Functions and values of sulfated polysaccharides from seaweed
Bibliographic record
Abstract
Sulfated polysaccharides (SPs) isolated from seaweed have emerged as remarkable bioactive compounds with a wide spectrum of biological activities and have substantial value in the scientific and industrial domains. The current study explores the diverse biological activities of SPs and their relationship with their structures. This aids in an in-depth examination of the multifaceted biological activities of SPs, including anticoagulant, anti-inflammatory, antiviral, antioxidant, and immunomodulatory properties, which underpin their potential health benefits. Furthermore, the current study explores the complicated properties of SPs, with their extraction methodologies and techniques for precise characterization. Elucidation of the commercial significance of SPs derived from brown, red, and green seaweed by highlighting their potential applications has emphasized their importance in human well-being. Further, this review emphasizes the challenges needed to overcome research and industrial innovations for SPs. Collaboration among researchers, industry stakeholders, and regulatory authorities can overcome these challenges and elevate the potential of SPs to revolutionize industries such as pharmaceuticals, cosmeceuticals, food, and biotechnology.
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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 | 0.001 |
| 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".