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An Improved Humanized Mouse Model for Excisional Wound Healing Using Double Transgenic Mice.

Michael S Hu1, Justin Cheng2, Mimi R Borrelli1

  • 1Division of Plastic and Reconstructive Surgery, Department of Surgery, Stanford University School of Medicine, Stanford, California.

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Summary

This study introduces a new method for tracking mouse wound healing using K14-Cre/ROSAmT/mG mice and fluorescence imaging. This technique significantly improves the accuracy of determining wound closure time in vivo.

Keywords:
mouse modeltransgenic micewound healing

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Area of Science:

  • Regenerative Medicine
  • Animal Models of Disease
  • Biotechnology

Background:

  • Splinting full-thickness cutaneous wounds in mice creates a humanized model for studying wound healing.
  • Assessing epithelialization and wound closure time macroscopically has been a significant challenge in these models.

Purpose of the Study:

  • To develop and validate a novel technique for accurately determining wound healing time in mice.
  • To improve the macroscopic evaluation of wound closure using fluorescence imaging.

Main Methods:

  • Crossbreeding K14-Cre and ROSAmT/mG reporter mice to create double transgenic mice.
  • Creating full-thickness excisional wounds and imaging them with normal and fluorescent light.
  • Utilizing blinded observers to assess wound closure and histological analysis for confirmation.

Main Results:

  • Wound closure was rated significantly faster using fluorescent light compared to normal light (11.6 vs. 13.6 postoperative days).
  • Histological analysis confirmed complete reepithelialization by 12 days postwounding.
  • The novel fluorescence imaging technique enhanced the accuracy of macroscopic wound healing assessment.

Conclusions:

  • The K14-Cre/ROSAmT/mG mouse model combined with fluorescence imaging offers a significant advancement in evaluating wound healing in mice.
  • This method provides a more accurate and reliable assessment of wound closure time in vivo.
  • The technique addresses the challenge of macroscopic visualization in mouse wound healing models.