Abstract
The dimorphism among male, female and freemartin intersex bovines, focusing on the vermal lobules VIII and IX, was analyzed using a novel data analytics approach to quantify morphometric differences in the cytoarchitecture of digitalized sections of the cerebellum. This methodology consists of multivariate and multi-aspect testing for cytoarchitecture-ranking, based on neuronal cell complexity among populations defined by factors, such as sex, age or pathology. In this context, we computed a set of shape descriptors of the neural cell morphology, categorized them into three domains named size, regularity and density, respectively. The output and results of our methodology are multivariate in nature, allowing an in-depth analysis of the cytoarchitectonic organization and morphology of cells. Interestingly, the Purkinje neurons and the underlying granule cells revealed the same morphological pattern: female possessed larger, denser and more irregular neurons than males. In the Freemartin, Purkinje neurons showed an intermediate setting between males and females, while the granule cells were the largest, most regular and dense. This methodology could be a powerful instrument to carry out morphometric analysis providing robust bases for objective tissue screening, especially in the field of neurodegenerative pathologies.
Highlights
Morphometric data analyticsThe concept of morphometrics was introduced in the early 1900s, but it was not until the 1980s that researchers started to use tools for the morphological analysis of cells and the identification of phenotypes
Since the cerebellum offers a good model to develop computational statistical approaches to the study of single cell morphology, we studied the structure of vermal lobules VIII and IX of male, female and intersex freemartins bovines
The major difference observed with the well-known anatomy of the primate cerebellum is the prevalence of the vermis over the lateral lobes, a feature typical of large herbivore mammals like Perissodactyls and terrestrial Cetartiodactyls (Fig. 1)
Summary
Morphometric data analyticsThe concept of morphometrics was introduced in the early 1900s, but it was not until the 1980s that researchers started to use tools for the morphological analysis of cells and the identification of phenotypes. Morphometric descriptors and tools were employed for the quantitative analysis of cell structure, and relevant geometrical features of the cell were, defined by proper objective parameters. The reliability of image-based cellular studies increased as researchers translated qualitative differences into quantitative measurements, establishing an objective approach to cell shape (Pasqualato et al 2012). These studies provided important steps forward to develop suitable statistical procedures for the analyses of morphological data. The analysis of the cellular morphology in the brain cytoarchitecture is still a challenge, and there is an open quest to translate the qualitative differences observed microscopically into quantitative measurements (Lobo et al 2016)
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