Micronutrients attenuate progression of prostate cancer by elevating the endogenous inhibitor of angiogenesis, Platelet Factor-4
Bibliographic record
Abstract
BACKGROUND: Longstanding evidence implicates an inadequate diet as a key factor in the onset and progression of prostate cancer. The purpose herein was to discover, validate and characterize functional biomarkers of dietary supplementation capable of suppressing the course of prostate cancer in vivo. METHODS: The Lady transgenic mouse model that spontaneously develops prostate cancer received a diet supplemented with a micronutrient cocktail of vitamin E, selenium and lycopene ad libitum. A proteomic analysis was conducted to screen for serum biomarkers of this dietary supplementation. Candidate peptides were validated and identified by sequencing and analyzed for their presence within the prostates of all mice by immunohistochemistry. RESULTS: Dietary supplementation with the combined micronutrients significantly induced the expression of the megakaryocyte-specific inhibitor of angiogenesis, platelet factor-4 (P = 0.0025). This observation was made predominantly in mice lacking tumors and any manifestations associated with progressive disease beyond 37 weeks of life, at which time no survivors remained in the control group (P < 0.0001). While prostates of mice receiving standard chow were enlarged and burdened with poorly differentiated carcinoma, those of mice on the supplemented diet appeared normal. Immunohistochemical analysis revealed marked amplifications of both platelet binding and platelet factor-4 within the blood vessels of prostates from mice receiving micronutrients only. CONCLUSION: We present unprecedented data whereby these combined micronutrients effectively promotes tumor dormancy in early prostate cancer, following initiation mutations that may drive the angiogenesis-dependent response of the tumor, by inducing platelet factor-4 expression and concentrating it at the tumor endothelium through enhanced platelet binding.
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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 | 0.000 | 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) | 0.001 | 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".