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Record W2137496599 · doi:10.1207/s15327914nc5002_6

Chemoprotection Against N-Nitrosomethylbenzylamine-Induced Mutation in the Rat Esophagus

2004· article· en· W2137496599 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNutrition and Cancer · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSesame and Sesamin Research
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsNitrosamineEllagic acidChemistryEthanolCarcinogenCarcinogenesisPharmacologyEsophagusBiochemistryMolecular biologyBiologyGeneAntioxidantAnatomyPolyphenol

Abstract

fetched live from OpenAlex

Prevention of esophageal cancer may be possible through dietary modification or supplementation. In this study we have investigated the mutation preventive properties of ellagic acid, green tea, and diallyl sulfide (DAS) against the mutagenicity of the nitrosamine N-nitrosomethylbenzylamine (NMBA) in the esophagus of the rat. In addition, the effect of the consumption of ethanol on the mutagenicity of NMBA was examined. NMBA is specific in inducing tumors in the rat esophagus and has been used in many studies investigating the mechanism and the prevention of this cancer. We found that the type of mutations induced by two 2-mg/kg subcutaneous injections of NMBA in the lacI gene of "Big Blue" rats is consistent with that found previously for nitrosamines in other systems and consists of G:C-->A:T transitions. We report that the addition of ellagic acid to the feed, replacing drinking water with green tea, and gavage with DAS significantly reduced the mutagenicity of NMBA. In contrast, the addition of 5% ethanol to the drinking water increased the mutagenicity of NMBA. This is consistent with findings that these compounds modulate NMBA-induced carcinogenesis in the rat.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.514
Threshold uncertainty score0.122

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 head0.041
GPT teacher head0.293
Teacher spread0.252 · 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