Linked Life Data

9860893

Source:http://linkedlifedata.com/resource/pubmed/id/9860893

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
1999-4-20
pubmed:abstractText
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 five 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 5(5) 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.
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
0091-6765
pubmed:author
pubmed:issnType
Print
pubmed:volume
106 Suppl 6
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1361-5
pubmed:dateRevised
2009-11-18
pubmed:meshHeading
pubmed:year
1998
pubmed:articleTitle
Statistically designed experiments to screen chemical mixtures for possible interactions.
pubmed:affiliation
TNO, Nutrition and Food Research Institute, Toxicology Division, Zeist, The Netherlands. groten@voeding.tno.nl
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't