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Related Experiment Video

Updated: Jul 24, 2025

Digital Planimetry for Assessing Wound Closure Kinetics in a Mouse Model
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Quantifying innervation facilitated by deep learning in wound healing.

Abijeet Singh Mehta, Sam Teymoori, Cynthia Recendez

    Biorxiv : the Preprint Server for Biology
    |July 3, 2023
    PubMed
    Summary

    Peripheral nerves (PNs) are crucial for wound healing. This study developed an automated method using deep learning to quantify skin re-innervation, revealing a strong correlation between nerve density and tissue repair.

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    Area of Science:

    • Neuroscience
    • Dermatology
    • Biomedical Imaging

    Background:

    • Peripheral nerves (PNs) play a vital role in skin innervation and wound healing processes.
    • Existing methods for quantifying skin innervation are often complex, labor-intensive, and prone to user bias due to image noise.

    Approach:

    • Employed a deep neural network (DnCNN) for noise reduction in Immunohistochemistry (IHC) images of skin wound healing.
    • Utilized an automated image analysis tool (Matlab-assisted) to quantify nerve fiber density in wild-type mouse skin samples.
    • Collected and analyzed skin samples at 3, 7, 10, and 15 days post-wounding, stained for the pan-neuronal marker PGP 9.5.

    Key Points:

    • Nerve fiber density was negligible on days 3 and 7, showing a slight increase on day 10 and a significant rise by day 15.
    • A strong positive correlation (R² = 0.933) was observed between nerve fiber density and re-epithelization.
    • The study establishes a quantitative timeline for re-innervation during wound healing.

    Conclusions:

    • The developed automated image analysis method provides a novel, efficient, and accurate tool for quantifying skin innervation.
    • Findings highlight the association between re-innervation and re-epithelization, underscoring the importance of nerve regeneration in wound repair.
    • This approach can facilitate research in skin innervation and wound healing across various tissues.