Antioxidants Block Prostate Cancer in <b> <i>Lady</i> </b> Transgenic Mice
Bibliographic record
Abstract
The development of chemopreventive agents against prostate cancer would benefit from conclusive evidence of their efficacy in animal models that emulate human disease. To date there has been little in vivo evidence supporting their preventive capabilities. The 12T-10 Lady transgenic model spontaneously develops localized prostatic adenocarcinoma and neuroendocrine cancer followed by metastases, recapitulating the natural history of human prostate cancer in many respects. Using male Lady version of the transgenic adenocarcinoma of the mouse prostate mice, we show that administration of antioxidants (vitamin E, selenium, and lycopene) in the diet dramatically inhibits prostate cancer development and increases the disease free survival. Treatment of animals with the antioxidants resulted in a 4-fold reduction in the incidence of prostate cancer compared with the untreated animals. Prostate cancer developed in 73.68% (14 of 19) and 100% (19 of 19) of the animals from the standard and high fat diet, respectively. In contrast, only 10.53% (2 of 19) and 15.79% (3 of 19; P < 0.0001) of the animals in the standard and high fat diets supplemented with antioxidants developed tumors. The micronutrients were well tolerated with no evidence of antioxidant-related toxicity. Histopathological analysis confirmed absence of cancer in the additive treated groups. Immunohistochemistry demonstrated a strong correlation between disease-free state and increased levels of the prognostic marker p27(Kip1) and a marked decrease in proliferating cell nuclear antigen expression. These observations provide support for the chemopreventive effect of these micronutrients and some clues as to their mechanism of action.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".