The Role of Seaweed Polysaccharides in Gastrointestinal Health: Protective Effect against Inflammatory Bowel Disease
Bibliographic record
Abstract
Inflammatory bowel disease (IBD) is a prominent global public health issue. Anti-inflammatory medications, immunosuppressants, and biological therapies are currently used as treatments. However, they are often unsuccessful and have negative consequences on human health. Thus, there is a tremendous demand for using natural substances, such as seaweed polysaccharides, to treat IBD's main pathologic treatment targets. The cell walls of marine algae are rich in sulfated polysaccharides, including carrageenan in red algae, ulvan in green algae, and fucoidan in brown algae. These are effective candidates for drug development and functional nutrition products. Algal polysaccharides treat IBD through therapeutic targets, including inflammatory cytokines, adhesion molecules, intestinal epithelial cells, and intestinal microflora. This study aimed to systematically review the potential therapeutic effects of algal polysaccharides on IBD while providing the theoretical basis for a nutritional preventive mechanism for IBD and the restoration of intestinal health. The results suggest that algal polysaccharides have significant potential in complementary IBD therapy and further research is needed for fully understanding their mechanisms of action and potential clinical applications.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".