Title |
Evaluation of ovarian structures using computerized microtomography
|
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Published in |
Anais da Academia Brasileira de Ciências, June 2017
|
DOI | 10.1590/0001-3765201720150864 |
Pubmed ID | |
Authors |
Fernanda Paulini, Sacha B Chaves, José Luiz J P Rôlo, Ricardo B DE Azevedo, Carolina M Lucci |
Abstract |
Visualization and clear understanding of the ovarian structures are important in determining the stage of oestrus, helping to diagnose several pathologies and supporting advances in reproductive technologies. In this research, computerized microtomography (microCT) was used to explore and characterize the ovarian structure of seven mammalian species. Ovaries of rats, female dog, queens, cows, mares, sows and a female donkey were used. After microCT scanning, the same samples were prepared for histologic evaluation, used here as a validation criterion. It was possible to distinguish regions of the cortex and medulla, visualize the morphology and distribution of blood vessels, clearly observe corpus luteum and antral follicles, and visualize oocytes inside some antral follicles. This is the first report using microCT to explore and compare ovarian structures in several domestic mammals. MicroCT revealed great potential for the evaluation of ovarian structures. This research open prospects for the use of computerized tomography (CT) as a non-invasive approach to studying ovarian structures in live animals, which may be especially attractive for scientific study of development of ovarian structures and/or ovarian pathologies in small animals' models. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 29 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Other | 4 | 14% |
Student > Bachelor | 4 | 14% |
Researcher | 4 | 14% |
Student > Ph. D. Student | 3 | 10% |
Professor | 2 | 7% |
Other | 4 | 14% |
Unknown | 8 | 28% |
Readers by discipline | Count | As % |
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Biochemistry, Genetics and Molecular Biology | 6 | 21% |
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Engineering | 3 | 10% |
Veterinary Science and Veterinary Medicine | 2 | 7% |
Agricultural and Biological Sciences | 2 | 7% |
Other | 4 | 14% |
Unknown | 8 | 28% |