Comparative anti-inflammatory characterization of selected fungal and plant water soluble polysaccharides
Bibliographic record
Abstract
β-Linked water soluble polysaccharides are important bioactive components of mushrooms and plants, they possess various biological activities, such as anti-inflammation, immunomodulation, anti-tumor and others. This study aimed to examine the comparative anti-inflammatory effects of five different β-linked water soluble polysaccharides from fungi and plants [i.e. Xylaria nigripes (XN), Grifola frondosa (GF), Lentinula lentodes (Len), Laminaria digitata (Lam) and Hordeum vulgare (BG)] in lipopolysaccharides-stimulated RAW264.7 macrophages. Although the selected five polysaccharides showed different potencies in anti-inflammatory activity, XN exhibited the strongest inhibitory effects on NO, TNF-α and IL-6 production, and iNOS and COX-2 expression, whereas the inhibitory activity of BG was the weakest. Among the polysaccharides with β-(1→3, 1→6) glucose linkages and triple-helix structures, the inhibition of GF and Len on TNF-α and IL-6 production was weaker than XN and Lam. This study concludes that the monosaccharide composition, glycosidic linkage and tertiary conformation were the main factors affecting the anti-inflammatory activity of polysaccharides, and polysaccharides with β-(1→3, 1→6) glycosidic linkages possessed stronger anti-inflammatory activity than β-(1→3, 1→4)-linked polysaccharides.
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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) | 0.001 | 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".