Date Awarded
2002
Document Type
Dissertation
Degree Name
Doctor of Philosophy (Ph.D.)
Department
Virginia Institute of Marine Science
Advisor
Michael C. Newman
Abstract
Environmental toxicologists adopted QSARs from pharmacology fairly early on to predict organic contaminant toxicity. In contrast, models relating metal ion characteristics to their bioactivity remain poorly explored and underutillized. Quantitative Ion Character-Activity Relationships (QICARs) have recently been developed to predict metal toxicity. The QICAR approach based on metal-ligand binding tendencies has been applied to a wide range of effects, species, and media on a single metal basis. In previous single metal studies, a softness parameter and the ; log of KOH ; were the ion qualities with the highest predictive value for toxicity. Here, QICAR modeling was brought a step further to predict toxicity of binary metal mixtures. Using the MicrotoxRTM bioassay, the interaction of binary mixtures of metals (Co, Cu, Mn, Ni, and Zn) is quantified using a linear model with an interaction term. A predictive relationship for metal interaction between pairs of metals and the difference in the softness parameter was developed. The interaction of binary mixtures of Co, Cu, Ni, and Zn was quantified using a linear model for nematode (Caenorhabditis elegans) exposures. Contrasting with earlier studies, the difference in polarizing power (Z2/r) between metal ions was the best ion characteristic for predicting interaction coefficients. Current risk assessment methods sum toxic units, assuming that all mixtures act in an additive fashion. General problems with this method are demonstrated utilizing data from the MicrotoxRTM metal mixture tests. An alternative, more accurate, method for summing toxicities with proportions instead of toxic units is illustrated. This study supports the hypothesis that general prediction of metal interactions from ion characteristics is possible. It is important to realize that even with the preliminary success of these models that additional work with metals of different valences and sizes might affect the accuracy of metal interaction predictions. Careful thought and examination of known modes of single metal toxicity should be considered when developing future quantitative metal interaction models.
DOI
https://dx.doi.org/doi:10.25773/v5-w1nf-pb08
Rights
© The Author
Recommended Citation
Ownby, David R., "Predicting metal interactions with a novel quantitative ion character -activity relationship (QICAR) approach" (2002). Dissertations, Theses, and Masters Projects. William & Mary. Paper 1539616800.
https://dx.doi.org/doi:10.25773/v5-w1nf-pb08
