Ursolic acid and its esters: occurrence in cranberries and other <i>Vaccinium</i> fruit and effects on matrix metalloproteinase activity in DU145 prostate tumor cells
Bibliographic record
Abstract
BACKGROUND: Ursolic acid and its cis- and trans-3-O-p-hydroxycinnamoyl esters have been identified as constituents of American cranberries (Vaccinium macrocarpon), which inhibit tumor cell proliferation. Since the compounds may contribute to berry anticancer properties, their content in cranberries, selected cranberry products, and three other Vaccinium species (V. oxycoccus, V. vitis-idaea and V. angustifolium) was determined by liquid chromatography-mass spectroscopy. The ability of these compounds to inhibit growth in a panel of tumor cell lines and inhibit matrix metalloproteinase (MMP) activity associated with tumor invasion and metastasis was determined in DU145 prostate tumor cells. RESULTS: The highest content of ursolic acid and esters was found in V. macrocarpon berries (0.460-1.090 g ursolic acid and 0.040-0.160 g each ester kg(-1) fresh weight). V. vitis-idaea and V. angustifolium contained ursolic acid (0.230-0.260 g kg(-1) ), but the esters were not detected. V. oxycoccus was lowest (0.129 g ursolic acid and esters per kg). Ursolic acid content was highest in cranberry products prepared from whole fruit. Ursolic acid and its esters inhibited tumor cell growth at micromolar concentrations, and inhibited MMP-2 and MMP-9 activity at concentrations below those previously reported for cranberry polyphenolics. CONCLUSION: Cranberries (V. macrocarpon) were the best source of ursolic acid and its esters among the fruit and products tested. These compounds may limit prostate carcinogenesis through matrix metalloproteinase inhibition.
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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 | 0.001 | 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".