Identification of Triterpene Hydroxycinnamates with <i>in Vitro</i> Antitumor Activity from Whole Cranberry Fruit (<i>Vaccinium macrocarpon</i>)
Bibliographic record
Abstract
Bioactivity-guided fractionation of cranberry fruit was used to determine the identity of triterpenoid esters from Vaccinium macrocarpon, which inhibit tumor cell growth and may play a role in cancer prevention. In our previous study, a fraction from whole fruit exhibited tumor cell growth inhibition in vitro. The major components of this fraction were isolated by chromatographic separation of ethyl acetate extracts, purified by semipreparative HPLC, and identified by NMR as cis- (1) and trans- (2) isomers of 3-O-p-hydroxycinnamoyl ursolic acid. These triterpenoid esters have not been previously reported in Vaccinium fruit. Bioassay of the purified triterpene cinnamates in tumor cell lines in vitro showed slightly greater activity of compound 1 in most cell lines, with GI(50) values of approximately 20 microM in MCF-7 breast, ME180 cervical and PC3 prostate tumor cell lines. Quercetin was slightly less active than 1, while cyanidin-3-galactoside exhibited much lower cytotoxicity, with GI(50) greater than 250 microM in all cell lines. Phenylboronic acid (3) was also isolated from the fruit but showed insignificant antitumor activity.
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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".