Literature DB >> 28982947

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

Yuan Wen1,2,3, Kevin A Murach2, Ivan J Vechetti1,2, Christopher S Fry4, Chase Vickery5, Charlotte A Peterson2,6, John J McCarthy1,2, Kenneth S Campbell1,2,7.   

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.

Entities:  

Keywords:  automation software; cell morphology; high-content microscopy; image analysis; skeletal muscle

Mesh:

Year:  2017        PMID: 28982947      PMCID: PMC6048460          DOI: 10.1152/japplphysiol.00762.2017

Source DB:  PubMed          Journal:  J Appl Physiol (1985)        ISSN: 0161-7567


  26 in total

1.  Ribosome biogenesis may augment resistance training-induced myofiber hypertrophy and is required for myotube growth in vitro.

Authors:  Michael J Stec; Neil A Kelly; Gina M Many; Samuel T Windham; S Craig Tuggle; Marcas M Bamman
Journal:  Am J Physiol Endocrinol Metab       Date:  2016-02-09       Impact factor: 4.310

2.  Fully automated segmentation and morphometrical analysis of muscle fiber images.

Authors:  Yoo-Jin Kim; Thomas Brox; Wolfgang Feiden; Joachim Weickert
Journal:  Cytometry A       Date:  2007-01       Impact factor: 4.355

3.  Active contour external force using vector field convolution for image segmentation.

Authors:  Bing Li; Scott T Acton
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4.  No change in myonuclear number during muscle unloading and reloading.

Authors:  J C Bruusgaard; I M Egner; T K Larsen; S Dupre-Aucouturier; D Desplanches; K Gundersen
Journal:  J Appl Physiol (1985)       Date:  2012-05-10

Review 5.  Fiber types in mammalian skeletal muscles.

Authors:  Stefano Schiaffino; Carlo Reggiani
Journal:  Physiol Rev       Date:  2011-10       Impact factor: 37.312

6.  Automated high-content morphological analysis of muscle fiber histology.

Authors:  Mauro Miazaki; Matheus P Viana; Zhong Yang; Cesar H Comin; Yaming Wang; Luciano da F Costa; Xiaoyin Xu
Journal:  Comput Biol Med       Date:  2015-04-23       Impact factor: 4.589

7.  Automated image analysis of skeletal muscle fiber cross-sectional area.

Authors:  Jyothi Mula; Jonah D Lee; Fujun Liu; Lin Yang; Charlotte A Peterson
Journal:  J Appl Physiol (1985)       Date:  2012-11-08

Review 8.  Automated methods for the analysis of skeletal muscle fiber size and metabolic type.

Authors:  Tatiana Y Kostrominova; David S Reiner; Richard H Haas; Randall Ingermanson; Patrick M McDonough
Journal:  Int Rev Cell Mol Biol       Date:  2013       Impact factor: 6.813

9.  Regrowth after skeletal muscle atrophy is impaired in aged rats, despite similar responses in signaling pathways.

Authors:  Jena R White; Amy L Confides; Stephanie Moore-Reed; Johanna M Hoch; Esther E Dupont-Versteegden
Journal:  Exp Gerontol       Date:  2015-02-12       Impact factor: 4.032

10.  Reduced voluntary running performance is associated with impaired coordination as a result of muscle satellite cell depletion in adult mice.

Authors:  Janna R Jackson; Tyler J Kirby; Christopher S Fry; Robin L Cooper; John J McCarthy; Charlotte A Peterson; Esther E Dupont-Versteegden
Journal:  Skelet Muscle       Date:  2015-11-16       Impact factor: 4.912

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  64 in total

1.  An investigation of p53 in skeletal muscle aging.

Authors:  Scott M Ebert; Jason M Dierdorff; David K Meyerholz; Steven A Bullard; Asma Al-Zougbi; Austin D DeLau; Kristin C Tomcheck; Zachary P Skopec; George R Marcotte; Sue C Bodine; Christopher M Adams
Journal:  J Appl Physiol (1985)       Date:  2019-08-29

2.  Serum extracellular vesicle miR-203a-3p content is associated with skeletal muscle mass and protein turnover during disuse atrophy and regrowth.

