Ovary Development: Insights From a Three-Dimensional Imaging Revolution

Soygur, Bikem; Laird, Diana J.

doi:10.3389/fcell.2021.698315

Cited by 16 publications

(10 citation statements)

References 113 publications

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“…In adolescence, the ovaries have a grayish-white, flattened oval appearance, begin to ovulate, and gradually have periodicity (82). Due to the extrusion of oocytes, the ovarian surface becomes uneven, and empty ovulation can be observed (83). In the absence of pregnancy, the ovaries of healthy adult women undergo extensive dynamic tissue remodeling during each menstrual cycle throughout the reproductive period (approximately 40 years) (84).…”

Section: Histomorphological and Functional Changes In The Ovary At Di...mentioning

confidence: 99%

Aging conundrum: A perspective for ovarian aging

Liu

Song

et al. 2022

Front. Endocrinol.

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Progressive loss of physiological integrity and accumulation of degenerative changes leading to functional impairment and increased susceptibility to diseases are the main features of aging. The ovary, the key organ that maintains female reproductive and endocrine function, enters aging earlier and faster than other organs and has attracted extensive attention from society. Ovarian aging is mainly characterized by the progressive decline in the number and quality of oocytes, the regulatory mechanisms of which have yet to be systematically elucidated. This review discusses the hallmarks of aging to further highlight the main characteristics of ovarian aging and attempt to explore its clinical symptoms and underlying mechanisms. Finally, the intervention strategies related to aging are elaborated, especially the potential role of stem cells and cryopreservation of embryos, oocytes, or ovarian tissue in the delay of ovarian aging.

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Section: Histomorphological and Functional Changes In The Ovary At Di...mentioning

confidence: 99%

Aging conundrum: A perspective for ovarian aging

Liu

Song

et al. 2022

Front. Endocrinol.

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“…Bottom: Development from PMF pool to young adulthood in mice and humans and human folliculogenesis and detail in PMF pool in humans at birth. Adapted from [ 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 ].…”

Section: Figurementioning

confidence: 99%

Unlaid Eggs: Ovarian Damage after Low-Dose Radiation

Reiser

Bazzano

Solano

et al. 2022

Cells

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The total body irradiation of lymphomas and co-irradiation in the treatment of adjacent solid tumors can lead to a reduced ovarian function, premature ovarian insufficiency, and menopause. A small number of studies has assessed the radiation-induced damage of primordial follicles in animal models and humans. Studies are emerging that evaluate radiation-induced damage to the surrounding ovarian tissue including stromal and immune cells. We reviewed basic laboratory work to assess the current state of knowledge and to establish an experimental setting for further studies in animals and humans. The experimental approaches were mostly performed using mouse models. Most studies relied on single doses as high as 1 Gy, which is considered to cause severe damage to the ovary. Changes in the ovarian reserve were related to the primordial follicle count, providing reproducible evidence that radiation with 1 Gy leads to a significant depletion. Radiation with 0.1 Gy mostly did not show an effect on the primordial follicles. Fewer data exist on the effects of radiation on the ovarian microenvironment including theca-interstitial, immune, endothelial, and smooth muscle cells. We concluded that a mouse model would provide the most reliable model to study the effects of low-dose radiation. Furthermore, both immunohistochemistry and fluorescence-activated cell sorting (FACS) analyses were valuable to analyze not only the germ cells but also the ovarian microenvironment.

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“…Some studies have also focused on the development of complex stereological approaches to limit the biases induced by 2D approaches (Charleston et al, 2007). Recently, the emergence of optical tissue clearing methods and powerful microscopes have opened new perspectives with the possibility of imaging whole ovaries in three dimensions (3D), notably for mice and fishes (Fiorentino et al, 2021; Lesage et al, 2020; Soygur and Laird, 2021). It is thus now possible to generate 3D image data, generally of very large size, that ideally allows direct and comprehensive access to all structures and to achieve a precise 3D image reconstruction of the whole ovary.…”

Section: Introductionmentioning

confidence: 99%

An end-to-end pipeline based on open source deep learning tools for reliable analysis of complex 3D images of Medaka ovaries

Lesage

Thermes

Bugeon

et al. 2022

Preprint

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Computational analysis of bio-images by deep learning (DL) algorithms has made exceptional progress in recent years and has become much more accessible to non-specialists with the development of ready-to-use tools. The study of oogenesis mechanisms and female reproductive success in fish has also recently benefited from the development of efficient three-dimensional (3D) imaging protocols on entire ovaries. Such large datasets have a great potential for the generation of new quantitative data on oogenesis but are, however, complex to analyze due to imperfect fluorescent signals and the lack of efficient image analysis workflows. Here, we applied two open-source DL tools, Noise2Void and Cellpose, to analyze the oocyte content of medaka ovaries at larvae and adult stages. These tools were integrated into end-to-end analysis pipelines that include image pre-processing, cell segmentation, and image post-processing to filter and combine labels. Our pipelines thus provide effective solutions to accurately segment complex 3D images of entire ovaries with either irregular fluorescent staining or low autofluorescence signal. In the future, these pipelines will be applicable to extensive cellular phenotyping in fish for developmental or toxicology studies.

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Ovary Development: Insights From a Three-Dimensional Imaging Revolution

Cited by 16 publications

References 113 publications

Aging conundrum: A perspective for ovarian aging

Aging conundrum: A perspective for ovarian aging

Unlaid Eggs: Ovarian Damage after Low-Dose Radiation

An end-to-end pipeline based on open source deep learning tools for reliable analysis of complex 3D images of Medaka ovaries

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