Abstract

One of the unsolved issues in neuromorphology is the classification of myelin nerve fibers (MNF). Objective: to use cluster analysis to classify the sciatic nerve MNF.
 Material and methods. The work was performed using 5 one-year-old male Wistar rats. Semi-thin sections were stained with methylene blue. MNF morphometry was performed using ImageJ, and statistical processing – using the software environment R.
 Results of the study. Ward’s and k-means methods were used to cluster the MNF. Three clusters of MNFs are defined and their parameters are determined. The presented algorithm for adapting the literature data to the format of the obtained results includes determining the total average for the combined set of each indicator and the total variance, which is the sum of intragroup and intergroup variances.
 Conclusions: 1) for the classification of MNF it is advisable to use cluster analysis; 2) clustering should be performed according to the transsection areas of the axial cylinder and myelin sheath; 3) the number of clusters is determined by the agglomerative method of Ward, and their metrics – by the iterative method of k-means; 4) three clusters of MNF of the rat sciatic nerve differ in the transsection areas of the fibers, the axial cylinder and the myelin sheath and the percentage of nerve fibers; 5) when comparing identical indicators according to the obtained and literature data, the results were equivalent in the areas of the axial cylinder and myelin sheath and their shape coefficients, despite the fact that the classification of myelin fibers and their morphometry was performed using different methods.

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