Biotransformation of Cranberry Proanthocyanidins to Probiotic Metabolites by<i>Lactobacillus rhamnosus</i>Enhances Their Anticancer Activity in HepG2 Cells<i>In Vitro</i>
Bibliographic record
Abstract
This study was designed to unravel the role of Lactobacillus rhamnosus in the bioconversion of cranberry proanthocyanidins and cytotoxicity of resulting metabolites to hepatocellular carcinoma HepG2 cells. Crude (CR) and flavonol+dihydrochalcone- (FL+DHC-), anthocyanin- (AN-), proanthocyanidin- (PR-), and phenolic acid+catechin- (PA+C-) rich fractions were subjected to fermentation with L. rhamnosus at 37°C for 12, 24, and 48 h under anaerobic conditions. The major metabolites produced by bioconversion of polyphenols were 4-hydroxyphenylacetic acid, 3-(4-hydroxyphenyl)propionic acid, hydrocinnamic acid, catechol, and pyrogallol. Furthermore, cytotoxicity of the biotransformed extracts was compared to their parent extracts using human hepatocellular carcinoma HepG2 cells. The results showed that PR-biotransformed extract completely inhibited HepG2 cell proliferation in a dose- and time-dependent manner with IC 50 values of 47.8 and 20.1 μ g/mL at 24 and 48 h, respectively. An insight into the molecular mechanisms involved revealed that the cytotoxic effects of PR at 24 h incubation were mitochondria-controlled and not by proapoptotic caspase-3/7 dependent. The present findings suggest that the application of a bioconversion process using probiotic bacteria can enhance the pharmacological activities of cranberry proanthocyanidins by generating additional biologically active metabolites.
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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) | 0.000 | 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 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".