The Synergistic Role of Sargassum horneri Fucoidan and Lactobacillus plantarum: Microbiome and Gut Barrier Restoration in Zebrafish Colitis
Bibliographic record
Abstract
Ulcerative colitis (UC) is a chronic inflammatory bowel disease marked by disruption of the intestinal barrier and gut microbiota imbalance, leading to significant impairment in patient quality of life. This study investigated the therapeutic efficacy of a synbiotic formulation composed of purified fucoidan from bloom-forming Sargassum horneri and the probiotic Lactobacillus plantarum in a dextran sulfate sodium (DSS)-induced zebrafish model of UC. Polysaccharides from S. horneri were extracted using Celluclast-assisted extraction and fractionated via DEAE anion-exchange chromatography, resulting in six fucoidan fractions. The sixth fraction (SH-F), with a molecular weight of 254 kDa, showed the highest fucose, sulfate contents, and demonstrated the highest effect on promoting L. plantarum growth. Structural analysis revealed that SH-F contained α-L-Fucp-(1→3), α-L-Fucp-(1→4), β-D-Galp-(1→2,3,4), α-L-Fucp-(1→3,4), and terminal α-L-Fucp residues where Fuc1(SO3)1, Gal1Fuc1(SO3)1, and Fuc2(SO3)2 were the most common glycans. Synbiotic administration significantly attenuated DSS-induced colonic shrinkage, inhibited pro-inflammatory cytokines (IL-6, TNF-ɑ, and IL-1β), restored tight junction proteins (ZO-1, occludin), and downregulated the iNOS, COX2, and NF-κB signaling pathway in adult zebrafish. 16S rRNA gene sequencing revealed restoration of gut microbial diversity and increased abundance of beneficial bacterial taxa to improve DSS-induced UC. These findings highlight the potential synergistic effects of SH-F and L. plantarum as a combinatorial strategy to regulate gut inflammation and enhance epithelial barrier function, potentially offering new insights and therapeutic opportunities for UC intervention.
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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) | 0.000 | 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".