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Record W2769254128 · doi:10.1002/em.22161

Structure–activity investigation of the potentiating effect of cyano substitution on nitroaniline mutagenicity in the ames test

2017· article· en· W2769254128 on OpenAlexafffund
P. David Josephy, Joban Dhanoa, George Elzawy, Kayla A. Heney, Laurenne E. Petrie, Chantel Senis

Bibliographic record

VenueEnvironmental and Molecular Mutagenesis · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCarcinogens and Genotoxicity Assessment
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAmes testChemistryNitroreductaseMutagenAdductStereochemistrySubstituentStructure–activity relationshipCarcinogenEnzymeBiochemistryOrganic chemistrySalmonellaBacteriaIn vitroGeneticsBiology

Abstract

fetched live from OpenAlex

2,6-Dicyano-4-nitroaniline and 2-cyano-4-nitroaniline (CNNA; 2-amino-5-nitrobenzonitrile) are potent mutagens in the Ames test, even though unsubstituted nitroanilines (NAs) are no more than weak mutagens. These compounds are putative reduction products of many commercial azo dyes, including Disperse Blue 165, Disperse Blue 337, Disperse Red 73, Disperse Red 82, Disperse Violet 33, and Disperse Violet 63. We have examined the mutagenicity in strains TA98 and YG1024 of a series of commercially-available isomers of CNNA, and some related compounds, to probe the relationship between structure and genotoxic activity in this class of compounds. The potentiating effect of the cyano substituent is seen in many cases; e.g. 2-amino-4-nitrobenzonitrile is a much more potent mutagen than 3-NA. 2,4-Dinitrobenzonitrile is also highly mutagenic. Possible mechanisms for the "cyano effect" are considered, with respect to the likely structures of cyanonitroaniline-DNA adducts and the roles of the enzymes (nitroreductase and acetyl CoA:arylamine N-acetyltransferase) believed to be involved in the activation of nitroaromatic compounds. Environ. Mol. Mutagen. 59:114-122, 2018. © 2017 Wiley Periodicals, Inc.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.281
Threshold uncertainty score0.326

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.004
GPT teacher head0.212
Teacher spread0.208 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2017
Admission routes2
Has abstractyes

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