Comparison of Phenolic and Flavonoid Compound Profiles and Antioxidant and α-Glucosidase Inhibition Properties of Cultivated Soybean (Glycine max) and Wild Soybean (Glycine soja)
Bibliographic record
Abstract
Wild soybean (Glycine soja Sieb.et Zucc; WS) has been used as a traditional food in China for many years and contains significantly higher levels of isoflavones than cultivated soybean (Glycine max; CS), but the secondary metabolites, including flavonoids and the phenolic composition differences between them, remain unclear. The results showed that WS possessed significantly higher total phenolic and flavonoid content and exhibited better antioxidant and α-glucosidase inhibition activities as well as excellent protective effects against H2O2-induced oxidative injury in a human endothelial cell line. Through metabolomic analysis, 642 metabolites were identified, and 238 showed differential expression, with 151 upregulated and 87 downregulated. A total of 79 flavonoid compounds were identified, 42 of which were upregulated in WS. 2′-Hydroxygenistein, garbanzol, protocatechuic aldehyde, ligustilide, and resveratrol were the most discriminated compounds in WS. The metabolic pathway analysis of differential metabolites related to the biosynthesis of flavonoids and phenolic acids were the biosynthesis of phenylpropanoids, flavonoids, isoflavonoids, flavones, and flavonols. This study substantially elucidated differences in the content of flavonoids and biological activities between WS and CS, which is useful information for the effective utilization of these two black soybean species in food processing.
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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) | 0.000 | 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".