High‐speed counter‐current chromatography assisted preparative isolation of phenolic compounds from the flowers of <i>Chrysanthemum morifolium</i> cv. Fubaiju
Bibliographic record
Abstract
Chrysanthemum morifolium cv. Fubaiju is rich in phenolic compounds with various benefits such as anti‐inflammatory, antioxidant, and cardiovascular protection. In this study, 12 phenolic compounds, including five flavonoid glycosides and seven quinic acid derivatives, were successfully separated from the flowers of Chrysanthemum morifolium cv. Fubaiju by high‐speed counter‐current chromatography and preparative high‐performance liquid chromatography. Ethyl acetate‐n‐butanol–acetonitrile–water–acetic acid (5:0.5:2.5:5:0.25, v/v/v/v/v) was selected as solvent system to separate six fractions from the flowers of Chrysanthemum morifolium cv. Fubaiju, and 20% aqueous acetonitrile (containing 0.1% formic acid) was chosen to be the elution solvent in preparative high‐performance liquid chromatography for purifying the fractions above. Luteolin‐7‐O‐β‐D‐glucoside (1), luteolin‐7‐O‐β‐D‐glucuronide (2), apigenin‐7‐O‐β‐D‐glucoside (3), luteolin‐7‐O‐β‐D‐rutinoside (4), diosmetin‐7‐O‐β‐D‐glucoside (5), chlorogenic acid (6), 1,5‐dicaffeoylquinic acid (7), 1,4‐dicaffeoylquinic acid (8), 3,4‐dicaffeoylquinic acid (9), 3,4‐dicaffeoyl‐epi‐quinic acid (10), 3,5‐dicaffeoylquinic acid (11), and 4,5‐dicaffeoylquinic acid (12) were isolated with purities all above 95%, respectively. In addition, all isolates were evaluated for their protective effects on H2O2‐induced oxidative damage in adult retinal pigment epithelial cells.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".