Dietary Vitamin E Affects Neutrophil Distribution and Genetic Instability in Murine Mutatect Tumors
Bibliographic record
Abstract
Vitamin E is best known for its ability to scavenge reactive oxygen and nitrogen species. Solid tumors are frequently infiltrated with leukocytes, a potential source of these reactive species. The Mutatect tumor model is a fibrosarcoma that can be grown subcutaneously in syngeneic C57BL/6 mice. We previously showed that these tumors are infiltrated with neutrophils and that the number of neutrophils correlates with the number of hypoxanthine phosphoribosyl transferase (hprt) mutations and loss of an interleukin-8 (IL-8) transgene. Neutrophils are a source of nitric oxide, and tumors contain nitrotyrosine, a marker of damage by nitric oxide-related species. We also showed previously that dietary vitamin E supplements markedly lower the frequency of hprt mutants and the level of myeloperoxidase (a neutrophil marker) in a tumor fraction containing "loosely bound" cells. In the present report, we examine the effect of dietary vitamin E in greater detail. No effect on inducible nitric oxide synthase expression or nitrotyrosine levels was observed. However, dietary vitamin E induced a major redistribution of neutrophils from the loosely bound cellular fraction to the "stromal" fraction, while the total number of neutrophils in tumors was essentially unchanged. The loss of the IL-8 transgene seen earlier in Mutatect tumors was largely prevented. Vitamin E also prevented the large increase in hprt mutants (in the cellular and stromal fractions). Thus vitamin E appears to be protective against genotoxicity by scavenging reactive species, but also its ability to affect the distribution of neutrophils within tumors may be important.
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".