Purified rutin and rutin‐rich asparagus attenuates disease severity and tissue damage following dextran sodium sulfate‐induced colitis
Bibliographic record
Abstract
SCOPE: This study investigated the effects of cooked whole asparagus (ASP) versus its equivalent level of purified flavonoid glycoside, rutin (RUT), on dextran sodium sulfate (DSS)-induced colitis and subsequent colitis recovery in mice. METHODS AND RESULTS: C57BL/6 male mice were fed an AIN-93G basal diet (BD), or BD supplemented with 2% cooked ASP or 0.025% RUT for 2 wks prior to and during colitis induction with 2% DSS in water for 7 days, followed by 5 days colitis recovery. In colitic mice, both ASP and RUT upregulated mediators of improved barrier integrity and enhanced mucosal injury repair (e.g. Muc1, IL-22, Rho-A, Rac1, and Reg3γ), increased the proportion of mouse survival, and improved disease activity index. RUT had the greatest effect in attenuating DSS-induced colonic damage indicated by increased crypt and goblet cell restitution, reduced colonic myeloperoxidase, as well as attenuated DSS-induced microbial dysbiosis (reduced Enterobacteriaceae and Bacteroides, and increased unassigned Clostridales, Oscillospira, Lactobacillus, and Bifidobacterium). CONCLUSION: These findings demonstrate that dietary cooked ASP and its flavonoid glycoside, RUT, may be useful in attenuating colitis severity by modulating the colonic microenvironment resulting in reduced colonic inflammation, promotion of colonic mucosal injury repair, and attenuation of colitis-associated microbial dysbiosis.
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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 | 0.000 |
| 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 | 0.001 |
| 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".