Chemistry Reference
In-Depth Information
In addition to the methods described above, those useful for quantifying metal
ion mixture bioactivities were also discussed. The general models described in
Chapter 1 are implemented with specific computer code to illustrate the two poten-
tial approaches. The first is based on similar joint action, assumes identical slopes for
similar acting metal ions, and measures deviations from identical slopes in order to
quantify departure from the assumption of similar action. This involves only probit
models for the individual metal ions alone. The second approach, which is based on
joint independent action, requires an experimental design in which different con-
centrations of each metal ion are in mixture with those of the second metal ion. An
interaction coefficient, ρ, quantifies deviations from the assumption of independent
action.
REFERENCES
Burman, P. 1996. Model fitting via testing.
Stat. Sinica
6:589-601.
Der, G., and B.S. Everitt. 2006.
Statistical Analysis of Medical Data Using SAS
. Boca Raton,
FL: Chapman and Hall/CRC.
Draper, N.R., and H. Smith. 1998.
Applied Regression Analysis, 3
rd
Edition
. New York: John
Wiley & Sons, Inc.
Finney, D.J. 1942. The analysis of toxicity tests on mixtures of poisons.
Ann. Appl. Biol.
29:82-94.
Finney, D.J. 1947.
Probit Analysis
. Cambridge: Cambridge University Press.
Hocking, R.R. 1976. The analysis and selection of variables in linear regression.
Biometrics
32:1-49.
Kinraide, T.B. 2009. Improved scales for metal ion softness and toxicity.
Environ. Toxicol.
Chem.
28:525-533.
Mallows, C.L. 1973. Some comments on C
p
.
Technometrics
15:661-675.
Mallows, C.L. 1995. More comments on C
p
.
Technometrics
37:362-372.
McCloskey, J.T., M.C. Newman, and S.B. Clark. 1996. Predicting the relative toxicity of metal
ions using ion characteristics: Microtox
®
bioluminescence assay.
Environ. Toxicol.
Chem.
15:1730-1737.
McKinney, J.D., A. Richard, C. Waller, M.C. Newman and F. Gerberick. 2000. The practice of
structure activity relationships (SAR) in toxicology.
Toxicol. Sci.
56:8-17.
Neter, J., W. Wasserman, and M.H. Kutner. 1990.
Applied Linear Statistical Models
.
Homewood, IL: Richard D. Irwin, Inc.
Newman, M.C. 1995.
Quantitative Methods in Aquatic Ecotoxicology
. Boca Raton, FL: Lewis
Publishers/CRC Press.
Newman, M.C., J.T. McCloskey, and C.P. Tatara. 1998. Using metal-ligand binding char-
acteristics to predict metal toxicity: Quantitative ion character-activity relationships
(QICARs).
Environ. Health Persp.
106:1419-1425.
Tatara, C.P., M.C. Newman, J.T. McCloskey, and P.L. Williams. 1998. Use of ion character-
istics to predict relative toxicity of mono-, di-, and trivalent metal ions.
Caenorhabditis
elegans
LC50.
Aquat. Toxicol.
42:255-269.
Walker, J.D., J.C. Dearden, T.W. Schultz, J. Jaworska, and M.H.I. Comber. 2003. QSARs
for new practitioners. In
QSARs for Pollution Prevention, Toxicity Screening, Risk
Assessment, and Web Applications
, ed. J.D. Walker, 3-18, Pensacola, FL: SETAC Press.
Wolterbeck, H.T. and T.G. Verburg. 2001. Predicting metal toxicity revisited: General proper-
ties vs. specific effects.
Sci. Total Environ.
279:87-115.
