Dose-Dependent Effects of Dietary - and -Tocopherols on Genetic Instability in Mouse Mutatect Tumors
Bibliographic record
Abstract
Vitamin E in foodstuffs is a mixture of tocopherols. In mouse Mutatect tumors, a model designed to detect DNA mutations, the hypoxanthine phosphoribosyltransferase (Hprt) gene mutation frequency is associated with the number of tumor-infiltrating neutrophils and both are markedly decreased in mice fed high levels of alpha-tocopherol. Dietary alpha-tocopherol is also associated with a decrease in neutrophil-associated loss of an interleukin 8 (IL-8)-expressing transgene in this tumor model. We examined Hprt gene mutation frequency (expressed as the number of 6-thioguanine-resistant colonies per 10(5) clonable tumor cells), IL-8 transgene loss, and myeloperoxidase activity (an indirect measure of neutrophil number) in tumors from Mutatect mice fed diets supplemented with various concentrations of D-alpha-tocopherol acetate and/or D-gamma-tocopherol acetate or neither tocopherol for 4 weeks. Hprt gene mutation frequency and myeloperoxidase activity were statistically significantly lower in tumor cells from mice fed alpha-tocopherol at 50 or 100 mg/kg body weight per day than in tumor cells from mice fed 0 mg/kg body weight per day alpha-tocopherol (P<.001 for each comparison). IL-8 transgene loss occurred in 28 of 28 tumors (100%; 95% confidence interval [CI] = 86% to 100%) from mice fed alpha-tocopherol at 50 mg or less/kg body weight per day and seven of 18 tumors (39%; 95% CI = 24% to 54%) from mice fed 100 mg/kg body weight per day (P<.001, Fisher's exact test, referent groups [pooled] 0, 25, and 50 mg/kg). gamma-Tocopherol had no detectable effect on any of the three endpoints. Thus, dietary alpha-tocopherol decreases two forms of genetic instability in a dose-dependent manner in this experimental tumor model.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".