# Tissue specific detection of inflammation in vivo.

> **NIH NIH R03** · LOYOLA UNIVERSITY CHICAGO · 2021 · $71,067

## Abstract

Abstract
The development and resolution of inflammation is central to the pathogenesis of numerous human diseases.
This is true of bacterial infections, in which host inflammatory responses promote pathogen clearance, as well
as inflammatory disorders, such as colitis, in which chronic inflammatory responses drive pathogenesis in local
tissue environments. In both cases, a critical mediator of cellular inflammatory responses which drive tissue
inflammation is the inflammasome, a multiprotein complex, which leads to the activation of caspase-1 and the
cleavage and release of inflammatory mediators, such as IL-1β. To monitor cellular inflammatory responses in
vivo, we have developed caspase-1 biosensors that allow the detection of inflammatory responses in the
context of mouse models of bacterial infection (S. aureus) and colitis. In this application, we propose to
develop mice expressing this novel biosensor in a tissue specific fashion. This mouse model will allow us to
define the cell types driving inflammation in the context of these established disease models as well as develop
an animal model which will be a valuable tool to monitor tissue specific inflammatory responses in the context
of numerous mouse models of human disease.

## Key facts

- **NIH application ID:** 10109431
- **Project number:** 1R03AI156507-01
- **Recipient organization:** LOYOLA UNIVERSITY CHICAGO
- **Principal Investigator:** Edward M. Campbell
- **Activity code:** R03 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $71,067
- **Award type:** 1
- **Project period:** 2021-03-18 → 2023-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10109431

## Citation

> US National Institutes of Health, RePORTER application 10109431, Tissue specific detection of inflammation in vivo. (1R03AI156507-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10109431. Licensed CC0.

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