A semi‐automated observation approach to quantify mouse skeletal muscle differentiation using immunohistochemistry

Histological analysis is vital for understanding skeletal muscle diseases. However, quantifying data requires much effort, so automation is expected to reduce workload. The present study proposes a semi-automated method to quantify expressed paired box protein (Pax-7) /bromodeoxyuridine (BrdU)-positive cells. Soleus muscle was harvested from mice 2 weeks after oral administration of the epicatechin tetramer cinnamantanin A2 (A2), known to induce skeletal muscle hypertrophy. Before the necropsy, mice were treated with BrdU to facilitate cell tracking. For histological examination, frozen sections were stained with hematoxylin and eosin (HE) to measure cell size by cross-sectional area (CSA) and were immunostained with anti-BrdU and anti-Pax-7 antibodies. Treatment with A2 caused a shift in the CSA distribution curve towards larger values, thus revealing an increase in muscle size. The analysis of BrdU/Pax-7 positive cells, performed both manually and semi-automatically, revealed a slight increase with A2 treatment, while Pax-7 positive cells remained unchanged. Correlation between manual and semi-automated analysis showed a coefficient of determination of 0.7132, indicating a significant reduction in analysis time by approximately 20 times. This study highlights the effectiveness of semi-automated histological analysis in skeletal muscle research and provides a practical solution to increase the efficiency of muscle regeneration evaluation.

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Publication Details

Journal
Physiological Reports
Published
2025-04-01
DOI
https://doi.org/10.14814/phy2.70330
Primary Topic
Muscle Physiology and Disorders
Type
article
Field-Weighted Citation Impact
0.00

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article

A semi‐automated observation approach to quantify mouse skeletal muscle differentiation using immunohistochemistry

Kazuo Iwasa, Yasuyuki Fujii, Vittorio Calabrese, Yamato Yoshida et al.
Physiological Reports
Muscle Physiology and Disorders
article

A semi‐automated observation approach to quantify mouse skeletal muscle differentiation using immunohistochemistry

Kazuo Iwasa, Yasuyuki Fujii, Vittorio Calabrese, Yamato Yoshida, Ali S. Abdelhameed, Kenta Shimizu, Naomi Osakabe, Tilman Fritsch, Ursula M. Jacob
article en

Abstract

Histological analysis is vital for understanding skeletal muscle diseases. However, quantifying data requires much effort, so automation is expected to reduce workload. The present study proposes a semi-automated method to quantify expressed paired box protein (Pax-7) /bromodeoxyuridine (BrdU)-positive cells. Soleus muscle was harvested from mice 2 weeks after oral administration of the epicatechin tetramer cinnamantanin A2 (A2), known to induce skeletal muscle hypertrophy. Before the necropsy, mice were treated with BrdU to facilitate cell tracking. For histological examination, frozen sections were stained with hematoxylin and eosin (HE) to measure cell size by cross-sectional area (CSA) and were immunostained with anti-BrdU and anti-Pax-7 antibodies. Treatment with A2 caused a shift in the CSA distribution curve towards larger values, thus revealing an increase in muscle size. The analysis of BrdU/Pax-7 positive cells, performed both manually and semi-automatically, revealed a slight increase with A2 treatment, while Pax-7 positive cells remained unchanged. Correlation between manual and semi-automated analysis showed a coefficient of determination of 0.7132, indicating a significant reduction in analysis time by approximately 20 times. This study highlights the effectiveness of semi-automated histological analysis in skeletal muscle research and provides a practical solution to increase the efficiency of muscle regeneration evaluation.

Physiological ReportsVol. 13(7)
Shibaura Institute of Technology (JP), King Saud University (SA), University of Catania (IT)
Ministry of Education, Culture, Sports, Science and Technology, King Saud University, Japan Society for the Promotion of Science
Openalex Percentile: Top 93%
Muscle Physiology and Disorders
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