Helping Your Research
Studying the early inflammatory response is fundamental to understanding the immune response and treating disease. The nCounter® Inflammation Panel lets you perform multiplex gene expression analysis on human or mouse samples with more than 200 genes focused on the study of inflammation. These genes represent a broad range of relevant pathways related to inflammation that include apoptosis, EGF, interleukin signaling, Ras, T cell receptor, and Toll-like receptor signaling. Panel highlights include:
- Content useful for the study of asthma, allergy, arthritis, and neurological-related inflammation
- Coverage of anti-inflammatory drugs that modulate the inflammatory response
- Overlapping coverage between Human and Mouse panels for direct species comparison
- Customizable with up to 55 additional user-defined genes with the Panel Plus option
Panel Selection Tool
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Mapping the Immune Cell Microenvironment with Spatial Profiling in Muscle Tissue Injected with the Venom of Daboia russelii
Pathological and inflammatory events in muscle after the injection of snake venoms vary in different regions of the affected tissue and at different time intervals. In order to study such heterogeneity in the immune cell microenvironment, a murine model of muscle necrosis based on the injection of the venom of Daboia russelii was used.
Spatial transcriptomic characterization of COVID-19 pneumonitis identifies immune circuits related to tissue injury
Severe lung damage resulting from COVID-19 involves complex interactions between diverse populations of immune and stromal cells. In this study, we used a spatial transcriptomics approach to delineate the cells, pathways, and genes present across the spectrum of histopathological damage in COVID-19-affected lung tissue.
Digital Spatial Profiling of Glomerular Gene Expression in Pauci-Immune Focal Necrotizing Glomerulonephritis
Pauci-immune focal necrotizing glomerulonephritis (piFNGN) involves asynchronous onset and progression of injurious lesions in biopsies. Pathologists can describe this heterogeneity within a biopsy, but translating the information into prognostic or expression analyses is challenging.
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