Meta-analysis of gut microbiota biodiversity in patients with polycystic ovary syndrome based on medical images

IF 2.5 4区 医学 Q3 BIOCHEMICAL RESEARCH METHODS SLAS Technology Pub Date : 2024-08-01 DOI:10.1016/j.slast.2024.100178
Baimiao Wang, Lanyawen Hu, Panpan Dong
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Abstract

PCOS is thought to be associated with metabolic disorders, endocrine disorders, and reproductive system problems. By collecting relevant literature and conducting meta-analyses, we integrated data from multiple studies to enhance the reliability of the analysis results. Studies with medical image data were selected to ensure the accuracy and credibility of the studies. A statistical framework was employed to examine the biodiversity indicators associated with the gut microbiota. These findings provide robust support for the notion that PCOS is intricately linked to notable alterations within the gut microbial community. The utilization of a statistical approach and the systematic synthesis of research findings in this meta-analysis contribute to a more comprehensive understanding of the substantial impact of PCOS on the gut microbiota landscape. PCOS patients showed significant changes in the relative abundance of certain bacteria in their gut microbiota. This imbalance will lead to the instability of intestinal microecological environment, and then affect the health of the body.

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基于医学影像的多囊卵巢综合征患者肠道微生物群生物多样性元分析。
多囊卵巢综合征被认为与代谢紊乱、内分泌失调和生殖系统问题有关。通过收集相关文献并进行荟萃分析,我们整合了多项研究的数据,以提高分析结果的可靠性。为了确保研究的准确性和可信度,我们选择了带有医学图像数据的研究。我们采用了一个统计框架来研究与肠道微生物群相关的生物多样性指标。这些研究结果为多囊卵巢综合症与肠道微生物群落的显著变化密切相关这一观点提供了有力的支持。在这项荟萃分析中,统计方法的使用和研究结果的系统综合有助于更全面地了解多囊卵巢综合症对肠道微生物群景观的重大影响。多囊卵巢综合症患者肠道微生物群中某些细菌的相对丰度发生了显著变化。这种失衡会导致肠道微生态环境的不稳定,进而影响人体健康。
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来源期刊
SLAS Technology
SLAS Technology Computer Science-Computer Science Applications
CiteScore
6.30
自引率
7.40%
发文量
47
审稿时长
106 days
期刊介绍: SLAS Technology emphasizes scientific and technical advances that enable and improve life sciences research and development; drug-delivery; diagnostics; biomedical and molecular imaging; and personalized and precision medicine. This includes high-throughput and other laboratory automation technologies; micro/nanotechnologies; analytical, separation and quantitative techniques; synthetic chemistry and biology; informatics (data analysis, statistics, bio, genomic and chemoinformatics); and more.
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