Authors:  Douglas W Van Pelt; Ivan J Vechetti; Marcus M Lawrence; Kathryn L Van Pelt; Parth Patel; Benjamin F Miller; Timothy A Butterfield; Esther E Dupont-Versteegden
Journal:  Am J Physiol Cell Physiol       Date:  2020-07-08       Impact factor: 4.249

3.  The role of neutrophil extracellular traps and TLR signaling in skeletal muscle ischemia reperfusion injury.

Authors:  Nicole J Edwards; Charles Hwang; Simone Marini; Chase A Pagani; Philip J Spreadborough; Cassie J Rowe; Pauline Yu; Annie Mei; Noelle Visser; Shuli Li; Geoffrey E Hespe; Amanda K Huber; Amy L Strong; Miriam A Shelef; Jason S Knight; Thomas A Davis; Benjamin Levi
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4.  The wasting-associated metabolite succinate disrupts myogenesis and impairs skeletal muscle regeneration.

Authors:  Paige C Arneson; Kelly A Hogan; Alexandra M Shin; Adrienne Samani; Aminah Jatoi; Jason D Doles
Journal:  JCSM Rapid Commun       Date:  2020-06-02

5.  Massage as a mechanotherapy promotes skeletal muscle protein and ribosomal turnover but does not mitigate muscle atrophy during disuse in adult rats.

Authors:  Marcus M Lawrence; Douglas W Van Pelt; Amy L Confides; Emily R Hunt; Zachary R Hettinger; Jaime L Laurin; Justin J Reid; Frederick F Peelor; Timothy A Butterfield; Esther E Dupont-Versteegden; Benjamin F Miller
Journal:  Acta Physiol (Oxf)       Date:  2020-03-17       Impact factor: 6.311

6.  Phosphorylation of eukaryotic initiation factor 4E is dispensable for skeletal muscle hypertrophy.

Authors:  Vandre C Figueiredo; Davis A Englund; Ivan J Vechetti; Alexander Alimov; Charlotte A Peterson; John J McCarthy
Journal:  Am J Physiol Cell Physiol       Date:  2019-10-09       Impact factor: 4.249

Review 7.  Muscle Fiber Splitting Is a Physiological Response to Extreme Loading in Animals.

Authors:  Kevin A Murach; Cory M Dungan; Charlotte A Peterson; John J McCarthy
Journal:  Exerc Sport Sci Rev       Date:  2019-04       Impact factor: 6.230

8.  In vivo analysis of γH2AX+ cells in skeletal muscle from aged and obese humans.

Authors:  Cory M Dungan; Bailey D Peck; R Grace Walton; Zhengyan Huang; Marcas M Bamman; Philip A Kern; Charlotte A Peterson
Journal:  FASEB J       Date:  2020-04-04       Impact factor: 5.191

9.  Elevated myonuclear density during skeletal muscle hypertrophy in response to training is reversed during detraining.

Authors:  Cory M Dungan; Kevin A Murach; Kaitlyn K Frick; Savannah R Jones; Samuel E Crow; Davis A Englund; Ivan J Vechetti; Vandre C Figueiredo; Bryana M Levitan; Jonathan Satin; John J McCarthy; Charlotte A Peterson
Journal:  Am J Physiol Cell Physiol       Date:  2019-03-06       Impact factor: 4.249

10.  Resident muscle stem cells are not required for testosterone-induced skeletal muscle hypertrophy.

Authors:  Davis A Englund; Bailey D Peck; Kevin A Murach; Ally C Neal; Hannah A Caldwell; John J McCarthy; Charlotte A Peterson; Esther E Dupont-Versteegden
Journal:  Am J Physiol Cell Physiol       Date:  2019-07-17       Impact factor: 4.249

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