SEMI-AUTOMATED COMPUTATIONAL METHOD FOR SKELETAL MUSCLE FIBER TYPING WITH LECTINS: CORRELATION WITH MORPHOMETRIC STUDIES

Abstract

Background :Muscle fiber typing has been an extensive field of study for many years. Though, limited researches applied lectin histochemistry in the clinical diagnosis of muscle disorders; attention was directed mainly towards enzyme histochemistry.
Objective:The use of lectins as recognition systems based on specific protein-carbohydrate interactions in correlation with muscle fibers morphometric standards and optical density features to favor the diagnostic procedures of muscle disorders.
Methods:Cross-sections of tibialis anterior muscle from 15 adult rats were stained with Con A, PNA, SBA, WGA, SWGA, LFA, UEA-I, and UEA-II lectins. Photographs of stained sections were analyzed with ImageJ 1.44 software for muscle fiber area, perimeter, optical density, and integrated density.
Results:There were statistically significant differences between the parameters of muscle fiber types under study (P<0.05) concerning Con A, LFA and UEA-II lectins, but not for the remaining lectins, regarding the optical density and integrated density of muscle fibers.
Conclusions: Lectins make accurate recognition of muscle fiber types on fixed paraffin sections when combined with computerized methods to quantify the features seen in muscle biopsies destined for pathological investigations.
Key words: Lectins, Muscle fiber typing, Quantitative, Optical density, Morphometry