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Razlivanov I, Liew T, Moore EW, Al-Kathiri A, Bartram T, Kuvshinov D, Nikolaev A. Long-term imaging of calcium dynamics using genetically encoded calcium indicators and automatic tracking of cultured cells. Biotechniques 2018; 65:37-39. [PMID: 30014737 DOI: 10.2144/btn-2018-0024] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Calcium dynamics is crucial for many signaling pathways and cell functions. Understanding how calcium regulates cell function often requires long-term imaging of calcium dynamics. Here we report a methodological approach of long-term (5-10 h) imaging of calcium dynamics in cultured cells. The approach links calcium imaging using genetically encoded calcium indicators and semi-automatic tracking of individual cells. It can be used in a large variety of situations, ranging from the role of calcium in biological processes to cell heterogeneity and screening of drugs modifying signaling pathways.
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Affiliation(s)
- Igor Razlivanov
- Department of Biomedical Sciences, The University of Sheffield, Western Bank, Sheffield, S10 2TN, UK
| | - Teresa Liew
- Department of Biomedical Sciences, The University of Sheffield, Western Bank, Sheffield, S10 2TN, UK
| | - Eira Watts Moore
- Department of Biomedical Sciences, The University of Sheffield, Western Bank, Sheffield, S10 2TN, UK
| | - Alaa Al-Kathiri
- Department of Biomedical Sciences, The University of Sheffield, Western Bank, Sheffield, S10 2TN, UK
| | - Tayma Bartram
- Department of Biomedical Sciences, The University of Sheffield, Western Bank, Sheffield, S10 2TN, UK.,Department of Oncology and Metabolism, The University of Sheffield, Medical School, Beech Hill Road, Sheffield, S10 2RX, UK
| | - Dmitriy Kuvshinov
- Department of Chemical Engineering, University of Hull, Cottingham Road, Hull, HU6 7RX, UK
| | - Anton Nikolaev
- Department of Biomedical Sciences, The University of Sheffield, Western Bank, Sheffield, S10 2TN, UK
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Lauvaux T, Miles NL, Deng A, Richardson SJ, Cambaliza MO, Davis KJ, Gaudet B, Gurney KR, Huang J, O'Keefe D, Song Y, Karion A, Oda T, Patarasuk R, Razlivanov I, Sarmiento D, Shepson P, Sweeney C, Turnbull J, Wu K. High-resolution atmospheric inversion of urban CO 2 emissions during the dormant season of the Indianapolis Flux Experiment (INFLUX). J Geophys Res Atmos 2016; 121:5213-5236. [PMID: 32818124 PMCID: PMC7430513 DOI: 10.1002/2015jd024473] [Citation(s) in RCA: 60] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Based on a uniquely dense network of surface towers measuring continuously the atmospheric concentrations of greenhouse gases (GHGs), we developed the first comprehensive monitoring systems of CO2 emissions at high resolution over the city of Indianapolis. The urban inversion evaluated over the 2012-2013 dormant season showed a statistically significant increase of about 20% (from 4.5 to 5.7 MtC ± 0.23 MtC) compared to the Hestia CO2 emission estimate, a state-of-the-art building-level emission product. Spatial structures in prior emission errors, mostly undetermined, appeared to affect the spatial pattern in the inverse solution and the total carbon budget over the entire area by up to 15%, while the inverse solution remains fairly insensitive to the CO2 boundary inflow and to the different prior emissions (i.e., ODIAC). Preceding the surface emission optimization, we improved the atmospheric simulations using a meteorological data assimilation system also informing our Bayesian inversion system through updated observations error variances. Finally, we estimated the uncertainties associated with undetermined parameters using an ensemble of inversions. The total CO2 emissions based on the ensemble mean and quartiles (5.26-5.91 MtC) were statistically different compared to the prior total emissions (4.1 to 4.5 MtC). Considering the relatively small sensitivity to the different parameters, we conclude that atmospheric inversions are potentially able to constrain the carbon budget of the city, assuming sufficient data to measure the inflow of GHG over the city, but additional information on prior emission error structures are required to determine the spatial structures of urban emissions at high resolution.
