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相关概念视频

Introduction to the Human Microbiota01:22

Introduction to the Human Microbiota

Microorganisms colonize various regions of the human body, including the mouth, nasal passages, throat, stomach, intestines, urogenital tract, and skin. The total number of microbial cells is estimated to range from 10¹³ to 10¹⁴—comparable to, or exceeding, the number of human somatic cells. This host–microbiome relationship has led to the conceptualization of humans as supraorganisms, wherein microbial communities perform vital roles in development, immunity, and disease...
Development of Human Microbiota01:30

Development of Human Microbiota

The human microbiota begins developing at birth and undergoes continual change as we age. Infancy marks a critical period of microbial sensitivity, offering a “window of opportunity” during which beneficial microbes help mature the immune system. By age three, children typically develop a more stable and diverse microbial community. Newborns acquire microbes from their immediate environment; vaginal delivery favors maternal vaginal microbes, while cesarean births favor microbes from the skin...
The Skin Microbiota01:27

The Skin Microbiota

The human skin serves as a complex ecosystem inhabited by a diverse community of microorganisms, including bacteria, fungi, and viruses. This microbiome plays a critical role in maintaining skin health and defending against pathogenic invaders. The composition of microbial communities varies significantly across different regions of the body, influenced primarily by the local levels of moisture and sebum.Regional Variation in Skin MicrobiotaCutibacterium acnes predominantly colonizes sebaceous...
The Oral Microbiota01:27

The Oral Microbiota

The oral microbiome includes a complex ecosystem comprising over 700 microbial species, identified through genomic sequencing and culture-based analyses to date. This community includes a core microbiome, found universally among individuals, and a variable component influenced by environmental factors such as diet, lifestyle, and host genetics. Site-specific conditions, including oxygen gradients, pH levels, and nutrient availability, determine the spatial distribution of these microorganisms...
Microbiota of the Respiratory Tract01:29

Microbiota of the Respiratory Tract

The human respiratory tract, comprising the upper and lower segments, serves as a critical interface with the external environment. The upper respiratory tract (URT)—including the nostrils, sinuses, pharynx, and oropharynx—is heavily colonized by microbes, while the lower respiratory tract (LRT), composed of the larynx, trachea, bronchi, and lungs, was long thought to be sterile. However, recent molecular studies have revealed that the lungs are not devoid of microbes but act more like...
Microbiota Modulation by Antibiotics01:21

Microbiota Modulation by Antibiotics

Antibiotics have revolutionized modern medicine by saving countless lives from bacterial infections. However, their widespread use has inadvertently harmed the delicate balance of the human gut microbiota. The gut microbiota, a complex community of bacteria, archaea, viruses, and fungi, plays a vital role in regulating metabolism, immune responses, and maintaining intestinal health. Antibiotics, especially broad-spectrum types, disrupt this ecosystem by eradicating both harmful and beneficial...

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相关实验视频

Updated: Jul 13, 2026

Characterization of Inflammatory Responses During Intranasal Colonization with Streptococcus pneumoniae
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Published on: January 17, 2014

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根据微生物群关系网络预测鼻腔疾病.

Yibo Liang1, Jie Mao2, Tianlei Qiu3

  • 1Department of Otorhinolaryngology Head and Neck Surgery, Tianjin First Central Hospital, Institute of Otolaryngology of Tianjin, Key Laboratory of Auditory Speech and Balance Medicine, Key Medical Discipline of Tianjin (Otolaryngology), Quality Control Centre of Otolaryngology, Tianjin, China.

Science progress
|February 18, 2025
PubMed
概括

研究人员确定了主要的鼻菌 (Moraxella,Prevotella,Rothia),它们作为鼻病的标记物. 这一发现有助于预测疾病状态并制定有针对性的预防策略.

关键词:
鼻腔微生物组是指鼻腔的微生物组.疾病预测 疾病预测图形理论中的图形理论.机器学习是机器学习.关系网络 关系网络 关系网络

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Divergence of Root Microbiota in Different Habitats based on Weighted Correlation Networks
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相关实验视频

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科学领域:

  • 微生物组研究的研究.
  • 医学诊断 医学诊断 医学诊断
  • 生物信息学是一种生物信息学.

背景情况:

  • 越来越多地认识到当地微生物组在预测宿主疾病状态方面的潜力.
  • 开发具有最小特征的预测模型仍然是微生物组研究的一个重大挑战.

研究的目的:

  • 建立鼻子微生物群数据库,并确定用于预测鼻病的关键细菌属.
  • 开发一个机器学习框架,与图形理论集成,以实现高效的特征选择.

主要方法:

  • 从132名慢性鼻炎患者,27名鼻倒膜瘤患者和45名对照患者中创建了一个鼻子微生物组数据库.
  • 使用16S rRNA基因测序来确定细菌物种和数量.
  • 机器学习框架与细菌相关性网络的图形理论分析相结合,用于选择预测特征.

主要成果:

  • 在患有鼻病的患者中观察到明显的鼻子微生物群特征.
  • 摩拉塞拉 (Moraxella),普雷沃特拉 (Prevotella) 和罗提亚 (Rothia) 被确定为标志着鼻病的基石属.
  • 图形理论分析显示,这些属是鼻腔微生物群中的关键控制路线.

结论:

  • 开发的框架有效地识别了用于预测鼻腔疾病状态的关键细菌属.
  • 这种方法可以为疾病预防和控制政策提供信息.
  • 该方法适用于其他疾病,用于识别有影响力的基石属和预测疾病状态.