Synbiotic regulation of chronic intestinal inflammation by Sargassum horneri fucoidan and Lactobacillus plantarum
Bibliographic record
Abstract
Severe inflammation in the intestinal tract is a hallmark of Inflammatory Bowel Disease (IBD). The present study explores the synbiotic potential of bloom seaweed Sargassum horneri fucoidan with Lactobacillus plantarum in preventing intestinal inflammation. Six fucoidan fractions were isolated via DEAE anion exchange chromatography, with SHF6 showing the highest sulfate and fucose content and significantly promoting L. plantarum growth. Synbiotic treatment of SHF6 and L. plantarum on 3 % DSS-induced HT-29 cells significantly improved cell viability, downregulated pro-inflammatory cytokines (IL-6, IL-8, TNF-α, IL-12, IL-1β), downregulated NF-κB/IL6/STAT3 pathway protein expression, and restored tight junction protein expression. In DSS-induced zebrafish larvae, the synbiotic treatment improved healthy intestinal lysosome number and improved mucin production. qPCR analysis showed decreased IL-1β, IL-6, TNF-α, and iNOS gene expressions and increased mucin 2 expression. These findings indicated that SHF6 and L. plantarum exhibit synergistic anti-inflammatory effects, highlighting their potential as a promising therapy for intestinal inflammation. • Sargassum horneri fucoidan (SHF6) contains high fucose and sulfate content. • SHF6, L. plantarum synbiotic therapy reduced DSS-induced pro-inflammatory cytokines production. • Synbiotic treatment inhibited NF-κb/IL-6/STAT3 signaling in DSS-induced HT-29 cells. • Synbiotic treatment restored tight junction protein expression in DSS-induced HT-29 cells. • Synbiotic treatment downregulated the inflammation in DSS-treated zebrafish larvae.
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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 | 0.000 |
| 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".