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Affiliation(s)
- Thomas Lauvaux
- Department of Meteorology, Pennsylvania State University, University Park, Pennsylvania, USA
- NASA Jet Propulsion Laboratory, Pasadena, California, USA
| | - Natasha L Miles
- Department of Meteorology, Pennsylvania State University, University Park, Pennsylvania, USA
| | - Aijun Deng
- Department of Meteorology, Pennsylvania State University, University Park, Pennsylvania, USA
| | - Scott J Richardson
- Department of Meteorology, Pennsylvania State University, University Park, Pennsylvania, USA
| | - Maria O Cambaliza
- Department of Physics, Ateneo de Manila University, Quezon City, Philippines
- Manila Observatory, Ateneo de Manila Campus, Quezon City, Philippines
| | - Kenneth J Davis
- Department of Meteorology, Pennsylvania State University, University Park, Pennsylvania, USA
| | - Brian Gaudet
- Department of Meteorology, Pennsylvania State University, University Park, Pennsylvania, USA
| | - Kevin R Gurney
- School of Life Sciences, Arizona State University, Tempe, Arizona, USA
| | - Jianhua Huang
- School of Life Sciences, Arizona State University, Tempe, Arizona, USA
| | - Darragh O'Keefe
- School of Life Sciences, Arizona State University, Tempe, Arizona, USA
| | - Yang Song
- School of Life Sciences, Arizona State University, Tempe, Arizona, USA
| | - Anna Karion
- CIRES, University of Colorado Boulder, Boulder, Colorado, USA
| | - Tomohiro Oda
- Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
- Goddard Earth Sciences Technologies and Research, Universities Space Research Association, Columbia, Maryland, USA
| | - Risa Patarasuk
- School of Life Sciences, Arizona State University, Tempe, Arizona, USA
| | - Igor Razlivanov
- School of Life Sciences, Arizona State University, Tempe, Arizona, USA
| | - Daniel Sarmiento
- Department of Meteorology, Pennsylvania State University, University Park, Pennsylvania, USA
| | - Paul Shepson
- Department of Chemistry, Purdue University, West Lafayette, Indiana, USA
| | - Colm Sweeney
- CIRES, University of Colorado Boulder, Boulder, Colorado, USA
| | - Jocelyn Turnbull
- Department of Chemistry, Purdue University, West Lafayette, Indiana, USA
- NOAA Earth System Research Laboratory, Boulder, Colorado, USA
- National Isotope Centre, GNS Science, Lower Hutt, New Zealand
| | - Kai Wu
- Department of Meteorology, Pennsylvania State University, University Park, Pennsylvania, USA
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Gurney KR, Razlivanov I, Song Y, Zhou Y, Benes B, Abdul-Massih M. Quantification of fossil fuel CO2 emissions on the building/street scale for a large U.S. city. Environ Sci Technol 2012; 46:12194-202. [PMID: 22891924 DOI: 10.1021/es3011282] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
In order to advance the scientific understanding of carbon exchange with the land surface, build an effective carbon monitoring system, and contribute to quantitatively based U.S. climate change policy interests, fine spatial and temporal quantification of fossil fuel CO(2) emissions, the primary greenhouse gas, is essential. Called the "Hestia Project", this research effort is the first to use bottom-up methods to quantify all fossil fuel CO(2) emissions down to the scale of individual buildings, road segments, and industrial/electricity production facilities on an hourly basis for an entire urban landscape. Here, we describe the methods used to quantify the on-site fossil fuel CO(2) emissions across the city of Indianapolis, IN. This effort combines a series of data sets and simulation tools such as a building energy simulation model, traffic data, power production reporting, and local air pollution reporting. The system is general enough to be applied to any large U.S. city and holds tremendous potential as a key component of a carbon-monitoring system in addition to enabling efficient greenhouse gas mitigation and planning. We compare the natural gas component of our fossil fuel CO(2) emissions estimate to consumption data provided by the local gas utility. At the zip code level, we achieve a bias-adjusted Pearson r correlation value of 0.92 (p < 0.001).
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Affiliation(s)
- Kevin R Gurney
- School of Life Sciences, Arizona State University, Tempe, Arizona 85287, USA.
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