Composition of Lutein Ester Regioisomers in Marigold\nFlower, Dietary Supplement, and Herbal Tea
Bibliographic record
Abstract
Characterization\nof lutein and its esters in a health product is\nnecessary for its efficacy. In the current study lutein ester regioisomers\nwere quantified and identified in several dietary supplements and\nherbal teas in comparison with marigold flower, the commercial source\nof lutein. The products were extracted with three solvents and separated\non a C30 column. The separated esters were identified/confirmed with\nLC-MS in APCI+ve mode with the use of synthetic lutein esters. The\ntotal content of lutein esters substantially varied among marigold\nflowers (167–5752 μg/g), supplements (88,000–110,700\nμg/g), and herbal teas (12.4–91.3 μg/g). Lutein\nsupplement had a lutein profile similar to that of marigold flower,\nwhereas herbal tea showed an extremely different profile. Lutein dipalmitate\nwas the dominant compound in supplements and marigold flowers followed\nby lutein 3′-<i>O</i>-myristate-3-<i>O</i>-palmitate and lutein 3′-<i>O</i>-palmitate-3-<i>O</i>-myristate. Lutein was the major compound in marigold herbal\ntea with small amounts of lutein mono- and diesters. Differences in\nthe concentration and composition of lutein compounds among marigold\nproducts could indicate distinct product quality and lutein bioavailability.
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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) | 0.310 | 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".