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长双歧杆菌CCFM1077通过调节肠道微生物组成和粪便代谢物来减轻高脂血症——一项随机、双盲、安慰剂对照的临床试验 Article
储传奇, 姜金池, 于雷雷, 李易文, 张松礼, 周巍, 王群, 赵建新, 翟齐啸, 田丰伟, 陈卫
《工程（英文）》 2023年 第28卷 第9期 页码 193-205 doi: 10.1016/j.eng.2023.04.010
一种通过检测特定粪便微生物群来评估人体肠道微生物稳态的方法 Article
Zhongwen Wu, Xiaxia Pan, Yin Yuan, Pengcheng Lou, Lorina Gordejeva, Shuo Ni, Xiaofei Zhu, Bowen Liu, Lingyun Wu, Lanjuan Li, Bo Li
《工程（英文）》 2023年 第29卷 第10期 页码 110-119 doi: 10.1016/j.eng.2023.03.007
Research on microecology has been carried out with broad perspectives in recent decades, which has enabled a better understanding of the gut microbiota and its roles in human health and disease. It is of great significance to routinely acquire the status of the human gut microbiota; however, there is no method to evaluate the gut microbiome through small amounts of fecal microbes. In this study, we found ten predominant groups of gut bacteria that characterized the whole microbiome in the human gut from a largesample Chinese cohort, constructed a real-time quantitative polymerase chain reaction (qPCR) method and developed a set of analytical approaches to detect these ten groups of predominant gut bacterial species with great maneuverability, efficiency, and quantitative features. Reference ranges for the ten predominant gut bacterial groups were established, and we found that the concentration and pairwise ratios of the ten predominant gut bacterial groups varied with age, indicating gut microbial dysbiosis. By comparing the detection results of liver cirrhosis (LC) patients with those of healthy control subjects, differences were then analyzed, and a classification model for the two groups was built by machine learning. Among the six established classification models, the model established by using the random forest algorithm achieved the highest area under the curve (AUC) value and sensitivity for predicting LC. This research enables easy, rapid, stable, and reliable testing and evaluation of the balance of the gut microbiota in the human body, which may contribute to clinical work.
关键词： Gut microbiota Machine learning Microbial dysbiosis Quantitative polymerase chain reaction Chinese cohort
胡莹洁, 孔祥斌, 张玉臻
《中国工程科学》 2018年 第20卷 第5期 页码 84-89 doi: 10.15302/J-SSCAE-2018.05.013
标题 作者 时间 类型 操作
长双歧杆菌CCFM1077通过调节肠道微生物组成和粪便代谢物来减轻高脂血症——一项随机、双盲、安慰剂对照的临床试验
储传奇, 姜金池, 于雷雷, 李易文, 张松礼, 周巍, 王群, 赵建新, 翟齐啸, 田丰伟, 陈卫
期刊论文
一种通过检测特定粪便微生物群来评估人体肠道微生物稳态的方法
Zhongwen Wu, Xiaxia Pan, Yin Yuan, Pengcheng Lou, Lorina Gordejeva, Shuo Ni, Xiaofei Zhu, Bowen Liu, Lingyun Wu, Lanjuan Li, Bo Li
期刊论文
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