inflammation
Definition
Inflammation is a complex biological response of tissues to harmful stimuli including pathogens, damaged cells, or irritants. It involves coordinated activation of immune cells, release of inflammatory mediators (cytokines, chemokines, prostaglandins), increased vascular permeability, and recruitment of leukocytes to affected sites. This process can be acute (rapid onset, short duration) or chronic (prolonged, potentially pathological). Key cellular players include macrophages, neutrophils, mast cells, and dendritic cells, which orchestrate responses through intricate signaling cascades involving NF-κB, MAPK, and JAK-STAT pathways. While essential for tissue repair and pathogen clearance, dysregulated inflammation underlies numerous diseases including autoimmune disorders, cardiovascular disease, cancer, and neurodegenerative conditions, making it a critical therapeutic target.
Visualize inflammation in Nodes Bio
Researchers can map inflammatory signaling networks by connecting cytokines, receptors, kinases, and transcription factors to visualize cascade propagation. Network analysis reveals key regulatory nodes, feedback loops, and crosstalk between pathways. Users can overlay expression data from inflamed tissues to identify activated modules, compare acute versus chronic inflammation signatures, or model how anti-inflammatory drugs disrupt specific network connections to predict therapeutic efficacy and off-target effects.
Visualization Ideas:
- Cytokine-receptor-transcription factor signaling cascades showing inflammatory pathway activation
- Immune cell interaction networks depicting cellular crosstalk during acute versus chronic inflammation
- Drug-target networks mapping anti-inflammatory compounds to their molecular targets and downstream effects
Example Use Case
A pharmaceutical team investigating rheumatoid arthritis treatments uses network visualization to map TNF-α signaling cascades in synovial tissue. They integrate transcriptomic data from patient biopsies with protein-protein interaction networks, revealing that beyond canonical NF-κB activation, TNF-α triggers unexpected crosstalk with TGF-β pathways. By visualizing these connections, they identify SMAD3 as a novel intervention point. Network perturbation analysis predicts that dual TNF-α/TGF-β inhibition could provide superior efficacy compared to TNF-α blockade alone, guiding their combination therapy development strategy.