Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 2 de 2
Filter
Add filters

Language
Document Type
Year range
1.
J AOAC Int ; 104(4): 889-913, 2021 Aug 20.
Article in English | MEDLINE | ID: covidwho-1174914

ABSTRACT

BACKGROUND: The PathogenDx EnviroX-Rv uses endpoint PCR + DNA microarray technology to detect SARS-CoV-2, the causative agent of COVID-19, from stainless-steel environmental sample swabs. OBJECTIVE: To validate the PathogenDx EnviroX-Rv assay as part of the Emergency Response Validation (ERV) Performance Tested Method(s)SM (PTM) program. METHOD: The PathogenDx EnviroX-Rv assay was evaluated for specificity using in silico analysis of ≥41 000 SARS-CoV-2 sequences and over 50 exclusivity organisms (both near neighbors and background organisms). The candidate method was evaluated in an unpaired study design for one environmental surface (stainless steel) and compared to the US Centers for Disease Control and Prevention (CDC) 2019-Novel Coronavirus (2019-nCoV) Real-Time-Polymerase Chain Reaction (RT-PCR) Diagnostic Panel, Instructions for Use (Revision 4, Effective 6/12/2020). RESULTS: Results of the in silico analysis demonstrated the high specificity of the method in being able to detect target SARS-CoV-2 sequences and discriminate them from near neighbors and environmental background organisms. In the matrix study, the candidate method demonstrated a statistically significant difference when compared to the results of the CDC method utilized in this study, with the candidate method resulting in more positive replicates as it only requires one target to be present for a positive sample. CONCLUSIONS: The EnviroX-Rv assay rapidly and accurately detected SARS-CoV-2 RNA on environmental swabs from stainless-steel surfaces at a concentration of 2000 genomic copies per 2 × 2" test area. HIGHLIGHTS: The EnviroX-Rv assay employs dual PCR and hybridization techniques to provide highly accurate results when detecting SARS-CoV-2 from surfaces.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , RNA, Viral , Real-Time Polymerase Chain Reaction , Sensitivity and Specificity , Stainless Steel
2.
Friedlingstein, Pierre, O'Sullivan, Michael, Jones, Matthew W.; Andrew, Robbie M.; Hauck, Judith, Olsen, Are, Peters, Glen P.; Peters, Wouter, Pongratz, Julia, Sitch, Stephen, Corinne, Le Quéré, Canadell, Josep G.; Ciais, Philippe, Jackson, Robert B.; Alin, Simone, Luiz E O , C. Aragão, Arneth, Almut, Arora, Vivek, Bates, Nicholas R.; Becker, Meike, Benoit-Cattin, Alice, Bittig, Henry C.; Bopp, Laurent, Bultan, Selma, Chandra, Naveen, Chevallier, Frédéric, Chini, Louise P.; Evans, Wiley, Florentie, Liesbeth, Forster, Piers M.; Gasser, Thomas, Gehlen, Marion, Gilfillan, Dennis, Gkritzalis, Thanos, Luke, Gregor, Gruber, Nicolas, Harris, Ian, Hartung, Kerstin, Haverd, Vanessa, Houghton, Richard A.; Ilyina, Tatiana, Jain, Atul K.; Joetzjer, Emilie, Kadono, Koji, Kato, Etsushi, Kitidis, Vassilis, Korsbakken, Jan Ivar, Landschützer, Peter, Lefèvre, Nathalie, Lenton, Andrew, Lienert, Sebastian, Liu, Zhu, Lombardozzi, Danica, Marland, Gregg, Metzl, Nicolas, Munro, David R.; Julia E M , S. Nabel, Shin-Ichiro, Nakaoka, Niwa, Yosuke, O'Brien, Kevin, Ono, Tsuneo, Palmer, Paul I.; Pierrot, Denis, Poulter, Benjamin, Resplandy, Laure, Robertson, Eddy, Rödenbeck, Christian, Schwinger, Jörg, Séférian, Roland, Skjelvan, Ingunn, Smith, Adam J. P.; Sutton, Adrienne J.; Toste, Tanhua, Tans, Pieter P.; Tian, Hanqin, Tilbrook, Bronte, van der Werf, Guido, Vuichard, Nicolas, Walker, Anthony P.; Wanninkhof, Rik, Watson, Andrew J.; Willis, David, Wiltshire, Andrew J.; Yuan, Wenping, Xu, Yue, Zaehle, Sönke.
Earth System Science Data ; 12(4):3269-3340, 2020.
Article in English | ProQuest Central | ID: covidwho-971932

ABSTRACT

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2010–2019), EFOS was 9.6 ± 0.5 GtC yr-1 excluding the cement carbonation sink (9.4 ± 0.5 GtC yr-1 when the cement carbonation sink is included), andELUC was 1.6 ± 0.7 GtC yr-1. For the same decade, GATM was 5.1 ± 0.02 GtC yr-1 (2.4 ± 0.01 ppm yr-1), SOCEAN 2.5 ± 0.6 GtC yr-1, and SLAND 3.4 ± 0.9 GtC yr-1, with a budget imbalance BIM of -0.1 GtC yr-1 indicating a near balance between estimated sources and sinks over the last decade. For the year 2019 alone, the growth in EFOS was only about 0.1 % with fossil emissions increasing to 9.9 ± 0.5 GtC yr-1 excluding the cement carbonation sink (9.7 ± 0.5 GtC yr-1 when cement carbonation sink is included), and ELUC was 1.8 ± 0.7 GtC yr-1, for total anthropogenic CO2 emissions of 11.5 ± 0.9 GtC yr-1 (42.2 ± 3.3 GtCO2). Also for 2019, GATM was 5.4 ± 0.2 GtC yr-1 (2.5 ± 0.1 ppm yr-1), SOCEAN was 2.6 ± 0.6 GtC yr-1, and SLAND was 3.1 ± 1.2 GtC yr-1, with a BIM of 0.3 GtC. The global atmospheric CO2 concentration reached 409.85 ± 0.1 ppm averaged over 2019. Preliminary data for 2020, accounting for the COVID-19-induced changes in emissions, suggest a decrease in EFOS relative to 2019 of about -7 % (median estimate) based on individual estimates from four studies of -6 %, -7 %,-7 % (-3 % to -11 %), and -13 %. Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2019, but discrepancies of up to 1 GtC yr-1 persist for the representation of semi-decadal variability in CO2 fluxes. Comparison of estimates from diverse approaches and observations shows (1) no consensus in the mean and trend in land-use change emissions over the last decade, (2) a persistent low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent discrepancy between the different methods for the ocean sink outside the tropics, particularly in the Southern Ocean. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set (Friedlingstein et al., 2019;Le Quéré et al., 2018b, a, 2016, 2015b, a, 2014, 2013). The data presented in this work are available at 10.18160/gcp-2020 (Friedlingstein et al., 2020).

SELECTION OF CITATIONS
SEARCH DETAIL