Phenolic Profile and Antioxidant Activity of the Edible Tree Peony Flower and Underlying Mechanisms of Preventive Effect on H2O2-Induced Oxidative Damage in Caco-2 Cells
Bibliographic record
Abstract
The entire phenolic profiles and antioxidant activities of different organs of the edible tree peony flowers (Fengdan Bai (FDB)) were analyzed. HPLC-quadrupole time-of-flight mass spectrometer (Q-TOF-MS/MS) analyses of individual phenolic compounds revealed that the petal and stamen contained higher levels of flavonoid glycosides than other organs (p < 0.05). Kaempferol-3,7-di-O-glucoside was the dominant flavonoid in these two organs, however, the calyx and ovary contained higher contents of gallic acid derivatives than other organs (p < 0.05). Hexa-O-galloyl-glucose was the dominant species in the calyx and ovary. At the same concentration of total phenolic extract (TPE), the stamen had the highest protection effect on Caco-2 cell oxidative damage induced by H2O2. The antioxidant effect was attributed to potent antioxidant capability; restored redox state due to the increased expression of glutathione peroxidase (GSH-Px) and superoxide dismutase (SOD); and improved barrier function of Caco-2 cell owing to increased zonula occludens-1 (ZO-1), CLDN3 (Claudin 3), and occludin mRNA expression. As a new resource food, the edible tree peony flower is a potential functional food material and natural antioxidants resource.
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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".