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Kersalé M, Meinen CS, Perez RC, Le Hénaff M, Valla D, Lamont T, Sato OT, Dong S, Terre T, van Caspel M, Chidichimo MP, van den Berg M, Speich S, Piola AR, Campos EJD, Ansorge I, Volkov DL, Lumpkin R, Garzoli SL. Highly variable upper and abyssal overturning cells in the South Atlantic. Sci Adv 2020; 6:eaba7573. [PMID: 32821826 PMCID: PMC7406378 DOI: 10.1126/sciadv.aba7573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/02/2020] [Accepted: 06/25/2020] [Indexed: 06/11/2023]
Abstract
The Meridional Overturning Circulation (MOC) is a primary mechanism driving oceanic heat redistribution on Earth, thereby affecting Earth's climate and weather. However, the full-depth structure and variability of the MOC are still poorly understood, particularly in the South Atlantic. This study presents unique multiyear records of the oceanic volume transport of both the upper (<~3100 meters) and abyssal (>~3100 meters) overturning cells based on daily moored measurements in the South Atlantic at 34.5°S. The vertical structure of the time-mean flows is consistent with the limited historical observations. Both the upper and abyssal cells exhibit a high degree of variability relative to the temporal means at time scales, ranging from a few days to a few weeks. Observed variations in the abyssal flow appear to be largely independent of the flow in the overlying upper cell. No meaningful trends are detected in either cell.
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Affiliation(s)
- M. Kersalé
- Cooperative Institute for Marine and Atmospheric Studies, University of Miami, Miami, FL, USA
- NOAA Atlantic Oceanographic and Meteorological Laboratory, Miami, FL, USA
| | - C. S. Meinen
- NOAA Atlantic Oceanographic and Meteorological Laboratory, Miami, FL, USA
| | - R. C. Perez
- NOAA Atlantic Oceanographic and Meteorological Laboratory, Miami, FL, USA
| | - M. Le Hénaff
- Cooperative Institute for Marine and Atmospheric Studies, University of Miami, Miami, FL, USA
- NOAA Atlantic Oceanographic and Meteorological Laboratory, Miami, FL, USA
| | - D. Valla
- Servicio de Hidrografía Naval, Buenos Aires, Argentina
| | - T. Lamont
- Oceans and Coasts Research Branch, Department of Environmental Affairs, Cape Town, South Africa
- Department of Oceanography, University of Cape Town, Rondebosch 7701, South Africa
| | - O. T. Sato
- Oceanographic Institute, University of São Paulo, São Paulo, Brazil
| | - S. Dong
- NOAA Atlantic Oceanographic and Meteorological Laboratory, Miami, FL, USA
| | - T. Terre
- IFREMER, University of Brest, CNRS, IRD, Laboratoire d'Océanographie Physique et Spatiale (LOPS), IUEM, Plouzané, France
| | - M. van Caspel
- Oceanographic Institute, University of São Paulo, São Paulo, Brazil
| | - M. P. Chidichimo
- Servicio de Hidrografía Naval, Buenos Aires, Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina
- Instituto Franco-Argentino sobre Estudio del Clima y sus Impactos (UMI-IFAECI/CNRS-CONICET-UBA), Buenos Aires, Argentina
| | - M. van den Berg
- Oceans and Coasts Research Branch, Department of Environmental Affairs, Cape Town, South Africa
| | - S. Speich
- Laboratoire de Météorologie Dynamique–IPSL, Ecole Normale Supérieure, Paris, France
| | - A. R. Piola
- Servicio de Hidrografía Naval, Buenos Aires, Argentina
- Instituto Franco-Argentino sobre Estudio del Clima y sus Impactos (UMI-IFAECI/CNRS-CONICET-UBA), Buenos Aires, Argentina
- Universidad de Buenos Aires, Buenos Aires, Argentina
| | - E. J. D. Campos
- Oceanographic Institute, University of São Paulo, São Paulo, Brazil
- Department of Biology, Chemistry and Environmental Sciences, School of Arts and Sciences, American University of Sharjah, Sharjah, United Arab Emirates
| | - I. Ansorge
- Department of Oceanography, University of Cape Town, Rondebosch 7701, South Africa
| | - D. L. Volkov
- Cooperative Institute for Marine and Atmospheric Studies, University of Miami, Miami, FL, USA
- NOAA Atlantic Oceanographic and Meteorological Laboratory, Miami, FL, USA
| | - R. Lumpkin
- NOAA Atlantic Oceanographic and Meteorological Laboratory, Miami, FL, USA
| | - S. L. Garzoli
