Quantitative 3D OPT and LSFM datasets of pancreata from mice with streptozotocin-induced diabetes

Max Hahn1, Christoffer Nord2, Pim P van Krieken3

  • 1Umeå Centre for Molecular Medicine, Umeå University, Umeå, Sweden. Max.Hahn@umu.se.

Scientific Data
|September 10, 2022
PubMed

Insights

Streptozotocin (STZ) mouse models are crucial for diabetes research. This study provides detailed 3D imaging of pancreatic beta-cell mass distribution after STZ administration, offering a comprehensive anatomical record.

Area of Science:

  • Endocrinology and Metabolism
  • Preclinical Research Models
  • Diabetes Mellitus Research

Background:

  • Streptozotocin (STZ) is widely used to induce diabetes in mouse models.
  • Previous studies lack comprehensive 3D spatial and quantitative data on pancreatic beta-cell mass distribution following STZ administration.
  • Stereological section extrapolation limits detailed anatomical understanding.

Purpose of the Study:

  • To present detailed ex vivo tomographic optical image datasets of full beta-cell mass distribution in STZ-treated mice.
  • To provide comprehensive anatomical records of STZ's effects on pancreatic islets.
  • To serve as reference material for the interpretation of STZ-induced diabetes models.

Main Methods:

  • Ex vivo tomographic optical imaging of mouse pancreas.
  • Analysis of beta-cell mass distribution after single high and multiple low doses of STZ.
  • Quantification of islet structural features, including beta-cell volume, spatial coordinates, shape, and signal intensities for insulin and GLUT2.

Main Results:

  • Detailed 3D datasets of beta-cell mass distribution are presented for various STZ administration protocols.
  • Comprehensive anatomical data on islet structure, beta-cell volume, and molecular markers (insulin, GLUT2) are provided.
  • The data captures effects of STZ on islets in both diabetic and glycaemia-recovered mice.

Conclusions:

  • This data descriptor offers the most comprehensive anatomical record of STZ's impact on mouse pancreatic islets to date.
  • The provided datasets facilitate a deeper understanding and reinterpretation of STZ-induced diabetes models.
  • This resource aids in the planning and utilization of preclinical diabetes research using STZ models.

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