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Related Concept Videos

Inflammatory Response01:28

Inflammatory Response

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An inflammatory response is a localized, nonspecific immune reaction that occurs when a tissue is injured. It is characterized by redness, swelling, heat, and pain, which are commonly called the cardinal signs and symptoms of inflammation. Inflammation can sometimes result in a loss of function.
Inflammation can be triggered by various stimuli, such as impact, abrasion, chemical irritation, infections, and extreme hot or cold temperatures. These can damage cells and connective tissue fibers,...
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Related Experiment Video

Updated: Jan 14, 2026

Quantitative Imaging of Lineage-specific Toll-like Receptor-mediated Signaling in Monocytes and Dendritic Cells from Small Samples of Human Blood
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Quantitative Imaging of Lineage-specific Toll-like Receptor-mediated Signaling in Monocytes and Dendritic Cells from Small Samples of Human Blood

Published on: April 16, 2012

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Interpretable inflammation landscape of circulating immune cells.

Laura Jiménez-Gracia1,2,3, Davide Maspero1, Sergio Aguilar-Fernández1,4,5,6

  • 1Centro Nacional de Análisis Genómico, C/Baldiri Reixac 4, Barcelona, Spain.

Nature Medicine
|January 12, 2026
PubMed
Summary

This study created a comprehensive single-cell atlas of inflammation in over 6.5 million immune cells from 1,047 patients. This resource advances understanding of inflammatory diseases and aids in developing new diagnostic tools.

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Area of Science:

  • Immunology
  • Genomics
  • Computational Biology

Background:

  • Inflammation is crucial for homeostasis but detrimental when dysregulated.
  • A holistic understanding of inflammation across diverse diseases remains elusive.
  • Single-cell transcriptomics offers a powerful approach to dissect cellular inflammation.

Purpose of the Study:

  • To delineate inflammatory processes in circulating immune cells across various diseases using single-cell transcriptomics.
  • To build a comprehensive single-cell atlas of inflammation.
  • To lay the foundation for a machine learning-based disease classification framework.

Main Methods:

  • Leveraged single-cell transcriptomics.
  • Analyzed over 6.5 million peripheral blood mononuclear cells from 1,047 patients across 19 diseases.
  • Applied unsupervised and explainable machine learning techniques.

Main Results:

  • Generated a comprehensive single-cell atlas of inflammation in circulating immune cells.
  • Expanded knowledge on the biology of inflammation in immune-mediated diseases, infections, and cancers.
  • Identified discriminative inflammation-related genes and charted altered molecular activity.

Conclusions:

  • The study presents a rich resource for understanding immune cell inflammation.
  • Circulating immune cells can serve as living biomarkers for inflammatory diseases.
  • The findings support the development of a disease classification framework for inflammatory conditions.