MyoVision: software for automated high-content analysis of skeletal muscle immunohistochemistry

Author:

Wen Yuan123ORCID,Murach Kevin A.2,Vechetti Ivan J.12,Fry Christopher S.4,Vickery Chase5,Peterson Charlotte A.26,McCarthy John J.12,Campbell Kenneth S.127ORCID

Affiliation:

1. Department of Physiology, College of Medicine, University of Kentucky, Lexington, Kentucky

2. Center for Muscle Biology, University of Kentucky, Lexington, Kentucky

3. MD/PhD Program, College of Medicine, University of Kentucky, Lexington, Kentucky

4. Department of Nutrition and Metabolism, Division of Rehabilitation Sciences, and Sealy Center on Aging, University of Texas Medical Branch, Galveston, Texas

5. MSTC Program, Paul Laurence Dunbar High School, Lexington, Kentucky

6. Department of Rehabilitation Sciences, College of Health Sciences, University of Kentucky, Lexington, Kentucky

7. Division of Cardiovascular Medicine, College of Medicine, University of Kentucky, Lexington, Kentucky

Abstract

Analysis of skeletal muscle cross sections is an important experimental technique in muscle biology. Many aspects of immunohistochemistry and fluorescence microscopy can now be automated, but most image quantification techniques still require extensive human input, slowing progress and introducing the possibility of user bias. MyoVision is a new software package that was developed to overcome these limitations. The software improves upon previously reported automatic techniques and analyzes images without requiring significant human input and correction. When compared with data derived by manual quantification, MyoVision achieves an accuracy of ≥94% for basic measurements such as fiber number, fiber type distribution, fiber cross-sectional area, and myonuclear number. Scientists can download the software free from www.MyoVision.org and use it to automate the analysis of their own experimental data. This will improve the efficiency and consistency of the analysis of muscle cross sections and help to reduce the burden of routine image quantification in muscle biology. NEW & NOTEWORTHY Scientists currently analyze images of immunofluorescently labeled skeletal muscle using time-consuming techniques that require sustained human supervision. As well as being inefficient, these techniques can increase variability in studies that quantify morphological adaptations of skeletal muscle at the cellular level. MyoVision is new software that overcomes these limitations by performing high-content analysis of muscle cross sections with minimal manual input. It is open source and freely available.

Funder

HHS | NIH | National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)

Publisher

American Physiological Society

Subject

Physiology (medical),Physiology

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3