Anthocyanin metabolites in human urine and serum
Bibliographic record
Abstract
In the present study we investigated the metabolic conversion of cyanidin glycosides in human subjects using solid-phase extraction,HPLC-diode array detector, MS, GC, and enzymic techniques. Volunteers consumed approximately 20 g chokeberry extract containing 1.3 g cyanidin 3-glycosides (899 mg cyanidin 3-galactoside, 321 mg cyanidin 3-arabinoside, 51 mg cyanidin 3-xyloside and 50 mg cyanidin 3-glucoside). Blood samples were drawn at 0, 0.5, 1, and 2 h post-consumption of the extract. Urine samples were also collected at 0, 4-5,and 22-24h. We have confirmed that human subjects have the capacity to metabolise cyanidin 3-glycosides, as we observed at least ten individual anthocyanin metabolites in the urine and serum. Average concentrations of anthocyanins and anthocyanin metabolites in the urine reached levels of 17.9 (range 14.9-20.9) l.mol/l within 5 h post-consumption and persisted in 24h urine samples at levels of 12.1 (range 11.1-13.0) nmol/l. In addition, average total levels of anthocyanins and anthocyanin metabolites detected in the serum were observed at 5917 (range 197.3-986.1) nmol/ within 2h post-consumption. Cyanidin 3-galactoside accounted for 55.4% (9.9(range 7-2-12-6) l.mol/) and 66.0% (390.6 (range 119.4-661-9) nmol V) of the detected anthocyanins in the urine and serum samples,respectively. The metabolites were identified as glucuronide conjugates, as well as methylated and oxidised derivatives of cyanidin 3-galactoside and cyanidin glucuronide. Conjugation probably affects the biological activity of anthocyanins and these metabolic products are likely in part responsible for the reported health benefits associated with the consumption of anthocyanins.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".