Mouse skin tumor initiation-promotion and complete carcinogenesis bioassays: mechanisms and biological activities of emission samples.
Author(s) -
Stephen Nesnow,
Larry L. Triplett,
T.J. Slaga
Publication year - 1983
Publication title -
environmental health perspectives
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.257
H-Index - 282
eISSN - 1552-9924
pISSN - 0091-6765
DOI - 10.1289/ehp.8347255
Subject(s) - carcinogen , chemistry , bioassay , tar (computing) , environmental chemistry , stove , diesel fuel , particulates , dmba , pulp and paper industry , environmental science , carcinogenesis , waste management , organic chemistry , biology , biochemistry , genetics , computer science , gene , engineering , programming language
Extracts of soots obtained from various sources were applied to the skin of mice in an effort to identify carcinogens in these mixtures and to link these materials to the etiology of human cancer. Samples of coal chimney soot, coke oven materials, industrial carbon black, oil shale soot, and gasoline vehicle exhaust materials have been examined by this method. The studies reported here have been constructed to compare the carcinogenic and tumorigenic potency of extracts from various particulate emissions: coke ovens, diesel and gasoline vehicles and a roofing tar pot. Automobile emission samples were obtained by collecting the diluted and cooled exhaust on Teflon-coated glass fiber filters. Coke oven and roofing tar samples were particulate emission samples collected by impaction and filtration. The organic components associated with each of the particles were extracted with dichloromethane and dermally applied to SENCAR mice. All agents were applied as tumor initiators by using a five-dose protocol. Selected extracts were also applied as complete carcinogens and as tumor promotors. Statistical analyses of the resulting tumor data were performed by using nonlinear Poisson and probit models. The results from these experiments provide a suitable data base for comparative potency estimation of complex mixtures.
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