Activity‐guided isolation of phase II enzyme inducers from buckwheat flour methanolic extracts
Bibliographic record
Abstract
Abstract BACKGROUND Buckwheat is an important alternative crop and a raw material for functional food formulation. Phase II detoxification proteins/enzymes provide cytoprotective roles against oxidative stress and inflammation originating from various stressors. We aimed to identify and characterize potential phase II enzyme inducers from methanolic extracts of buckwheat flour, using an activity‐guided fractionation based on the induction of quinone reductase (QR) (EC 1.6.5.2) in Hepa 1c1c7 cells. RESULTS We isolated the QR inducers N‐trans ‐feruloyltyramine ( I ), syringic acid ( II ), quercetin ( III ) and myricetin ( IV ). The relative QR‐inducing ability, as well as the concentration required to double QR specific activity (CD values, in parentheses), decreased in the order: quercetin (3.0 µmol L –1 ) > N‐trans ‐feruloyltyramine (24 µmol L –1 ) > myricetin (58 µmol L –1 ) > syringic acid (5.4 mmol L –1 ). Quercetin and N‐trans ‐feruloyltyramine exhibited the greatest extent of QR induction of an approximately four‐fold maximum induction and these compounds also exhibited the greatest values for the ratio of IC 50 (i.e. level to reduce viability by 50%): CD values of 11 and > 8.3, respectively, among the four QR inducers isolated. Isobologram analyses for binary combinations of compounds I–IV revealed primarily antagonistic interactions for QR induction. CONCLUSION These findings add to our understanding of the nutraceutical potential of buckwheat as a chemoprophylactic dietary component. © 2018 Society of Chemical Industry
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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".