In vitro simulated saliva, gastric, and intestinal digestion followed by faecal fermentation reveals a potential modulatory activity of Epimedium on human gut microbiota
Bibliographic record
Abstract
Herba Epimedii, known for its rich array of bioactive ingredients and widespread use in ethnopharmacological practices, still lacks a comprehensive understanding of its gastrointestinal biotransformation. In this study, we qualitatively explored the dynamic changes in Epimedium sagittatum components during in vitro simulated digestions, with a quantitative focus on its five major flavonoids. Notably, significant metabolism of E. sagittatum constituents occurred in the simulated small intestinal fluid and colonic fermentation stages, yielding various low molecular weight metabolites. Flavonoids like kaempferol glycosides were fully metabolized in the simulated intestinal fluid, while hyperoside digestion occurred during simulated colon digestion. Colonic fermentation led to the production of two known bioactive isoflavones, genistein, and daidzein. The content and bioaccessibility of the five major epimedium flavonoids-icariin, epimedin A, epimedin B, epimedin C, and baohuoside I-significantly increased after intestinal digestion. During colon fermentation, these components gradually decreased but remained incompletely metabolized after 72 h. Faecal samples after E. sagittatum fermentation exhibited shift towards dominance by Lactobacillus (Firmicutes), Bifidobacterium (Actinobacteria), Streptococcus (Firmicutes), and Dialister (Firmicutes). These findings enhance our comprehension of diverse stages of Herba Epimedii constituents in the gut, suggesting that the primary constituents become bioaccessible in the colon, where new bioactive compounds may emerge.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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".