R-954, a bradykinin B1 receptor antagonist, as a potential therapy in a preclinical endometriosis model.

来自 PUBMED

作者:

França PRCPaiva JPBCarvalho RRFigueiredo CPSirois PFernandes PD

展开

摘要:

Endometriosis is a gynecological condition characterized by the growth of endometrium-like tissues outside of the uterine cavity. Currently available drugs are efficacious in treating endometriosis-related pain, however it's not a targeted treatment. The aim of this work is to evaluate the effects of R-954, a bradykinin B1 receptor antagonist, in a murine model of endometriosis. The model was induced in animals through autologous transplantation of part of the uterine horn. After 51 days, it was observed that implants developed into endometriotic lesions. The administration of R-954 or progesterone, for 15 consecutive days, prevented the progression of cyst development, reduced the size and weight of the cysts. Both treatments also reduced cellular infiltrate and production of inflammatory mediators (interleukin-1β, interleukin-6, tumor necrosis factor). However, only R-954 decreased angiogenic factors (VEGF and VEGF receptor). In addition, treatment with the antagonist did not interfere in the females' estrous cycle, as well as prevented gestational losses (reduction in the number of intermediate resorptions in pregnant females with endometriosis). Data suggested that R-954 has anti-inflammatory and anti-angiogenic effects; does not influence the estrous cycle; and prevents the number of gestational losses suggesting it as a good candidate for endometriosis treatment.

收起

展开

DOI:

10.1016/j.peptides.2024.171294

被引量:

0

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(100)

参考文献(0)

引证文献(0)

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