Ex ovo omnia - 为什么我们不能通过成像更多地了解卵子质量?

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Caitlin F Boylan, Keshia M Sambo, Genevieve Neal-Perry, Lynae M Brayboy
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引用次数: 0

摘要

确定卵子质量是辅助生殖技术(ART)的首要挑战。尽管在过去的四十年中,辅助生殖技术的多个领域都取得了长足的进步,但卵母细胞质量评估工具的发展还远远没有超越标准的形态学观察。卵母细胞不仅能为胚胎提供一半的核遗传物质和全部的线粒体 DNA,还能在胚胎生长过程中提供完整的发育支持。卵母细胞线粒体的数量远远超过任何体细胞,但目前很少有人对卵母细胞线粒体生物能进行评估。目前,体外受精(IVF)中心的标准卵母细胞评估包括通过体视显微镜或倒置显微镜观察卵母细胞及其周围的细胞复合体(积层细胞),这在很大程度上是原始的。其他卵母细胞评估包括极体分级和偏振光减数分裂纺锤体成像。然而,上述卵母细胞质量评估方法和试管婴儿结果的相关证据相互矛盾,且不可再现。高分辨率显微镜技术也已应用于动物和人体模型,并取得了可喜的成果。随着卵母细胞形态选择人工智能模型的发现,当前的卵母细胞成像技术仍在不断发展,尽管发展速度缓慢。在这篇综述中,将对过去、现在和未来的卵母细胞成像技术进行研究,目的是让人们注意到限制我们实时评估卵母细胞能力的差距。本文将讨论改进的卵母细胞成像技术对试管婴儿患者的影响,以及在试管婴儿实验室开发护理点卵母细胞评估测试的必要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ex ovo omnia-why don't we know more about egg quality via imaging?

Determining egg quality is the foremost challenge in assisted reproductive technology (ART). Although extensive advances have been made in multiple areas of ART over the last 40 years, oocyte quality assessment tools have not much evolved beyond standard morphological observation. The oocyte not only delivers half of the nuclear genetic material and all of the mitochondrial DNA to an embryo but also provides complete developmental support during embryonic growth. Oocyte mitochondrial numbers far exceed those of any somatic cell, yet little work has been done to evaluate the mitochondrial bioenergetics of an oocyte. Current standard oocyte assessment in in vitro fertilization (IVF) centers include the observation of oocytes and their surrounding cell complex (cumulus cells) via stereomicroscope or inverted microscope, which is largely primitive. Additional oocyte assessments include polar body grading and polarized light meiotic spindle imaging. However, the evidence regarding the aforementioned methods of oocyte quality assessment and IVF outcomes is contradictory and non-reproducible. High-resolution microscopy techniques have also been implemented in animal and human models with promising outcomes. The current era of oocyte imaging continues to evolve with discoveries in artificial intelligence models of oocyte morphology selection albeit at a slow rate. In this review, the past, current, and future oocyte imaging techniques will be examined with the goal of drawing attention to the gap which limits our ability to assess oocytes in real time. The implications of improved oocyte imaging techniques on patients undergoing IVF will be discussed as well as the need to develop point of care oocyte assessment testing in IVF labs.

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来源期刊
CiteScore
7.20
自引率
4.30%
发文量
567
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