The Improvement and Clinical Application of Human Oocyte In Vitro Maturation (IVM).

来自 PUBMED

作者:

Gong XLi HZhao Y

展开

摘要:

Oocyte in vitro maturation (IVM) is a technology with a long history that was established before IVF. Although it has been studied extensively, the efficiency of IVM has been poor for almost 30 years. In terms of the benefits of IVM, the efficiency and adoption of IVM are being improved by some notable improvements that have occurred in recent years. The establishment of biphasic IVM is the most important advancement in recent years. Biphasic IVM includes the pre-IVM culturing phase and IVM phase. The CNP-mediated pre-IVM culturing system is specifically tailored for non/minimally stimulated immature oocytes, and its efficiency has been shown. This is the most significant improvement made in recent decades in this area. In the clinic, IVM can be used for PCOS patients to avoid the occurrence of ovarian hyperstimulation syndrome (OHSS). Additionally, this method can solve the reproductive problems of some patients with special diseases (resistant ovary syndrome) that cannot be solved by IVF. In most fertility preservation procedures, oocytes in small antral follicles are lost. However, IVM has the ability to capture this kind of oocyte and save reproductive potential. IVM can be easily combined with fertility preservation strategies that have been applied in the clinic and improve the efficiency of fertility preservation. IVM is a useful and attractive technology and may be used widely worldwide in the near future.

收起

展开

DOI:

10.1007/s43032-021-00613-3

被引量:

10

年份:

1970

SCI-Hub (全网免费下载) 发表链接

通过 文献互助 平台发起求助,成功后即可免费获取论文全文。

查看求助

求助方法1:

知识发现用户

每天可免费求助50篇

求助

求助方法1:

关注微信公众号

每天可免费求助2篇

求助方法2:

求助需要支付5个财富值

您现在财富值不足

您可以通过 应助全文 获取财富值

求助方法2:

完成求助需要支付5财富值

您目前有 1000 财富值

求助

我们已与文献出版商建立了直接购买合作。

你可以通过身份认证进行实名认证,认证成功后本次下载的费用将由您所在的图书馆支付

您可以直接购买此文献,1~5分钟即可下载全文,部分资源由于网络原因可能需要更长时间,请您耐心等待哦~

身份认证 全文购买

相似文献(127)

参考文献(72)

引证文献(10)

来源期刊

-

影响因子:暂无数据

JCR分区: 暂无

中科院分区:暂无

研究点推荐

关于我们

zlive学术集成海量学术资源,融合人工智能、深度学习、大数据分析等技术,为科研工作者提供全面快捷的学术服务。在这里我们不忘初心,砥砺前行。

友情链接

联系我们

合作与服务

©2024 zlive学术声明使用前必读