# Metabolic Tissue Function

> **NIH NIH P30** · WASHINGTON UNIVERSITY · 2024 · $73,863

## Abstract

PROJECT SUMMARY: Metabolic Tissue Function Core
 The purpose of the Metabolic Tissue Function Core is to improve the efficiency of diabetes-related
research through provision of expertise, equipment, and services that optimize the investigational capacity of
Washington University Diabetes Research Center (DRC) members. The Core facilitates acquisition of high
quality rodent and human islets and assists investigators in developing induced pluripotent stem cells.
In addition, the Core provides services for the functional analyses of islets and other metabolic tissues
relevant to the pathogenesis of diabetes and its complications. These functional studies include hormone
secretion assays, assessment of -cell mass, quantification of metabolism, and characterization of other
variables critical to the pathogenesis of diabetes. The Core provided services to 34 different DRC member
laboratories during the past funding period, including 6 P&F recipients, and these services supported the
publication of 51 papers. The Metabolic Tissue Function Core, through its unique expertise, state-of-the-art
equipment, and services, thus has considerable potential to contribute to the development of new therapies
likely to improve the health of Americans with diabetes, prediabetes, related endocrine and metabolic
diseases, and their devastating complications.

## Key facts

- **NIH application ID:** 10820547
- **Project number:** 5P30DK020579-47
- **Recipient organization:** WASHINGTON UNIVERSITY
- **Principal Investigator:** FUMIHIKO URANO
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $73,863
- **Award type:** 5
- **Project period:** 1996-12-01 → 2028-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10820547

## Citation

> US National Institutes of Health, RePORTER application 10820547, Metabolic Tissue Function (5P30DK020579-47). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10820547. Licensed CC0.

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