Cranberry proanthocyanidins affect human prostate cancer cell growth via cell cycle arrest by modulating expression of cell cycle regulators
Bibliographic record
Abstract
The effects of a proanthocyanidin‐enriched fraction (PACs) from American cranberry( V. macrocarpon ) on DU145 cancer cells’ behavior in vitro was studied. PACs was characterized by MALDI‐TOF MS to contain PAC‐oligomers ranging in size from 2–12 epicatechin units with at least one A type linkage. PACs (25 ug/mL) decreased cellular viability by ~30 % post 6h.of treatment. PACs (post 6h. exposure) increased the proportion of cells in G2‐M and decreased the proportion of cells in G1. These alterations in cell cycle were associated with changes in cell cycle regulatory proteins and other cell cycle associated activities. PACs decreased the protein expression levels of cyclin A & cyclin B1 and increased the expression of cyclin D1 & cyclin E. PACs treatment resulted in an increase in the protein expression levels of CDK2 & CDK4. Decreased p21, p16, & pRBp107 protein expression levels and increased p27 protein expression levels were evident in response to PACs treatment with no apparent alteration in the levels of pRbp130 protein. These findings demonstrate that PACs contribute to the cranberry mediated alterations in cell cycle proteins. Cranberry extracts can affect the behavior of DU145 prostate cancer cells in vitro further supporting the potential health benefits associated with cranberries. [N.C.I.C.‐ CCS, P.E‐HRP, The Cranberry Institute (Wisconsin Cranberry Board), Telus MRFD Prostate Cancer Fund (PEI Division)]
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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".