Dendritic Polyglycerol Sulfate Reduces Inflammation Through Inhibition of the HMGB1/RAGE Axis in RAW 264.7 Macrophages
Bibliographic record
Abstract
High Mobility Group Box 1 (HMGB1) is a central pro-inflammatory mediator released from damaged or stressed cells, where it activates receptors such as the Receptor for Advanced Glycation Endproducts (RAGE). Dendritic polyglycerol sulfate (dPGS), a hyperbranched polyanionic polymer, is known for its anti-inflammatory activity. In this study, we examined how dPGS modulates HMGB1-driven signaling in RAW 264.7 macrophages and human microglia. Recombinant human HMGB1 expressed in Escherichia coli (E. coli) was purified by nickel-nitrilotriacetic acid (Ni-NTA) and heparin chromatography. Proximity ligation assays (PLA) revealed that dPGS significantly disrupted HMGB1/RAGE interactions, particularly under lipopolysaccharide (LPS) stimulation, thereby reducing inflammatory signaling complex formation. This correlated with reduced activation of the nuclear factor kappa B (NF-κB) pathway, demonstrated by decreased nuclear translocation and transcriptional activity. Reverse transcription polymerase chain reaction (RT-PCR) and quantitative real-time PCR (RT-qPCR) showed that dPGS suppressed HMGB1- and LPS-induced transcription of tumor necrosis factor alpha (TNF-α), interleukin-6 (IL-6), monocyte chemoattractant protein-1 (MCP-1), cyclooxygenase-2 (COX-2), and inducible nitric oxide synthase (iNOS). Enzyme-linked immunosorbent assay (ELISA) and Griess assays confirmed reduced TNF-α secretion and nitric oxide production. Electron paramagnetic resonance (EPR) spectroscopy further showed that dPGS altered HMGB1/soluble RAGE (sRAGE) complex dynamics, providing mechanistic insight into its receptor-disruptive action.
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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 | 0.001 |
| 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".