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Record W2333205177 · doi:10.1158/1538-7445.am2011-3701

Abstract 3701: Dimethylbenzanthracene (DMBA) and DMBA dihydrodiol mutagenicity in rat epithelial and fibroblast cell lines, and its inhibition by combinations of nutraceuticals

2011· article· en· W2333205177 on OpenAlexaffabout
Peter G. Sacks, Zhonglin Zhao, Wieslawa Kosinska, Zhiming He, P. David Josephy, Joseph B. Guttenplan

Bibliographic record

VenueCancer Research · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics, phytochemicals, and oxidative stress
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsDMBAChemistryCarcinogenMetaboliteChinese hamster ovary cellBiochemistryCell cultureIn vitroMolecular biologyPharmacologyCarcinogenesisBiologyGenetics

Abstract

fetched live from OpenAlex

Abstract 7,12-Dimethylbenzanthracene (DMBA) is a potent mammary carcinogen in rats. Combinations of non-toxic nutraceutical agents, administered at or near physiological levels, were investigated for their abilities to inhibit the mutagenicity of DMBA or DMBA-dihydrodiol (DMBAD, a primary metabolite and proximate mutagen of DMBA) in vitro, in rat mammary epithelial and fibroblast cells derived from a lacI (BigBlue) Fischer rat (McDiarmid, H.M., Douglas, G.R., Coomber, B.L., and Josephy, P.D. Epithelial and fibroblast cell lines cultured from the transgenic BigBlue rat: an in vitro mutagenesis assay. Mutat. Res., 497: 39-47, 2001). In the epithelial cells, DMBA was not appreciably mutagenic at concentrations up to 4 µM, but DMBAD, was significantly mutagenic at ten-fold lower concentrations. These results indicate that the epithelial cells can bioactivate the intermediate, DMBAD, but cannot effect the complete biotransformation of DMBA to its ultimate mutagenic metabolite, DMBA-dihydrodiolepoxide. In the fibroblast cell line, in contrast, DMBA was mutagenic at concentrations as low as 20 nM and DMBAD was even more potent than DMBA. Several combinations of nutraceuticals (dietary components providing health benefits) were tested for their abilities to inhibit mutagenesis in these cell lines; the concentrations tested were based on reported serum concentrations and these were used to establish 1x concentrations. The agents and their 1x concentrations were: resveratrol (Res), 2.4 μM; sulforaphane (Sul), 0.06 μM; antioxidant mix (α- and γ-tocopherol, 30 μM, plus vitamin C, 68 μM – VCE); α-lipoic acid (LA), 2 μM; epigallocatechin gallate (EGCG), 0.7 μM; and N-acetylcysteine (NAC), 12 μM. None of the agents or their combinations, tested at 1 – 3 x concentrations, showed any cytotoxicity. In both epithelial and fibroblast cells, Sul and Res alone slightly inhibited mutagenesis at 2x concentrations; no other agents had observable effects. All binary combinations of Res, LA, and Sul, at 2x concentrations, inhibited mutagenesis; the Res + Sul combination was particularly effective (ca. 50% inhibition). These results suggest a role for fibroblast cells in the bioactivation of carcinogens, implicating the microenvironment, and indicate that combinations of nutraceuticals can inhibit mutagenesis by polycyclic aromatic hydrocarbons. Supported by the Susan Komen Foundation grant # KG080836 (JBG) and NSERC Canada (PDJ). Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 3701. doi:10.1158/1538-7445.AM2011-3701

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.051
GPT teacher head0.339
Teacher spread0.288 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2011
Admission routes2
Has abstractyes

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