Effects of short-chain fatty acids on blood glucose and lipid levels in mouse models of diabetes mellitus: A systematic review and network meta-analysis

荟萃分析 医学 置信区间 内科学 糖尿病 科克伦图书馆 甘油三酯 血脂 丁酸盐 胃肠病学 内分泌学 胆固醇 生物化学 化学 发酵
作者
Jie Zheng,Yu An,Yage Du,Ying Song,Qian Zhao,Yanhui Lu
出处
期刊:Pharmacological Research [Elsevier BV]
卷期号:199: 107041-107041 被引量:14
标识
DOI:10.1016/j.phrs.2023.107041
摘要

Short-chain fatty acids (SCFAs), the main metabolites of gut microbiota, have been associated with lower blood glucose and lipid levels in diabetic mice. However, a comprehensive summary and comparison of the effects of different SCFA interventions on blood glucose and lipid levels in diabetic mice is currently unavailable. This study aims to compare and rank the effects of different types of SCFAs on blood glucose and lipid levels by collecting relevant animal research. A systematic search through PubMed, Embase, Cochrane Library, and Web of Science database was conducted to identify relevant studies from inception to March 17, 2023. Both pairwise meta-analysis and Bayesian network meta-analysis were used for statistical analyses. In total, 18 relevant studies involving 5 interventions were included after screening 3793 citations and 53 full-text articles. Notably, butyrate therapy (mean difference [MD] = -4.52, 95% confidence interval [-6.29, -2.75]), acetate therapy (MD = -3.12, 95% confidence interval [-5.79, -0.46]), and propionate therapy (MD = -2.96, 95% confidence interval [-5.66, -0.26]) significantly reduced the fasting blood glucose levels compared to the control group; butyrate therapy was probably the most effective intervention, with a surface under the cumulative ranking curve (SUCRA) value of 85.5%. Additionally, acetate plus propionate therapy was probably the most effective intervention for reducing total cholesterol (SUCRA = 85.8%) or triglyceride levels (SUCRA = 88.1%). These findings underscore the potential therapeutic implications of SCFAs for addressing metabolic disorders, particularly in type 2 diabetes mellitus.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
Ktrise发布了新的文献求助10
刚刚
完美怀亦发布了新的文献求助10
刚刚
贪玩夏柳完成签到,获得积分10
刚刚
1秒前
1秒前
李爱国的应助被科研通管家采纳,获得10
1秒前
pluto的应助被科研通管家采纳,获得10
2秒前
思源的应助被科研通管家采纳,获得10
2秒前
GG完成签到,获得积分10
2秒前
jy的应助被博修采纳,获得10
2秒前
火星上火完成签到,获得积分10
3秒前
4秒前
小蘑菇的应助被OnonoImoko采纳,获得10
6秒前
范fan发布了新的文献求助30
6秒前
6秒前
7秒前
科研通AI6.2的应助被煜宁HY采纳,获得10
10秒前
揽万里星河入梦完成签到,获得积分10
11秒前
XXXXXX发布了新的文献求助10
11秒前
务实鞅完成签到,获得积分10
11秒前
wml3466792358完成签到 ,获得积分10
12秒前
罗门完成签到,获得积分10
14秒前
14秒前
务实鞅发布了新的文献求助10
14秒前
14秒前
14秒前
destiny完成签到 ,获得积分10
15秒前
15秒前
彩色蚂蚁完成签到 ,获得积分10
16秒前
标致的半仙完成签到,获得积分10
16秒前
16秒前
xyy完成签到 ,获得积分10
16秒前
橘子发布了新的文献求助10
16秒前
SilverSoul完成签到,获得积分10
18秒前
Xavii发布了新的文献求助10
19秒前
认真台灯完成签到 ,获得积分10
19秒前
RON发布了新的文献求助10
20秒前
顾矜的应助被何梓怡采纳,获得10
21秒前
21秒前
22秒前
高分求助中
(应助此贴封号)通过应助OA文献获取积分 10000
Rosenblum, Global Change Biology 800
Computational Chemical Reaction Engineering: Modeling, Simulation, and Design with MATLAB 600
Organizational Behavior 510
Management and the Arts 510
Production Logging: Theoretical and Interpretive Elements 400
CLSI C56QG Examples of Hemolyzed, Icteric, and Lipemic/Turbid Samples Quick Guide 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 计算机科学 工程类 纳米技术 内科学 物理 有机化学 化学工程 生物化学 复合材料 光电子学 细胞生物学 心理学 量子力学 催化作用 物理化学 电极
热门帖子
关注 科研通微信公众号,转发送积分 7817850
求助须知:如何正确求助?哪些是违规求助? 9346252
关于积分的说明 20534940
捐赠科研通 7410402
什么是DOI,文献DOI怎么找? 3331819
关于科研通互助平台的介绍 2478149
邀请新用户注册赠送积分活动 2351579