<i>In vitro</i> antioxidant synergism and antagonism between food extracts can lead to similar activities in H<sub>2</sub>O<sub>2</sub>‐induced cell death, caspase‐3 and MMP‐2 activities in H9c2 cells
Bibliographic record
Abstract
BACKGROUND: The cardio-health-promoting activity of some foods may be due to their specific antioxidant content. The antioxidant activity of a mixture of plant extracts has been shown to differ from the activity of the individual extracts. As a result, the activity of the mixture can be described as synergistic, antagonistic or additive. This in vitro study evaluated the relationship between the in vitro antioxidant capacity of mixtures and their bioactivity when cardiomyocytes (H9c2) were challenged with H(2)O(2). RESULTS: A mixture of raspberry and adzuki bean extracts produced a synergistic response and a mixture of broccoli and soybean extracts produced an antagonistic response in chemical-based antioxidant assays. When these extracts were tested in cell cultures, individually and in mixtures, the mixture of raspberry and adzuki bean protected the cardiomyocytes from H(2)O(2)-induced cell damage significantly better than the individual extracts. Conversely, the mixture of broccoli and soybean extracts was less effective in protecting H9c2 cells. The synergistic and antagonistic effects of the mixtures in protecting cell damage were brought about by enhanced or reduced ability in attenuating caspase-3 and matrix metalloproteinase-2 activities elevated by H(2)O(2). CONCLUSION: Food mixtures with synergistic antioxidant activity and protective property against reactive oxygen species-induced cell death can potentially be incorporated into novel functional foods or beverages with optimum health benefit. The antagonistic effect of food mixtures can be a health concern and thus should be avoided.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".