Cellular Antioxidant Effect of an Aronia Extract and Its Polyphenolic Fractions Enriched in Proanthocyanidins, Phenolic Acids, and Anthocyanins
Bibliographic record
Abstract
Oxidative stress and chronic inflammation contribute to some chronic diseases. Aronia berries are rich in polyphenols. The aim of the present study was to characterize the cellular antioxidant effect of an aronia extract to reflect the potential physiological in vivo effect. Cellular in vitro assays in three cell lines (Caco-2, HepG2, and SH-SY5Y) were used to measure the antioxidant effect of AE, in three enriched polyphenolic fractions (A1: anthocyanins and phenolic acids; A2: oligomeric proanthocyanidins; A3: polymeric proanthocyanidins), pure polyphenols and microbial metabolites. Both direct (intracellular and membrane radical scavenging, catalase-like effect) and indirect (NRF2/ARE) antioxidant effects were assessed. AE exerted an intracellular free radical scavenging activity in the three cell lines, and A2 and A3 fractions showed a higher effect in HepG2 and Caco-2 cells. AE also exhibited a catalase-like activity, with the A3 fraction having a significant higher activity. Only A1 fraction activated the NRF2/ARE pathway. Quercetin and caffeic acid are the most potent antioxidant polyphenols, whereas cyanidin and 5-(3',4'-dihydroxyphenyl)-γ-valerolactone showed the highest antioxidant effect among polyphenol metabolites. AE rich in polyphenols possesses broad cellular antioxidant effects, and proanthocyanidins are major contributors. Polyphenol metabolites may contribute to the overall antioxidant effect of such extract in vivo.
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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".