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ARS Home » Plains Area » Grand Forks, North Dakota » Grand Forks Human Nutrition Research Center » Dietary Prevention of Obesity-related Disease Research » Research » Publications at this Location » Publication #87135
Title: NONLINEAR ANALYSIS OF THE INTERACTION BETWEEN COPPER AND ZINC IN THE RAT

Author
item Zaslavsky, Boris
item Klevay, Leslie
item Uthus, Eric

Submitted to: Federation of American Societies for Experimental Biology Conference
Publication Type: Abstract Only
Publication Acceptance Date: 4/18/1998
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Metabolic interrelationships between dietary copper (Cu) and zinc (Zn) have been known for decades, but subtle relationships may have been unrecognized because of straightforward employment of linear statistical methods. Nonlinear models such as saturation curves, logarithms, or polynomials may fit the experimental data better (as related to least square deviations) and reveal previously unreported patterns. We reviewed the individual, experimental data (partially published in J. Nutr. 104:1458, 1974) from a 4x5 factorially arranged experiment in which rats were given a purified diet deficient in Cu and Zn with graded concentrations of Cu and Zn in drinking water in all combinations: Cu at 0.25, 0.5, 1 or 2 ug/ml and Zn at 2.5, 5, 10, 20 or 40 ug/ml. We confirmed that plasma cholesterol and uric acid generally decreased as Cu intake increased, but also found a small, independent decrease in these concentrations with increasing Zn. Nonlinear analysis revealed effects on granulocyte count, white cell count (WBC), and body temperature. Granulocyte counts decreased with increasing Cu at all doses of Zn, but increased and decreased respectively at low and high Cu intake. At low Cu intakes (0.25 and 0.5 ug/ml) WBC decreased with increasing Zn intake. At Cu intake of 2 ug/ml, WBC increased with increasing Zn intake; at a Cu intake of 1 ug/ml, there was no effect of Zn. Body temperature increased with Cu (Zn) at low Zn (Cu) intake and decreased with Cu (Zn) at higher Zn (Cu). Nonlinear analysis revealed relationships previously hidden and may stimulate hypotheses leading to better experiment selection.