The Salmonella typhimurium/mammalian microsomal assay

Kier, Larry D.; Brusick, David; Auletta, Angela E.; Halle, E. Von; Brown, Mary; Simmon, Vincent F.; Dunkel, Virginia C.; McCann, Joyce; Mortelmans, Kristien; Prival, Michael J.; Rao, T.K.; Ray, Verne A.

doi:10.1016/0165-1110(86)90002-3

Cited by 261 publications

(20 citation statements)

References 200 publications

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“…Therefore, the proportions in the three Ames classes have been relatively constant over time, with 13−16% of new agents deemed strongly positive or positive, likely reflecting the proportion of mutagenic commercial chemicals used in Japan, although the ANEI-HOU data included highly reactive synthetic intermediates, which are not final commercial products. However, in a survey of the US National Toxicology Program (NTP) database (25), the overall proportion of Ames mutagens was 35% (522/1497), while in the US EPA Gene-Tox database that summarised published Ames studies, 56% (603/1078) of the chemicals were positive (26). Many of the NTP chemicals were tested due to suspicion of carcinogenicity or mutagenicity or because they were structural analogues of known mutagens.…”

Section: Resultsmentioning

confidence: 99%

Improvement of quantitative structure–activity relationship (QSAR) tools for predicting Ames mutagenicity: outcomes of the Ames/QSAR International Challenge Project

et al. 2018

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The International Conference on Harmonization (ICH) M7 guideline allows the use of in silico approaches for predicting Ames mutagenicity for the initial assessment of impurities in pharmaceuticals. This is the first international guideline that addresses the use of quantitative structure–activity relationship (QSAR) models in lieu of actual toxicological studies for human health assessment. Therefore, QSAR models for Ames mutagenicity now require higher predictive power for identifying mutagenic chemicals. To increase the predictive power of QSAR models, larger experimental datasets from reliable sources are required. The Division of Genetics and Mutagenesis, National Institute of Health Sciences (DGM/NIHS) of Japan recently established a unique proprietary Ames mutagenicity database containing 12140 new chemicals that have not been previously used for developing QSAR models. The DGM/NIHS provided this Ames database to QSAR vendors to validate and improve their QSAR tools. The Ames/QSAR International Challenge Project was initiated in 2014 with 12 QSAR vendors testing 17 QSAR tools against these compounds in three phases. We now present the final results. All tools were considerably improved by participation in this project. Most tools achieved >50% sensitivity (positive prediction among all Ames positives) and predictive power (accuracy) was as high as 80%, almost equivalent to the inter-laboratory reproducibility of Ames tests. To further increase the predictive power of QSAR tools, accumulation of additional Ames test data is required as well as re-evaluation of some previous Ames test results. Indeed, some Ames-positive or Ames-negative chemicals may have previously been incorrectly classified because of methodological weakness, resulting in false-positive or false-negative predictions by QSAR tools. These incorrect data hamper prediction and are a source of noise in the development of QSAR models. It is thus essential to establish a large benchmark database consisting only of well-validated Ames test results to build more accurate QSAR models.

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Section: Resultsmentioning

confidence: 99%

Improvement of quantitative structure–activity relationship (QSAR) tools for predicting Ames mutagenicity: outcomes of the Ames/QSAR International Challenge Project

et al. 2018

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“…A summary of the results reported so far is presented in Table 2. When mutagenic activity was assessed in bacterial systems with the Salmonella typhimurium Ames test either positive or negative results have been reported (Simmon, 1979;Plewa et al, 1984;Kier et al, 1986). Furthermore, similar situation were observed in Escherichia coli and Bacillus subtilis when the reverse mutation assay was applied (Simmon, 1979;Leifer et al, 1981;Waters et al, 1981).…”

Section: Genotoxicity and Cytotoxicity Of Dicambamentioning

confidence: 86%

Herbicides in Argentina. Comparative Evaluation of the Genotoxic and Cytotoxic Effects on Mammalian Cells Exerted by Auxinic Members

Soloneski¹,

Larramendy²

2011

Herbicides and Environment

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“…The experiments were conducted according to OECD TG 471 [ 39 ] using bacterial tester strains (Moltox, Inc., Boone, NC, USA) Salmonella typhimurium TA98, TA100, TA1535, and TA1537 and Escherichia coli WP2 uvrA without and with a Phenobarbital/β-naphthoflavone-induced rat liver post mitochondrial supernatant (S9) (Moltox, Inc., Boone, NC, USA) metabolic activation system (S9-mix). Ultrapure water (ASTM Type 1) was chosen as the vehicle, and test item concentrations of 5000, 1600, 500, 160, 50, and 16 μg/plate were chosen for the main tests (initial plate incorporation and confirmatory pre-incubation methods using procedures adapted from Ames et al [ 40 ], Maron and Ames [ 41 ], Kier et al [ 42 ], Venitt and Parry [ 43 ], and Mortelmans and Zeiger [ 44 ]), based on preliminary solubility and concentration range finding tests. Strain specific positive controls for use without (4-Nitro-1,2-phenylenediamine, sodium azide, and 9-aminoacridine obtained from Merck Life Science GmbH (Eppelheim, Germany) and methyl methanesulfonate obtained from Sigma-Aldrich Co. (St. Louis, MO, USA)) and with (2-aminoanthracene, Sigma-Aldrich Co., (St. Louis, MO, USA)) metabolic activation were chosen based on the TG and cited literature.…”

Section: Methodsmentioning

confidence: 99%