Elucidation of regulatory mechanisms in the activation of dendritic cells by combined stimuli with PRR ligands and sulfated polysaccharide fucoidan
Bibliographic record
Abstract
Abstract Fucoidan, a series of natural high-molecular weight sulfated polysaccharides derived from brown algae, has been reported to have various physiological effects such as antitumor, antiviral, and immunomodulatory activities. In a previous study, we demonstrated that fucoidan from Cladosiphon okamuranus (Okinawamozuku) was effectively activate murine macrophage-like cell line RAW264 in synergistic action with dectin-1-stimulating beta-glucan from Saccharomyces cerevisiae. In this study, we further examined their synergistic mode of action of Okinawamozuku-derived fucoidan in cooperate with pathogen stimulation in terms of dendritic cell activation. After myeloid dendritic cells (mDC) and plasmacytoid dendritic cells (pDC) were differentiated by culturing bone marrow cells isolated from C57BL/6J mice with Flt3 ligand, cytokine production upon stimulation with fucoidan and various pathogen components (pattern recognition receptor, PRR ligands) was measured. As the results, fucoidan alone enhanced the production of interferon (IFN)-gamma by the Flt3-L-induced mixed BMDCs, and besides, fucoidan synergistically augmented IFN-gamma production with Pam3CSK4 (bacterial TLR1/TLR2 ligand) or Poly(I:C)/LyoVec (viral RIG-I ligand). On the other hand, their IFN-alpha productions were reinforced with Poly(I:C) (viral TLR3 ligand), ODN1585 (viral TLR9 ligand) and Poly(I:C)/LyoVec, although no synergic enhancement by fucoidan was observed. These results suggested that fucoidan was extremely effective in activating dendritic cells, which play a central role in the regulation of immune function to eliminate infectious pathogens. Supported by grants from JSPS KAKENHI (JP21K05423)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".