Green Pea (Pisum sativum L.) Hull Polyphenol Extracts Ameliorate DSS-Induced Colitis through Keap1/Nrf2 Pathway and Gut Microbiota Modulation
Bibliographic record
Abstract
As a processing by-product, green pea hull (GPH) was found to be rich in phenolic components in our previous studies. In this study, UHPLC-LTQ-OrbiTrap-MS (Ultra performance liquid chromatography-linear ion trap orbitrap tandem mass spectrometry) technique was used to quantify polyphenols, and DSS (sodium dextran sulfate)-induced colitis mouse model was established to explore the effect of GPH extracts on colitis. The results showed that quercetin and its derivatives, kaempferol trihexanside and catechin and its derivatives were the main phenolic substances in the extract, reaching 2836.57, 1482.00 and 1339.91 µg quercetin/g GPH extract, respectively; GPH extracts can improved inflammatory status, repaired colonic function, regulated inflammatory factors, and restored oxidative balance in mice. Further, GPH extracts can activate Keap1-Nrf2-ARE signaling pathway, regulate downstream antioxidant protease and gut microbiota by increasing F/B value and promoting the growth of Lactobacillaceae and Lachnospiraceae, and improve the level of SCFAs (short-chain fatty acids) to relieve DSS-induced colitis in mice. Therefore, GPH may be a promising dietary resource for the treatment of ulcerative colitis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".