Scientific Institute, 20132 Milano, Italy and Institute for Maternal and Child Health—IRCCS ‘‘Burlo Garofolo’’—Trieste, 34137 Trieste, Italy),Jon White106 (UCL Genetics Institute, Department of Genetics, Environment and Evolution, UCL, London WC1E 6BT, UK),Inês Barroso107,108,109 (Metabolic Disease Group, The Wellcome Trust Sanger Institute, Cambridge CB10 1SA, UK and NIHR Cambridge Biomedical Research Centre, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge CB2 0QQ, UK and University of Cambridge Metabolic Research Laboratories, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge CB2 0QQ, UK),Andrew Bjonnes87 (Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA),Rory Collins103 (Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, 3508 GA Utrecht, Netherlands),Gail Davies110 (Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK),Graciela Delgado86 (Medical Clinic V, Mannheim Medical Faculty, University of Heidelberg, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany),Pieter A. Doevendans103 (Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, 3508 GA Utrecht, Netherlands),Lude Franke111 (Department of Genetics, University Medical Center, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, Netherlands),Ron T. Gansevoort112 (Department of Internal Medicine, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, Netherlands),Tanja B. Grammer86 (Medical Clinic V, Mannheim Medical Faculty, University of Heidelberg, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany),Niels Grarup86 (Medical Clinic V, Mannheim Medical Faculty, University of Heidelberg, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany),Jagvir Grewal72,74 (Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK and Ealing Hospital NHS Trust, Middlesex UB1 3HW, UK),Anna-Liisa Hartikainen113,114 (Department of Obstetrics and Gynecology, University Hospital of Oulu, University of Oulu, Oulu FI-90014, Finland and Department of Clinical Sciences/Obsterics and Gynecology, University of Oulu, Oulu FI-90014, Finland),Stanley L. Hazen115,116 (Center for Cardiovascular Diagnostics and Prevention, Cleveland Clinic, Cleveland, OH 44195, USA and Department of Cellular and Molecular Medicine, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA),Chris Hsu117 (Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA),Lise L.N. Husemoen118 (Research Centre for Prevention and Health, Glostrup University Hospital, 2600 Glostrup, Denmark),Johanne M. Justesen90 (Novo Nordisk Foundation Centre for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, 2100 Copenhagen, Denmark),Meena Kumari119 (Department of Epidemiology and Public Health, UCL, London WC1E 6BT, UK),Wolfgang Lieb91 (Institute of Epidemiology and Biobank Popgen, Christian-Albrechts-University of Kiel, 24105 Kiel, Germany),David C.M. Liewald110 (Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK),Evelin Mihailov78 (Estonian Genome Center, University of Tartu, Riia 23c, 51010 Tartu, Estonia),Lili Milani78 (Estonian Genome Center, University of Tartu, Riia 23c, 51010 Tartu, Estonia),Rebecca Mills74 (Ealing Hospital NHS Trust, Middlesex UB1 3HW, UK),Nina Mononen95,96 (Department of Clinical Chemistry, Fimlab Laboratories, FI-33520 Tampere, Finland and Department of Clinical Chemistry, University of Tampere School of Medicine, FI-33014 Tampere, Finland),Kjell Nikus120 (Heart Centre, Department of Cardiology, Tampere University Hospital, and University of Tampere School of Medicine, FI-33521 Tampere, Finland),Teresa Nutile102 (Institute of Genetics and Biophysics A. Buzzati-Traverso, CNR, 80131 Naples, Italy),Sarah Parish93 (Clinical Trial Service Unit & Epidemiological Studies Unit, University of Oxford, Richard Doll Building, Old Road Campus, Roosevelt Drive, Oxford OX3 7LF, UK),Olov Rolandsson121 (Department of Public Health & Clinical Medicine, Section for Family Medicine, Umeå universitet, SE-901 85 Umeå, Sweden),Daniela Ruggiero102 (Institute of Genetics and Biophysics A. Buzzati-Traverso, CNR, 80131 Naples, Italy),Cinzia F. Sala104 (Division of Genetics and Cell Biology, San Raffaele Scientific Institute, 20132 Milano, Italy),Harold Snieder122 (Department of Epidemiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, Netherlands),Thomas