RESUMO
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
RESUMO
SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.
Assuntos
Algoritmos , Biologia Computacional/métodos , Linguagens de Programação , Software , Biologia Computacional/história , Simulação por Computador , História do Século XX , História do Século XXI , Modelos Lineares , Modelos Biológicos , Dinâmica não Linear , Processamento de Sinais Assistido por ComputadorRESUMO
The orientation of vascular smooth muscle cells of porcine aortae was assessed to test the widely accepted assumption that these smooth muscle cells are arranged in two helices. We used tangential histological sections of 82 samples of five anatomical segments of thoracic and abdominal porcine aortae and three age groups in animals ranging in age from 5 to 210 days. The distribution of the orientation of smooth muscle cell nuclei in five proximodistal segments of the porcine aortae was determined using an algorithm that fitted a mixture of one to five von Mises probability distributions of the data retrieved from histological micrographs. Automated tracking of the nuclei was confirmed by and consistent with manual histological analysis. The orientation of the vascular smooth muscle cells was successfully fitted using two von Mises distributions in most of the samples with different ages, wall thicknesses, and anatomical positions, which corresponds to two populations of vascular smooth muscle cells. A minor fraction of samples also required a tertiary von Mises distribution to describe the orientation of the smooth muscle cell nuclei. The distribution of vascular smooth muscle cells in five aortic segments ranging from the thoracic ascending aorta to the abdominal intrarenal aorta exhibited similar main directions but different shapes. These results are consistent with the widely used model of two muscular helices intermingling in the arterial wall. Furthermore, we calculated the central angles of symmetry and the mean value of angles between the two assumed smooth muscle directions. We also successfully approximated the orientation of the smooth muscle cells using a mixture of von Mises distributions and our open-source software named dist_mixtures. This method is openly available to researchers who are interested in mathematically assessing the orientation of cell nuclei in various tissues.
