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Color subtractive-computer-assisted image analysis for quantification of cutaneous nerves in a diabetic mouse model
R A Underwood1, N S Gibran, L A Muffley
1Department of Medicine (Dermatology), University of Washington, Seattle, Washington, USA.
Summary
Quantifying nerve staining in tissues is challenging. A new computer-assisted image analysis system (CS-CAIA) objectively measures cutaneous innervation, revealing significantly lower nerve profiles in diabetic mice compared to controls.
Area of Science:
- Neuroscience
- Histology
- Biomedical Engineering
Background:
- Immunohistochemistry (IHC) is crucial for tissue analysis but quantifying results is difficult.
- Traditional methods like manual counting are biased and labor-intensive.
- Stereology offers accuracy but is complex for large sample sizes.
Purpose of the Study:
- To develop a rapid, objective, and reproducible method for quantifying cutaneous innervation.
- To assess differences in epidermal nerve density between diabetic and control mice.
Main Methods:
- Developed a color subtractive-computer-assisted image analysis (CS-CAIA) system.
- Used IHC for the neural marker PGP 9.5 on diabetic (db/db) and wild-type (db/-) mouse skin.
- Employed colorimetric isolation, background removal, thresholding, and binarization for automated analysis.
Main Results:
- CS-CAIA successfully quantified nerve profile counts, area fraction, and area density.
- Diabetic (db/db) mice showed significantly lower epidermal nerve profile counts.
- Area fraction and area density of epidermal nerves were also significantly reduced in db/db mice.
Conclusions:
- CS-CAIA provides an efficient and objective method for quantifying IHC-stained neural structures.
- Diabetic mice exhibit reduced cutaneous innervation compared to non-diabetic controls.
- This method facilitates large-scale studies on neuropathy and tissue innervation.