Literature DB >> 12924590

Quantitative cationic-activity relationships for predicting toxicity of metals.

John D Walker1, Monica Enache, John C Dearden.   

Abstract

Developing and validating quantitative cationic-activity relationships or (Q)CARs to predict the toxicity metals is challenging because of issues associated with metal speciation, complexation and interactions within biological systems and the media used to study these interactions. However, a number of simplifying assumptions can be used to develop and validate (Q)CARs to predict the toxicity of metals: The ionic form is the most active form of a metal; the bioactivity of a dissolved metal is correlated with its free ion concentration or activity; most metals exist in biological systems as cations, and differences in metal toxicity result from differences in metal ion binding to biological molecules (ligand-binding). In summary, it appears that certain useful correlations can be made between several physical and chemical properties of ions (mostly cations) and toxicity of metals. This review provides a historical perspective of studies that have reported correlations between physical and chemical properties of cations and toxicity to mammalian and nonmammalian species using in vitro and in vivo assays. To prepare this review, approximately 100 contributions dating from 1839 to 2003 were evaluated and the relationships between about 20 physical and chemical properties of cations and their potential to produce toxic effects were examined.

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Year:  2003        PMID: 12924590     DOI: 10.1897/02-568

Source DB:  PubMed          Journal:  Environ Toxicol Chem        ISSN: 0730-7268            Impact factor:   3.742


  5 in total

1.  Toxicity testing in the 21st century: a vision and a strategy.

Authors:  Daniel Krewski; Daniel Acosta; Melvin Andersen; Henry Anderson; John C Bailar; Kim Boekelheide; Robert Brent; Gail Charnley; Vivian G Cheung; Sidney Green; Karl T Kelsey; Nancy I Kerkvliet; Abby A Li; Lawrence McCray; Otto Meyer; Reid D Patterson; William Pennie; Robert A Scala; Gina M Solomon; Martin Stephens; James Yager; Lauren Zeise
Journal:  J Toxicol Environ Health B Crit Rev       Date:  2010-02       Impact factor: 6.393

2.  Non-parametric kernel density estimation of species sensitivity distributions in developing water quality criteria of metals.

Authors:  Ying Wang; Fengchang Wu; John P Giesy; Chenglian Feng; Yuedan Liu; Ning Qin; Yujie Zhao
Journal:  Environ Sci Pollut Res Int       Date:  2015-05-09       Impact factor: 4.223

3.  Achieving global perfect homeostasis through transporter regulation.

Authors:  Yonatan Savir; Alexander Martynov; Michael Springer
Journal:  PLoS Comput Biol       Date:  2017-04-17       Impact factor: 4.475

4.  Directly Predicting Water Quality Criteria from Physicochemical Properties of Transition Metals.

Authors:  Ying Wang; Fengchang Wu; Yunsong Mu; Eddy Y Zeng; Wei Meng; Xiaoli Zhao; John P Giesy; Chenglian Feng; Peifang Wang; Haiqing Liao; Cheng Chen
Journal:  Sci Rep       Date:  2016-03-03       Impact factor: 4.379

5.  Evaluating the Metal Tolerance Capacity of Microbial Communities Isolated from Alberta Oil Sands Process Water.

Authors:  Mathew L Frankel; Marc A Demeter; Joe A Lemire; Raymond J Turner
Journal:  PLoS One       Date:  2016-02-05       Impact factor: 3.240

  5 in total

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