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Software for muscle fibre type classification and analysis
P. Karen, M. Števanec, V. Smerdu, E. Cvetko, L. Kubínová, I. Erzen
Language English Country Italy
Document type Research Support, Non-U.S. Gov't
NLK
Free Medical Journals
from 2000
PubMed Central
from 2009
Europe PubMed Central
from 2009
ProQuest Central
from 2000-01-01 to 2020-06-30
Open Access Digital Library
from 2003-01-01
Open Access Digital Library
from 2009-01-01
Health & Medicine (ProQuest)
from 2000-01-01 to 2020-06-30
ROAD: Directory of Open Access Scholarly Resources
from 2000
PubMed
19683982
DOI
10.4081/ejh.2009.87
Knihovny.cz E-resources
- MeSH
- In Situ Hybridization MeSH
- Immunohistochemistry MeSH
- Muscle Fibers, Skeletal cytology classification MeSH
- Rats MeSH
- Humans MeSH
- Masseter Muscle cytology MeSH
- Myosins genetics metabolism MeSH
- Image Processing, Computer-Assisted methods MeSH
- Protein Isoforms genetics metabolism MeSH
- Reproducibility of Results MeSH
- Software MeSH
- Myosin Heavy Chains genetics metabolism MeSH
- User-Computer Interface MeSH
- Animals MeSH
- Check Tag
- Rats MeSH
- Humans MeSH
- Animals MeSH
- Publication type
- Research Support, Non-U.S. Gov't MeSH
Fibre type determination requires a large series of differently stained muscle sections. The manual identification of individual fibres through the series is tedious and time consuming. This paper presents a software that enables (i) adjusting the position of individual fibres through a series of differently stained sections (image registration) and identification of individual fibres through the series as well as (ii) muscle fibre classification and (iii) quantitative analysis. The data output of the system is the following: numerical and areal proportions of fibre types, fibre type size and optical density (grey level) of the final reaction product in every fibre. The muscle fibre type can be determined stepwise, based on one set of stained sections while further, newly stained sections can be added to the already defined muscle fibre profile. Several advantages of the presented software application in skeletal muscle research are presented. The system is semiquantitative, flexible, and user friendly.
References provided by Crossref.org
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