Diverse polyphenol components contribute to antioxidant activity and hypoglycemic potential of mulberry varieties
Bibliographic record
Abstract
Profiles of phenolic compounds , antioxidant activities , α -glucosidase inhibitory and anti -glycation activities of nine mulberry varieties were investigated. Twenty-three phenolic components were identified in the mulberry fruit. Chlorogenic was the predominant phenolic acid , while rutin was the most abundant flavonoid . In the colored mulberry fruits, the major anthocyanins were cyanidin-3- O -glucoside and cyanidin-3- O -rutinoside. Furthermore, we provide the first report of taxifolin- O -glucoside and two p -coumaroyl-caffeoylquinic acid isomers from mulberry fruit. The total phenolic content (TPC) ranged from 4.12 to 35.50 mg gallic acid equivalents (GAE)/g, while the total flavonoid content (TFC) varied between 1.16 and 39.95 mg rutin equivalents (RE)/g. The total anthocyanin content (TAC) ranged from 7.44 to 25.84 mg/g. The Zisang NO 1 variety presented the highest TPC, TFC and TAC with values of 35.50 mg GAE/g, 39.35 mg RE/g and 25.84 mg/g, respectively. Accordingly, it was characterized by the highest antioxidant capacity with values of 238.3 μmol Trolox equivalents (TE)/g and 560.1 μmol TE/g for DPPH and FRAP assays , respectively. Additionally, Zisang NO 1 showed better α-glucosidase inhibitory activity and anti-glycosylation activity, which may be due to its diverse polyphenolic composition. The antioxidant activity and the hypoglycemic potential were significantly higher in the colored mulberry fruits compared to the white mulberry varieties.
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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".