H.W. Spasø90 (Novo Nordisk Foundation Centre for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, 2100 Copenhagen, Denmark),Wilko Spiering123 (Department of Vascular Medicine, University Medical Center Utrecht, 3508 GA Utrecht, Netherlands),John M. Starr83,124 (Centre for Cognitive Aging and Cognitive Epidemiology, University of Edinburgh, Edinburgh EH8 9JZ, UK and Alzheimer Scotland Dementia Research Centre, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK),David J. Stott125 (Academic Section of Geriatric Medicine, Institute of Cardiovascular and Medical Sciences, Faculty of Medicine, University of Glasgow, Glasgow G4 0SF, UK),Daniel O. Stram117 (Keck School of Medicine, University of Southern California, Los Angeles, CA 90089, USA),Silke Szymczak126 (Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel 24105, Germany),W.H.Wilson Tang115,116 (Center for Cardiovascular Diagnostics and Prevention, Cleveland Clinic, Cleveland, OH 44195, USA and Department of Cellular and Molecular Medicine, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA),Stella Trompet127 (Department of Cardiology, Leiden University Medical Center, 2300 RC Leiden, Netherlands),Väinö Turjanmaa128,129 (Department of Clinical Physiology, Tampere University Hospital, FI-33521 Tampere, Finland and Department of Clinical Physiology, University of Tampere School of Medicine, FI-33014 Tampere, Finland),Marja Vaarasmaki130 (Department of Obstetrics and Gynecology, Oulu University Hospital, PO Box 23FI-90029 Oulu, Finland),Wiek H. van Gilst73 (Department of Cardiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, Netherlands),Dirk J. van Veldhuisen73 (Department of Cardiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, Netherlands),Jorma S. Viikari131,132 (Department of Medicine, Turku University Hospital, FI-20521 Turku, Finland and Department of Medicine, University of Turku, FI-20014 Turku, Finland),Folkert W. Asselbergs103,133,134 (Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, 3508 GA Utrecht, Netherlands and Durrer Center for Cardiogenetic Research, ICIN-Netherlands Heart Institute, 3511 GC Utrecht, Netherlands and Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London WC1E 6BT, UK),Marina Ciullo102 (Institute of Genetics and Biophysics A. Buzzati-Traverso, CNR, 80131 Naples, Italy),Andre Franke126 (Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel 24105, Germany),Paul W. Franks94,121,135 (Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Skåne University Hospital Malmö, SE-205 02 Malmö, Sweden and Department of Public Health & Clinical Medicine, Section for Family Medicine, Umeå universitet, SE-901 85 Umeå, Sweden and Department of Nutrition, Harvard School of Public Health, Boston, MA 02115, USA),Steve Franks136 (Institute of Reproductive and Developmental Biology, Imperial College London, Hammersmith Hospital, London W120HS, UK),Myron D. Gross137 (School of Medicine, University of Minnesota, Minneapolis, MN 55455, USA),Torben Hansen90 (Novo Nordisk Foundation Centre for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, 2100 Copenhagen, Denmark),Marjo-Riitta Jarvelin72,92,138,139,140 (Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK and Department of Epidemiology and Biostatistics, MRC Health Protection Agency (HPE) Centre for Environment and Health, School of Public Health, Imperial College London, London SW7 2AZ, UK and Biocenter Oulu, University of Oulu, P.O. Box 5000 Aapistie 5A, FI-90014 Oulu, Finland and Unit of Primary Care, Oulu University Hospital, Kajaanintie 50 P.O.Box 20FI-90220 Oulu, Finland and Department of Children and Young People and Families, National Institute for Health and Welfare, Aapistie 1, Box 310, FI-90101 Oulu, Finland),Torben Jørgensen118 (Research Centre for Prevention and Health, Glostrup University Hospital, 2600 Glostrup, Denmark),Wouter J. Jukema127,133,141 (Department of Cardiology, Leiden University Medical Center, 2300 RC Leiden, Netherlands and Durrer Center for Cardiogenetic Research, ICIN-Netherlands Heart Institute, 3511 GC Utrecht, Netherlands and Interuniversity Cardiology Institute of the Netherlands, Utrecht 3511 EP, Netherlands),Mika Kähönen128,129 (Department of