Conjugated linoleic acid inhibits mutagenesis by 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine in the prostate of Big Blue(R) rats
Bibliographic record
Abstract
2-Amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) is a potent mutagen and carcinogen formed at high temperature during the cooking of meat. PhIP induces tumors in the colon and prostate of male rats and in the mammary gland of female rats and has been associated with the etiology of human cancers. We have recently demonstrated that PhIP induces mutations in the prostate in Big Blue transgenic rats. In the current study we have examined the effect of a dietary anti-carcinogen, conjugated linoleic acid (CLA), on PhIP-induced mutagenesis in the prostate. CLA is a mixture of positional and geometric isomers of linoleic acid and has been reported to inhibit various chemical-induced cancers in rodent models. Fifty day old male Big Blue rats were fed a standard diet containing 100 p.p.m. PhIP for 47 days, which induced a mutation frequency of 14.6 x 10(-5) in the prostate, 5.1-fold higher than that of controls. The addition of 1% CLA (w/w) in the diet starting 1 week prior to exposure to PhIP decreased PhIP-induced mutagenesis by 38% (P = 0.03). The predominant class of mutation induced by PhIP is -1 frameshifts involving the loss of G:C base pairs, followed by G:C-->T:A transversions and G:C-->A:T transitions. Addition of CLA to the diet significantly changed the PhIP-induced mutation spectrum; notably, -1 frameshifts and G:C-->A:T transitions were selectively inhibited, suggesting involvement of mismatch repair. This is the first report to show the protective effect of CLA against PhIP-induced mutagenesis in the prostate on both mutation frequency and mutational spectrum. The inhibitory effect of CLA against PhIP-induced mutagenicity suggests a possibility for its application in human chemoprevention studies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".