Composition of Lutein Ester Regioisomers in Marigold Flower, Dietary Supplement, and Herbal Tea
Bibliographic record
Abstract
Characterization of lutein and its esters in a health product is necessary for its efficacy. In the current study lutein ester regioisomers were quantified and identified in several dietary supplements and herbal teas in comparison with marigold flower, the commercial source of lutein. The products were extracted with three solvents and separated on a C30 column. The separated esters were identified/confirmed with LC-MS in APCI+ve mode with the use of synthetic lutein esters. The total content of lutein esters substantially varied among marigold flowers (167-5752 μg/g), supplements (88,000-110,700 μg/g), and herbal teas (12.4-91.3 μg/g). Lutein supplement had a lutein profile similar to that of marigold flower, whereas herbal tea showed an extremely different profile. Lutein dipalmitate was the dominant compound in supplements and marigold flowers followed by lutein 3'-O-myristate-3-O-palmitate and lutein 3'-O-palmitate-3-O-myristate. Lutein was the major compound in marigold herbal tea with small amounts of lutein mono- and diesters. Differences in the concentration and composition of lutein compounds among marigold products could indicate distinct product quality and lutein bioavailability.
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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".