Characterization of the Interindividual Variability Associated with the Microbial Metabolism of (−)-Epicatechin
Bibliographic record
Abstract
Although the relationship between gut microbiota and flavan-3-ol metabolism differs greatly between individuals, the specific metabolic profiles, known as metabotypes, have not yet been clearly defined. In this study, fecal batch fermentations of 34 healthy donors inoculated with (−)-epicatechin were stratified into groups based on their conversion rate of (−)-epicatechin and their quali–quantitative metabolic profile. Fast and slow converters of (−)-epicatechin, high producers of 1-(3′-hydroxyphenyl)-3-(2″,4″,6″-trihydroxyphenyl)-propan-2-ol (3-HPP-2-ol) and 5-(3′,4′-dihydroxyphenyl)-γ-valerolactone (3,4-DHPVL) were identified. Fecal microbiota analysis revealed that fast conversion of (−)-epicatechin was associated with short-chain fatty acid (SCFA)-producing bacteria, such as Faecalibacterium spp. and Bacteroides spp., and higher levels of acetate, propionate, butyrate, and valerate were observed for fast converters. Other bacteria were associated with the conversion of 1-(3′,4′-dihydroxyphenyl)-3-(2″,4″,6″-trihydroxyphenyl)-propan-2-ol into 3-HPP-2-ol ( Lachnospiraceae UCG-010 spp.) and 3,4-DHPVL ( Adlercreutzia equolifaciens ). Such stratification sheds light on the mechanisms of action underlying the high interindividual variability associated with the health benefits of flavan-3-ols.
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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) | 0.000 | 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) | 0.001 | 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".