Suppr超能文献

与日本传统药物大建中汤引发的肠道收缩反应相关的微生物组生物标志物。

Microbiome biomarkers associated with the gut contraction response elicited by the Japanese traditional medicine daikenchuto.

作者信息

Wada Yu, Nishiyama Mitsue, Uehara Hideaki, Sato Kazuko, Hamamoto Yoshihiko, Ogihara Hiroyuki, Nishi Akinori, Asakawa Takeshi, Yamamoto Masahiro

机构信息

Tsumura Advanced Technology Research Laboratories, Tsumura & Co., Ibaraki 300-1192, Japan.

Tsumura Advanced Technology Research Laboratories, Tsumura & Co., Ibaraki 300-1192, Japan.

出版信息

Gene. 2022 Jun 5;826:146262. doi: 10.1016/j.gene.2022.146262. Epub 2022 Mar 4.

Abstract

Objective biomarkers are crucial in the development of personalized medicines, such as Japanese traditional medicine (Kampo). To date, some objective markers to predict the response of Kampo medicines have been reported, but the information is somewhat limited. The aim of this study was to search for objective markers and combinations thereof to estimate the effect of the Japanese traditional medicine daikenchuto (DKT) on colon contraction intensity in guinea pigs. Specifically, the microbiome biomarkers were employed as candidate, using the Fisher ratio and the nearest neighbor classifier for statistical pattern recognition. The combination of the ratio between gut microbes of family Ruminococcaceae/Rikenellaceae, Ruminococcaceae/Paraprevotellaceae, and genus Ruminococcus/unknown genus in family Rikenellaceae of guinea pig gut microbes was found to influence the activity of DKT with 0.8 accuracy for test samples. These findings suggest that statistical pattern recognition can contribute to identifying target markers of multi-target drugs such as Kampo.

摘要

客观生物标志物在个性化药物(如日本传统医学汉方)的开发中至关重要。迄今为止,已经报道了一些预测汉方药物反应的客观标志物,但相关信息较为有限。本研究的目的是寻找客观标志物及其组合,以评估日本传统药物大建中汤(DKT)对豚鼠结肠收缩强度的影响。具体而言,采用微生物组生物标志物作为候选指标,使用费舍尔比率和最近邻分类器进行统计模式识别。发现豚鼠肠道微生物中瘤胃球菌科/理研菌科、瘤胃球菌科/副普雷沃菌科的肠道微生物比例以及理研菌科中瘤胃球菌属/未知属的组合对DKT的活性有影响,测试样本的准确率为0.8。这些发现表明,统计模式识别有助于识别汉方等多靶点药物的靶标标志物。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验