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The Case for Visual Analytics of Arsenic Concentrations in Foods

Arsenic is a naturally occurring toxic metal and its presence in food could be a potential risk to the health of both humans and animals. Prolonged ingestion of arsenic contaminated water may result in manifestations of toxicity in all systems of the body. Visual Analytics is a multidisciplinary fie...

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Autores principales: Johnson, Matilda O., Cohly, Hari H.P., Isokpehi, Raphael D., Awofolu, Omotayo R.
Formato: Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2898029/
https://www.ncbi.nlm.nih.gov/pubmed/20623005
http://dx.doi.org/10.3390/ijerph7051970
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author Johnson, Matilda O.
Cohly, Hari H.P.
Isokpehi, Raphael D.
Awofolu, Omotayo R.
author_facet Johnson, Matilda O.
Cohly, Hari H.P.
Isokpehi, Raphael D.
Awofolu, Omotayo R.
author_sort Johnson, Matilda O.
collection PubMed
description Arsenic is a naturally occurring toxic metal and its presence in food could be a potential risk to the health of both humans and animals. Prolonged ingestion of arsenic contaminated water may result in manifestations of toxicity in all systems of the body. Visual Analytics is a multidisciplinary field that is defined as the science of analytical reasoning facilitated by interactive visual interfaces. The concentrations of arsenic vary in foods making it impractical and impossible to provide regulatory limit for each food. This review article presents a case for the use of visual analytics approaches to provide comparative assessment of arsenic in various foods. The topics covered include (i) metabolism of arsenic in the human body; (ii) arsenic concentrations in various foods; (ii) factors affecting arsenic uptake in plants; (ii) introduction to visual analytics; and (iv) benefits of visual analytics for comparative assessment of arsenic concentration in foods. Visual analytics can provide an information superstructure of arsenic in various foods to permit insightful comparative risk assessment of the diverse and continually expanding data on arsenic in food groups in the context of country of study or origin, year of study, method of analysis and arsenic species.
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spelling pubmed-28980292010-07-09 The Case for Visual Analytics of Arsenic Concentrations in Foods Johnson, Matilda O. Cohly, Hari H.P. Isokpehi, Raphael D. Awofolu, Omotayo R. Int J Environ Res Public Health Review Arsenic is a naturally occurring toxic metal and its presence in food could be a potential risk to the health of both humans and animals. Prolonged ingestion of arsenic contaminated water may result in manifestations of toxicity in all systems of the body. Visual Analytics is a multidisciplinary field that is defined as the science of analytical reasoning facilitated by interactive visual interfaces. The concentrations of arsenic vary in foods making it impractical and impossible to provide regulatory limit for each food. This review article presents a case for the use of visual analytics approaches to provide comparative assessment of arsenic in various foods. The topics covered include (i) metabolism of arsenic in the human body; (ii) arsenic concentrations in various foods; (ii) factors affecting arsenic uptake in plants; (ii) introduction to visual analytics; and (iv) benefits of visual analytics for comparative assessment of arsenic concentration in foods. Visual analytics can provide an information superstructure of arsenic in various foods to permit insightful comparative risk assessment of the diverse and continually expanding data on arsenic in food groups in the context of country of study or origin, year of study, method of analysis and arsenic species. Molecular Diversity Preservation International (MDPI) 2010-04-28 2010-05 /pmc/articles/PMC2898029/ /pubmed/20623005 http://dx.doi.org/10.3390/ijerph7051970 Text en © 2010 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland. http://creativecommons.org/licenses/by/3.0 This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Review
Johnson, Matilda O.
Cohly, Hari H.P.
Isokpehi, Raphael D.
Awofolu, Omotayo R.
The Case for Visual Analytics of Arsenic Concentrations in Foods
title The Case for Visual Analytics of Arsenic Concentrations in Foods
title_full The Case for Visual Analytics of Arsenic Concentrations in Foods
title_fullStr The Case for Visual Analytics of Arsenic Concentrations in Foods
title_full_unstemmed The Case for Visual Analytics of Arsenic Concentrations in Foods
title_short The Case for Visual Analytics of Arsenic Concentrations in Foods
title_sort case for visual analytics of arsenic concentrations in foods
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2898029/
https://www.ncbi.nlm.nih.gov/pubmed/20623005
http://dx.doi.org/10.3390/ijerph7051970
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