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Updated: Feb 15, 2026

Murine Excisional Wound Healing Model and Histological Morphometric Wound Analysis
Published on: August 21, 2020
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.
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.
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.
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