- Cooperative Institute for Marine and Atmospheric Studies, University of Miami, Miami, FL, USA
- NOAA Atlantic Oceanographic and Meteorological Laboratory, Miami, FL, USA
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Choi B, Busch S, Kazadi D, Ilunga B, Okitolonda E, Dai Y, Lumpkin R, Saucedo O, KhudaBukhsh WR, Tien J, Yotebieng M, Kenah E, Rempala GA. Modeling outbreak data: Analysis of a 2012 Ebola virus disease epidemic in DRC. Biomath (Sofia) 2019; 8:1910037. [PMID: 33192155 PMCID: PMC7665115 DOI: 10.11145/j.biomath.2019.10.037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
We describe two approaches to modeling data from a small to moderate-sized epidemic outbreak. The first approach is based on a branching process approximation and direct analysis of the transmission network, whereas the second one is based on a survival model derived from the classical SIR equations with no explicit transmission information. We compare these approaches using data from a 2012 outbreak of Ebola virus disease caused by Bundibugyo ebolavirus in city of Isiro, Democratic Republic of the Congo. The branching process model allows for a direct comparison of disease transmission across different environments, such as the general community or the Ebola treatment unit. However, the survival model appears to yield parameter estimates with more accuracy and better precision in some circumstances.
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Affiliation(s)
- Boseung Choi
- Department of National Statistics, Korea University Sejoung Campus Sejoung, Republic of Korea
| | - Sydney Busch
- Department of Mathematics, Augsburg College Minneapolis, MN, USA
| | - Dieudonné Kazadi
- Ministry of Health, Democratic Republic of the Congo
- School of Public Health, University of Kinshasa Kinshasa, Democratic Republic of the Congo
| | - Benoit Ilunga
- School of Public Health, University of Kinshasa Kinshasa, Democratic Republic of the Congo
| | | | - Yi Dai
- Division of Biostatistics, College of Public Health, The Ohio State University, Columbus, OH, USA
| | - Robert Lumpkin
- Department of Mathematics, The Ohio State University, Columbus, OH, USA
| | - Omar Saucedo
- Mathematical Biosciences Institute, The Ohio State University, Columbus, OH, USA
| | - Wasiur R. KhudaBukhsh
- Division of Biostatistics, College of Public Health, The Ohio State University, Columbus, OH, USA
- Mathematical Biosciences Institute, The Ohio State University, Columbus, OH, USA
| | - Joseph Tien
- Department of Mathematics, The Ohio State University, Columbus, OH, USA
| | - Marcel Yotebieng
- Division of Epidemiology, College of Public Health, The Ohio State University, Columbus, OH, USA
| | - Eben Kenah
- Division of Biostatistics, College of Public Health, The Ohio State University, Columbus, OH, USA
| | - Grzegorz A. Rempala
- Division of Biostatistics, College of Public Health, The Ohio State University, Columbus, OH, USA
- Department of Mathematics, The Ohio State University, Columbus, OH, USA
- Mathematical Biosciences Institute, The Ohio State University, Columbus, OH, USA
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Abstract
Amylin is a 37 amino acid hormone, co-secreted with insulin from the pancreatic beta-cell in response to nutrient stimuli. Because the human amylin analog, pramlintide, is being tested in patients with diabetes mellitus, a known risk factor for nephropathy, we examined the role of the kidney on amylin and pramlintide metabolism and action in functionally nephrectomized rats. Nephrectomy markedly altered amylin metabolism: it increased incremental area under the plasma amylin concentration curve 3.6-fold (P<0.001) and increased the elimination half-life from 17+/-1 to 26+/-2 minutes (P < 0.01) after subcutaneous injection of 100 microg amylin. Nephrectomy decreased plasma amylin clearance from 20.3+/-1.1 to 7.9+/-0.4 mL/min (P < 0.0001). Thus, at these doses in the rat, the kidney is important for metabolizing amylin and pramlintide.
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Affiliation(s)
- W Vine
- Amylin Pharmaceuticals Inc., San Diego, CA 92121, USA
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