The epigenetic potentials of dietary polyphenols in prostate cancer management
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Prostate cancer is a disease that is greatly affected by lifestyle, particularly diet, and is more prevalent in US and European countries compared with South and East Asia. Among several known causes and risk factors, nutrition plays an important role in prostate cancer pathogenesis. Various dietary components including polyphenols have been shown to possess anticancer properties. Dietary polyphenols have been the subject of extensive studies for the last decade because of their anticancer and chemopreventive potentials. Besides possessing various antitumor properties, dietary polyphenols also contribute to epigenetic changes associated with the fate of cancer cells and have emerged as potential drugs for therapeutic intervention. Various polyphenols have been shown to affect DNA methylation, histone posttranslational modifications, and microRNA expression patterns in prostate cancer. In this review, we discuss the contribution of dietary polyphenols to various epigenetic modifications in prostate cancer. Since prostate cancer and diet are intimately associated, polyphenol-rich diets that epigenetically modify tumor biology have great significance in the prevention and management of prostate cancer.
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.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it