Statistically designed experiments to screen chemical mixtures for possible interactions
article
For the accurate analysis of possible interactive effects of chemicals in a defined mixture, statistical designs are necessary to develop clear and manageable experiments. For instance, factorial designs have been successfully used to detect two-factor interactions. Particularly useful for this purpose are fractionated factorial designs, requiring only a fraction of all possible combinations of a full factorial design. Once the potential interaction has been detected with a fractionated design, a more accurate analysis can be performed for the particular binary mixtures to ensure and characterize these interactions. In this paper this approach is illustrated using an in vitro cytotoxicity assay to detect the presence of mixtures of Fusarium mycotoxins in contaminated food samples. We have investigated interactions between live mycotoxin species (Trichothecenes, Fumonisins, and Zearalenone) using the DNA synthesis inhibition assay in L929 fibroblasts. First, a central composite design was applied to identify possible interactive effects between mycotoxins in the mixtures (27 combinations from 55 possible combinations). Then two-factor interactions of particular interest were further analyzed by the use of a full factorial design (5 x 5 design) to characterize the nature of those interactions more precisely. Results show that combined exposure to several classes of mycotoxins generally results in effect addition with a few minor exceptions indicating synergistic interactions. In general, the nature of the interactions characterized in the full factorial design was similar to the nature of those observed in the central composite design. However, the magnitude of interaction was relatively small in the full factorial design.
Topics
BioassayBox Behnken designCentral composite designFactorial designFractionated factorial designMixturesMycotoxinsMycotoxinAccuracyAnalysisChemical interactionConference paperCytotoxicityDNA synthesis inhibitionFactorial analysisFibroblastFood contaminationFusariumPriority journalScreeningStatistical analysisAlgorithmsCell LineData Interpretation, StatisticalDNADrug InteractionsHumansMycotoxinsResearch DesignToxicity TestsFusarium
TNO Identifier
234723
ISSN
00916765
Source
Environmental Health Perspectives, 106(SUPPL. 6), pp. 1361-1365.
Pages
1361-1365