Flavonoid Metabolites in Human Urine during Blueberry Anthocyanin Intake
Bibliographic record
Abstract
The human health benefits of anthocyanins (Anc) and other flavonoids are widely recognized. However, the flavonoid-based urinary metabolites arising in vivo after Anc intake are not well described. Human (n = 17) urine was collected while blueberry juice (BJ) was consumed daily for 28 days and once after a 7 day washout. MS/MS scanning of 664 urine samples for 18 parent Anc (PAnc) and 42 predicted Anc metabolites (AncM) yielded 371 products (i.e., MS/MS × retention time (RT)). Flavonoid-based AncM, which were likely underestimated, were almost 20 times more abundant than PAnc. Together, PAnc and AncM accounted for about 1% of the daily Anc dose. Aglycone forms were >94% of the total. Cluster analysis of the 371 Anc identified about 55 major Anc that contributed about 80% to the total Anc. The abundance of flavonoid-based Anc-derived products in the gastrointestinal tract could contribute to the health benefits of Anc-rich berries.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".