Antioxidant, Scavenging, Reducing, and Anti-Proliferative Activities of Selected Tropical Brown Seaweeds Confirm the Nutraceutical Potential of Spatoglossum asperum
Bibliographic record
Abstract
Brown seaweeds have shown high potential of bioactivity and provide health benefits as an important functional food ingredient. Therefore, four abundantly growing tropical brown seaweeds—Iyengaria stellata, Spatoglossum asperum, Sargassum linearifolium, and Stoechospermum polypodioides—were collected from the Saurashtra Coast of the Arabian Sea. They were analyzed for metabolite profiling, biochemical activities (including total antioxidant, reducing, scavenging, and anti-proliferative characteristics), and total phenolic and flavonoid contents. A concentration-dependent antioxidant, reducing, and scavenging activities were observed for all four brown seaweeds. The S. asperum and I. stellata extracts showed maximum total antioxidant activity. S. asperum also showed high scavenging and reducing activities compared to other studied brown seaweeds. Further, S. asperum contained high total phenolic and flavonoid content compared to other brown seaweeds collected from the same coast. A multivariate correlation study confirmed a positive correlation between total phenolic and flavonoid contents, and biochemical activities (total antioxidant, scavenging and reducing) for all brown seaweeds. About 35% anti-proliferative activity was observed with S. asperum extract on Huh7 cells; in contrast S. polypodioide showed about 44% proliferation inhibition of Huh7 cells. Similarly, 26% proliferation inhibition of HeLa cells was observed with S. asperum extract. Overall, S. asperum possesses high total flavonoid and phenolic amounts, and showed potential antioxidant, scavenging and reducing characteristics. The study confirmed the nutraceutical potential of S. asperum and that it could be a promising functional food ingredient.
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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) | 0.001 | 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".