Literature DB >> 17454552

Copper and human health: biochemistry, genetics, and strategies for modeling dose-response relationships.

Bonnie Ransom Stern1, Marc Solioz, Daniel Krewski, Peter Aggett, Tar-Ching Aw, Scott Baker, Kenny Crump, Michael Dourson, Lynne Haber, Rick Hertzberg, Carl Keen, Bette Meek, Larisa Rudenko, Rita Schoeny, Wout Slob, Tom Starr.   

Abstract

Copper (Cu) and its alloys are used extensively in domestic and industrial applications. Cu is also an essential element in mammalian nutrition. Since both copper deficiency and copper excess produce adverse health effects, the dose-response curve is U-shaped, although the precise form has not yet been well characterized. Many animal and human studies were conducted on copper to provide a rich database from which data suitable for modeling the dose-response relationship for copper may be extracted. Possible dose-response modeling strategies are considered in this review, including those based on the benchmark dose and categorical regression. The usefulness of biologically based dose-response modeling techniques in understanding copper toxicity was difficult to assess at this time since the mechanisms underlying copper-induced toxicity have yet to be fully elucidated. A dose-response modeling strategy for copper toxicity was proposed associated with both deficiency and excess. This modeling strategy was applied to multiple studies of copper-induced toxicity, standardized with respect to severity of adverse health outcomes and selected on the basis of criteria reflecting the quality and relevance of individual studies. The use of a comprehensive database on copper-induced toxicity is essential for dose-response modeling since there is insufficient information in any single study to adequately characterize copper dose-response relationships. The dose-response modeling strategy envisioned here is designed to determine whether the existing toxicity data for copper excess or deficiency may be effectively utilized in defining the limits of the homeostatic range in humans and other species. By considering alternative techniques for determining a point of departure and low-dose extrapolation (including categorical regression, the benchmark dose, and identification of observed no-effect levels) this strategy will identify which techniques are most suitable for this purpose. This analysis also serves to identify areas in which additional data are needed to better define the characteristics of dose-response relationships for copper-induced toxicity in relation to excess or deficiency.

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Year:  2007        PMID: 17454552     DOI: 10.1080/10937400600755911

Source DB:  PubMed          Journal:  J Toxicol Environ Health B Crit Rev        ISSN: 1093-7404            Impact factor:   6.393


  26 in total

1.  Body burdens of mercury, lead, selenium and copper among Baltimore newborns.

Authors:  Ellen M Wells; Jeffery M Jarrett; Yu Hong Lin; Kathleen L Caldwell; Joseph R Hibbeln; Benjamin J Apelberg; Julie Herbstman; Rolf U Halden; Frank R Witter; Lynn R Goldman
Journal:  Environ Res       Date:  2011-01-31       Impact factor: 6.498

Review 2.  IAPs: what's in a name?

Authors:  Srinivasa M Srinivasula; Jonathan D Ashwell
Journal:  Mol Cell       Date:  2008-04-25       Impact factor: 17.970

3.  Heavy metals in fish from the Red Sea, Arabian Sea, and Indian Ocean: effect of origin, fish species and size and correlation among the metals.

Authors:  Mohammad M Obaidat; Adnan M Massadeh; Ahmad M Al-Athamneh; Qasem M Jaradat
Journal:  Environ Monit Assess       Date:  2015-03-31       Impact factor: 2.513

4.  The trace element content of top-soil and wild edible mushroom samples collected in Tuscany, Italy.

Authors:  Gino Giannaccini; Laura Betti; Lionella Palego; Giovanni Mascia; Lara Schmid; Mario Lanza; Antonio Mela; Laura Fabbrini; Luciano Biondi; Antonio Lucacchini
Journal:  Environ Monit Assess       Date:  2012-02-29       Impact factor: 2.513

5.  Residents health risk of Pb, Cd and Cu exposure to street dust based on different particle sizes around zinc smelting plant, Northeast of China.

Authors:  Qiuhong Zhou; Na Zheng; Jingshuang Liu; Yang Wang; Chongyu Sun; Qiang Liu; Heng Wang; Jingjing Zhang
Journal:  Environ Geochem Health       Date:  2014-08-13       Impact factor: 4.609

6.  A Colorimetric and Fluorescent Probe Based on Rhodamine B for Detection of Fe3+ and Cu2+ Ions.

Authors:  Liqiang Yan; Ya Xie; Jianping Li
Journal:  J Fluoresc       Date:  2019-10-10       Impact factor: 2.217

7.  Does dietary copper supplementation enhance or diminish PCB126 toxicity in the rodent liver?

Authors:  Ian K Lai; William D Klaren; Miao Li; Brian Wels; Donald L Simmons; Alicia K Olivier; Wanda M Haschek; Kai Wang; Gabriele Ludewig; Larry W Robertson
Journal:  Chem Res Toxicol       Date:  2013-04-15       Impact factor: 3.739

8.  Association of selenium and copper with lipids in umbilical cord blood.

Authors:  E M Wells; A Navas-Acien; B J Apelberg; J B Herbstman; J M Jarrett; Y H Lin; C P Verdon; C Ward; K L Caldwell; J R Hibbeln; R U Halden; F R Witter; L R Goldman
Journal:  J Dev Orig Health Dis       Date:  2014-08       Impact factor: 2.401

9.  Identifying natural and anthropogenic sources of metals in urban and rural soils using GIS-based data, PCA, and spatial interpolation.

Authors:  Harley T Davis; C Marjorie Aelion; Suzanne McDermott; Andrew B Lawson
Journal:  Environ Pollut       Date:  2009-04-10       Impact factor: 8.071

10.  Effect of magnesium supplementation on the distribution patterns of zinc, copper, and magnesium in rabbits exposed to prolonged cadmium intoxication.

Authors:  Zorica Bulat; Danijela Dukić-Ćosić; Biljana Antonijević; Petar Bulat; Dragana Vujanović; Aleksandra Buha; Vesna Matović
Journal:  ScientificWorldJournal       Date:  2012-06-04
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