相关实验视频

Updated: Jul 12, 2025

Multiplex Detection of Bacteria in Complex Clinical and Environmental Samples using Oligonucleotide-coupled Fluorescent Microspheres

Multiplex Detection of Bacteria in Complex Clinical and Environmental Samples using Oligonucleotide-coupled Fluorescent Microspheres

Published on: October 23, 2011

功能数据分析以描述频繁的纵向数据中的疾病模式:使用每周Nugent分数对细菌性阴道微生物群模式的应用,并确定模式特异性风险因素

Rahul Biswas¹, Marie Thoma², Xiangrong Kong³

¹University of Washington, Seattle, WA, USA.

BMC medical research methodology

|October 26, 2023

概括

先进的技术使频繁的生物标志物监测成为可能,揭示了女性独特的阴道微生物群模式. 持续性细菌性阴道炎 (BV) 的关键风险因素包括年龄较小和特定避孕药的使用.

科学领域:

微生物学微生物学
流行病学流行病学
数据科学数据科学数据科学

背景情况:

技术进步允许更频繁的生物标志物监测,从而获得密集采样的纵向数据.
这种数据结构有助于研究疾病病因和进展的人内变异性.
细菌性阴道炎 (BV) 发病因子被用乌干达妇女的每周阴道微生物群Nugent分数研究了两年.

研究的目的:

用数据驱动的方法来描述阴道微生物群波动的纵向模式.
为了确定阴道微生物群变化的临床意义上的模式.
识别与不同阴道微生物群模式相关的风险因素,以了解BV病变发生.

主要方法:

功能性主要组件分析用于时间序列Nugent分数的维度缩小.
一个层次的功能聚类框架被用来识别不同的阴道微生物群模式.
多项逻辑回归确定了与每个已识别模式相关的风险因素.

主要成果:

在211名女性中,在两年内确定了四种不同的阴道微生物群模式:持续的BV,持续的正常,波动的BV主导和波动的正常主导.
与持续性BV相关的因素包括较高的初始Nugent分数,年龄较小 (<20岁),未受保护的游泳水源,未受割礼的伴侣和使用荷尔蒙避孕药.

结论:

层次功能数据集群对于密集采样的纵向数据的无监督集群是有效的.
这种方法可以识别临床信息集群和相关的风险因素.
这些发现有助于更好地了解BV病变的流行病学和病因学.

关键词:

功能数据聚类功能数据聚类.在人体内变化的变化.纵向数据分析的数据分析.没有监督的学习学习.阴道菌群阴道菌群

更多相关视频

Characterization and Functional Prediction of Bacteria in Ovarian Tissues

Characterization and Functional Prediction of Bacteria in Ovarian Tissues

Published on: October 23, 2021

Models of Murine Vaginal Colonization by Anaerobically Grown Bacteria

Models of Murine Vaginal Colonization by Anaerobically Grown Bacteria

Published on: May 25, 2022

相关概念视频

Modern Molecular Taxonomy

Modern Molecular Taxonomy

Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...

Statistical Methods for Analyzing Epidemiological Data

Statistical Methods for Analyzing Epidemiological Data

Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:

Applications of Molecular Taxonomy

Applications of Molecular Taxonomy

Molecular taxonomy has revolutionized the understanding and classification of bacteria, providing precise insights into their diversity, evolutionary relationships, and ecological roles. By utilizing molecular techniques such as DNA sequencing and fingerprinting, researchers have made significant strides in various fields related to bacterial studies.Resolving Taxonomic AmbiguitiesMolecular taxonomy has been instrumental in distinguishing closely related bacterial species initially thought to...