Clinical Physiology, Tampere University Hospital, FI-33521 Tampere, Finland and Department of Clinical Physiology, University of Tampere School of Medicine, FI-33014 Tampere, Finland),Mika Kivimaki119 (Department of Epidemiology and Public Health, UCL, London WC1E 6BT, UK),Terho Lehtimäki95,96 (Department of Clinical Chemistry, Fimlab Laboratories, FI-33520 Tampere, Finland and Department of Clinical Chemistry, University of Tampere School of Medicine, FI-33014 Tampere, Finland),Allan Linneberg118 (Research Centre for Prevention and Health, Glostrup University Hospital, 2600 Glostrup, Denmark),Oluf Pedersen90 (Novo Nordisk Foundation Centre for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, 2100 Copenhagen, Denmark),Nilesh J. Samani142,143 (Department of Cardiovascular Sciences, University of Leicester, Glenfield Hospital, Leicester LE3 9QP, UK and National Institute for Health Research Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Leicester LE3 9QP, UK),Daniela Toniolo104,144 (Division of Genetics and Cell Biology, San Raffaele Scientific Institute, 20132 Milano, Italy and Institute of Molecular GeneticsCNR, 27100 Pavia, Italy),Hooman Allayee84,85 (Department of Preventive Medicine, USC Keck School of Medicine, Los Angeles, CA 90033, USA and Institute for Genetic Medicine, USC Keck School of Medicine, Los Angeles, CA 90033, USA),Ian J. Deary83,110 (Centre for Cognitive Aging and Cognitive Epidemiology, University of Edinburgh, Edinburgh EH8 9JZ, UK and Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK),Winfried März86,145,146 (Medical Clinic V, Mannheim Medical Faculty, University of Heidelberg, Theodor-Kutzer-Ufer 1-3, 68167 Mannheim, Germany and Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Auenbruggerplatz 15, 8036 Graz, Austria and Synlab Academy, Synlab Services GmbH, Gottlieb-Daimler-Straße 25, 68165 Mannheim, Germany),Andres Metspalu78 (Estonian Genome Center, University of Tartu, Riia 23c, 51010 Tartu, Estonia),Cisca Wijmenga111 (Department of Genetics, University Medical Center, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, Netherlands),Bruce H.W. Wolffenbuttel147 (Department of Endocrinology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, Netherlands),Paolo Vineis72 (Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK),Soterios A. KyrtopoulosNational Hellenic Research Foundation, Institute of Biological Research and Biotechnology, Athens 116 35, Greece),Jos C.S. Kleinjans149 (Department of Toxicogenomics, Maastricht University, Universiteitssingel 50, 6229ER Maastricht, Netherlands),Mark I. McCarthy75,150 (Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK and Oxford Centre for Diabetes Endocrinology and Metabolism, University of Oxford, Oxford OX3 7LE, UK),James Scott77 (National Heart and Lung Institute, Imperial College London, London W12 0NN, UK)Abstract Blood pressure (BP) is a major risk factor for cardiovascular disease and more than 200 genetic loci associated with BP are known. Here, we perform a multi-stage genome-wide association study for BP (max N = 289,038) principally in East Asians and meta-analysis in East Asians and Europeans. We report 19 new genetic loci and ancestry-specific BP variants, conforming to a common ancestry-specific variant association model. At 10 unique loci, distinct non-rare ancestry-specific variants colocalize within the same linkage disequilibrium block despite the significantly discordant effects for the proxy shared variants between the ethnic groups. The genome-wide transethnic correlation of causal-variant effect-sizes is 0.898 and 0.851 for systolic and diastolic BP, respectively. Some of the ancestry-specific association signals are also influenced by a selective sweep. Our results provide new evidence for the role of common ancestry-specific variants and natural selection in ethnic differences in complex traits such as BP.Acknowledgements Marie Loh71,72 (Institute of Health Sciences, University of Oulu, P.O.Box 5000FI-90014 Oulu, Finland and Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK),Niek Verweij73 (Department of Cardiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, Netherlands),Weihua Zhang72,74 (Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK and Ealing Hospital NHS Trust, Middlesex UB1 3HW, UK),Benjamin Lehne72 (Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK),Irene Mateo Leach73 (Department of Cardiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groning

