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Updated: Mar 8, 2026

Author Spotlight: Advanced Integrated Model for Sepsis-Induced Myopathy and Single-Cell Metabolic Analysis
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综合多态学和机器学习识别了病原体特异性败血症分层和转化优先级的线粒体生物标志物

Chaoyuan Jin1,2,3, Ruijinlin Hao4, Bate Gonggaoang1,2,3

  • 1Center of Emergency & Intensive Care Unit, Jinshan Hospital, Fudan University, Shanghai, 201508, China.

European journal of medical research
|March 6, 2026
PubMed
概括

这项研究揭示了线粒体基因失调如何导致败血症异质性. 使用这些基因的机器学习模型显示出改善败血症风险分层和生物标志物发现的前景.

关键词:
表观遗传学 在表观遗传学中,表观遗传学是指表观遗传学.门德尔的随机化线粒体功能障碍 线粒体功能障碍多个omics的多个omics.败血症 这是一种败血症.

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Mass spectrometry is a powerful characterization technique that can identify and separate a wide variety of compounds ranging from chemical to biological entities, based on their mass-to-charge ratio (m/z). The instruments that allow this detection, known as mass spectrometers, have three components: an ion source, a mass analyzer, and a detector. These spectrometers differ based on the nature of their ion source and analyzers.Matrix-assisted laser desorption ionization (MALDI) is a commonly...
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