Health benefits of algae and marine-derived bioactive metabolites for modulating ulcerative colitis symptoms
Bibliographic record
Abstract
Ulcerative colitis is a type of inflammatory bowel disease (IBD) that has risen around the world in recent years. Diet, lifestyle, genetics, stress, are the risk factors of ulcerative colitis. Indeed, oxidative stress, impairment of the intestinal barrier, inflammation, and dysbiosis of gut microbiota are the main pathways involved in ulcerative colitis. Therefore, using the anti-inflammatory and antioxidant ingredients can modulate the ulcerative colitis symptoms. Recent investigations in functional foods have demonstrated that diet and fortified foods play major therapeutic effects in human health, thus, the natural remedies have become an attractive approach. Among various natural substances, algae and marine products are valuable sources and rich in a wide range of metabolites with biological activities that can ameliorate ulcerative colitis signs. It has been reported that algal sulfated polysaccharides , peptides, pigments, polyphenols, and marine oil are useful for controlling ulcerative colitis via different pathways including modulating of TNF-α and other related inflammatory cytokines secretion, increasing the antioxidant enzymes [superoxide dismutase (SOD) and catalase(CAT)] activities, reduction of myeloperoxidase (MPO) activity and malondialdehyde (MDA) production, improving the intestinal barrier function and repairing histological damage in the colon. This review focused on the pathology of ulcerative colitis, pathogenesis and key inflammatory pathways, and the role of algae and marine-based metabolites for reduction of ulcerative colitis signs via alleviating the inflammation cytokines secretion, and improving the barrier function and gut microbiota.
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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 | 0.001 | 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) | 0.003 | 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".