The anti-inflammatic activity of a sulfated polysaccharide Fucoidan in innate immune cells
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Bibliographic record
Abstract
Abstract Fucoidan is a series of natural sulfated polysaccharides derived from brown seaweeds and have reported to possess various biological activities such as anti-tumor, anti-virus, and immuno-modulatory effects. In previous study, we revealed that fucoidan derived from Cladosiphon okamuranus activated murine macrophage-like cell line RAW264 cooperatively with Zymosan, a Saccharomyces cerevisiae-derived β-glucan. On the other hand, several reports demonstrated that fucoidan inhibited lipopolysaccharide (LPS)-induced production of nitrogen oxide (NO) and inflammatory cytokines by RAW264 cells. Therefore, in this study, we investigated the potential of fucoidan derived from Undaria pinnatifida to regulate the excessive activation of RAW264 cells in response to overstimulation with pathogen components. RAW264 cells were inoculated at 20000 cells/well in 96-well culture plates, and after a recovery culture for 24 hr, the cells were treated with fucoidan with or without appropriate concentrations of each ligand for pattern recognition receptors (PRRs) including Toll-like receptors (TLRs). Whereas the production of NO was significantly enhanced with fucoidan alone, it was dose-dependently inhibited by fucoidan under stimulation with Pam3CSK4 (TLR1/TLR2 ligand), heat killed Listeria monocytogenes (HKLM, TLR2 ligand), LPS (TLR4 ligand), Pam2CGDPKHPKSF (FSL-1, TLR2/TLR6 ligand). These results suggested that fucoidan have beneficial ability to alleviate excessive inflammatory reaction during pathogenic infection and maintain suitable immune balance. Supported by Laboratory of Analytical Food Immunoscience belonging YM is a donated fund laboratory established in Faculty of Agriculture, Kyushu University by Ventuno Co., Ltd.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it