Effect of Dietary Vitamin E on Spontaneous or Nitric Oxide Donor-Induced Mutations in a Mouse Tumor Model
Bibliographic record
Abstract
BACKGROUND: Vitamin E, an antioxidant, has been investigated for its effect on cancer incidence in humans, but no firm conclusions about a protective effect can be drawn from these studies. Recently, we reported a statistically significant correlation in the Mutatect mouse tumor model between the number of neutrophils and the frequency of mutation at the hypoxanthine phosphoribosyltransferase (hprt) locus. We have now used this model to investigate vitamin E's effect on the hprt mutation rate. METHODS: Mutatect cells were grown in mice as subcutaneous tumors for 2-3 weeks, the tumor cells were recovered, and 6-thioguanine-resistant (i.e., hprt mutant) colonies were scored. Myeloperoxidase activity was used as a measure of neutrophil infiltration. Vitamin E (2 IU/kg body weight) was provided in the diet for 3-4 weeks. In some experiments, glyceryl trinitrate (100 mg/kg body weight) was also administered as a source of nitric oxide. All statistical tests were two-sided. RESULTS: Mouse tumors from the Mutatect MN-11 cell line exhibited a 3.2-fold higher median mutation frequency than the same cells in culture (P:<. 0001); vitamin E reduced this frequency by 24.9% (P: =.01). Mutatect TM-28-derived tumors (which secrete interleukin 8) were heavily infiltrated with neutrophils and had a correspondingly high mutation frequency; in two separate experiments, vitamin E reduced the median mutation frequency by 68.9% (P: =.0019) and 84.1% (P: =.011) and myeloperoxidase levels by 75.3% (P: =.0002) and 75.5% (P: =.026), respectively. Glyceryl trinitrate increased the mutation frequency in MN-11 tumors, and vitamin E reduced the median frequency by 61.4% (P: =.058). CONCLUSIONS: Dietary vitamin E afforded strong protection against both spontaneously arising and nitric oxide-induced mutations. Two separate protective mechanisms by vitamin E may be operating: scavenging of a nitric oxide-related genotoxic species and altering the infiltration of neutrophils into tumors.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".