Lipid imaging for visualizing cilastatin amelioration of cisplatin-induced nephrotoxicity.

来自 PUBMED

摘要:

Nephrotoxicity is a major limitation to cisplatin antitumor therapies. Cilastatin, an inhibitor of renal dehydropeptidase-I, was recently proposed as a promising nephroprotector against cisplatin toxicity, preventing apoptotic cell death. In this work, cilastatin nephroprotection was further investigated in a rat model, with a focus on its effect on 76 renal lipids altered by cisplatin, including 13 new cisplatin-altered mitochondrial cardiolipin species. Lipid imaging was performed with MALDI mass spectrometry imaging (MALDI-MSI) in kidney sections from treated rats. Cilastatin was proved to significantly diminish the lipid distribution alterations caused by cisplatin, lipid levels being almost completely recovered to those of control samples. The extent of recovery of cisplatin-altered lipids by cilastatin turned out to be relevant for discriminating direct or secondary lipid alterations driven by cisplatin. Lipid peroxidation induced by cisplatin was also shown to be reduced when cilastatin was administered. Importantly, significant groups separation was achieved during multivariate analysis of cortex and outer-medullary lipids, indicating that damaged kidney can be discerned from the nephroprotected and healthy groups and classified according to lipid distribution. Therefore, we propose MALDI-MSI as a powerful potential tool offering multimolecule detection possibilities to visualize and evaluate nephrotoxicity and nephroprotection based on lipid analysis.

收起

展开

DOI:

10.1194/jlr.M080465

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(100)

参考文献(68)

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