Effects of Red Sorghum-Derived Deoxyanthocyanidins and Their O-β-D-Glucosides on E-Cadherin Promoter Activity in PC-3 Prostate Cancer Cells
Bibliographic record
Abstract
Although much less common than anthocyanins, 3-Deoxyanthocyanidins (3-DAs) and their glucosides can be found in cereals such as red sorghum. It is speculated that their bioavailability is higher than that of anthocyanins. Thus far, little is known regarding the therapeutic effects of 3-DAs and their O-β-D-glucosides on cancer, including prostate cancer. Thus, we evaluated their potential to decrease cell viability, to modulate the activity of transcription factors such as NFκB, CREB, and SOX, and to regulate the expression of the gene CDH1, encoding E-Cadherin. We found that 4′,7-dihydroxyflavylium chloride (P7) and the natural apigeninidin can reduce cell viability, whereas 4′,7-dihydroxyflavylium chloride (P7) and 4′-hydroxy-7-O-β-D-glucopyranosyloxyflavylium chloride (P3) increase the activities of NFkB, CREB, and SOX transcription factors, leading to the upregulation of CDH1 promoter activity in PC-3 prostate cancer cells. Thus, these compounds may contribute to the inhibition of the epithelial-to-mesenchymal transition in cancer cells and prevent the metastatic activity of more aggressive forms of androgen-resistant prostate cancer.
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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".