Wastewater to clinical case (WC) ratio of COVID-19 identifies insufficient clinical testing, onset of new variants of concern and population immunity in urban communities

Clinical testing has been the cornerstone of public health monitoring and infection control efforts in communities throughout the COVID-19 pandemic. With the extant and anticipated reduction of clinical testing as the disease moves into an endemic state, SARS-CoV-2 wastewater surveillance (WWS) is likely to have greater value as an important diagnostic tool to inform public health. As the widespread adoption of WWS is relatively new at the scale employed for COVID-19, interpretation of data, including the relationship to clinical cases, has yet to be standardized. An in-depth analysis of the metrics derived from WWS is required for public health units/agencies to interpret and utilize WWS-acquired data effectively and efficiently. In this study, the SARS-CoV-2 wastewater signal to clinical cases (WC) ratio was investigated across seven different cities in Canada over periods ranging from 8 to 21 months. Significant increases in the WC ratio occurred when clinical testing eligibility was modified to appointment-only testing, identifying a period of insufficient clinical testing in these communities. The WC ratio decreased significantly during the emergence of the Alpha variant of concern (VOC) in a relatively non-immunized community’s wastewater (40-60% allelic proportion), while a more muted decrease in the WC ratio signaled the emergence of the Delta VOC in a relatively well-immunized community’s wastewater (40-60% allelic proportion). Finally, a rapid and significant decrease in the WC ratio signaled the emergence of the Omicron VOC, likely because of the variant’s greater effectiveness at evading immunity, leading to a significant number of new reported clinical cases, even when vaccine-induced community immunity was high. The WC ratio, used as an additional monitoring metric, complements clinical case counts and wastewater signals as individual metrics in its ability to identify important epidemiological occurrences, adding value to WWS as a diagnostic technology during the COVID-19 pandemic and likely for future pandemics.Ontario's Ministry of Environment, Conservation and Parks||Alberta Healt

Evaluation of Coastal Ecological Security Barrier Functions Based on Ecosystem Services: A Case Study of Fujian Province, China

Constructing coastal ecological security barriers is beneficial for preventing environmental degradation and enhancing resilience to natural disasters. This study examines the functionality of these barriers from an ecosystem service perspective, developing an Ecosystem Security Barrier Function (ESBF) index to analyze its spatiotemporal variations. From 2000 to 2020, habitat quality in the study area experienced a slight decline, while water supply capacity initially increased and then decreased. Water purification capacity hit its lowest point in 2015 before improving. The ESBF generally ranged from moderate to high levels, with higher values in the northwest and lower values in the southeast, showing strong spatial autocorrelations. Despite mild degradation in some areas, overall stability was maintained with frequent transitions between ESBF levels. Utilizing the Multiscale Geographically Weighted Regression (MGWR) model, we conducted a grid-scale analysis of the driving mechanisms behind ESBF. We found that precipitation, elevation, and the Normalized Difference Vegetation Index (NDVI) positively correlated with ESBF, whereas population density, land use, and nighttime lights negatively correlated. The relationship between temperature and ESBF showed a “north-positive, south-negative” pattern. The study recommends enhancing coastal wetland restoration, strengthening protective forest construction, and effectively controlling pollutant sources entering the sea to safeguard and improve the ecological security barrier function