Multi-aspect testing and ranking inference to quantify dimorphism in the cytoarchitecture of cerebellum of male, female and intersex individuals: a model applied to bovine brains.
Journal article
Corain, L., Grisan, E., Graïc, J., Carvajal-Schiaffino, R., Cozzi, B. and Peruffo, A. (2020). Multi-aspect testing and ranking inference to quantify dimorphism in the cytoarchitecture of cerebellum of male, female and intersex individuals: a model applied to bovine brains. Brain structure & function. https://doi.org/10.1007/s00429-020-02147-x
| Authors | Corain, L., Grisan, E., Graïc, J., Carvajal-Schiaffino, R., Cozzi, B. and Peruffo, A. |
|---|---|
| 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. |
| Keywords | Brain dimorphism; Cerebellum; Cytoarchitecture morphometrics; Image analysis; Multi-aspect analysis in neuroanatomy |
| Year | 2020 |
| Journal | Brain structure & function |
| Publisher | Springer |
| ISSN | 1863-2661 |
| Digital Object Identifier (DOI) | https://doi.org/10.1007/s00429-020-02147-x |
| Funder | Università degli Studi di Padova |
| Publication dates | |
| Online | 28 Sep 2020 |
| Publication process dates | |
| Deposited | 10 Sep 2020 |
| Accepted | 08 Sep 2020 |
| Publisher's version | License File Access Level Open |
| Accepted author manuscript | License File Access Level Controlled |
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