生物能聚类分析——人成纤维细胞中的线粒体呼吸控制

Bioenergetic cluster analysis – mitochondrial respiratory control in human fibroblasts

Keywords：human dermal fibroblasts HDF, living cells ce, cell respiration, coupling control, oxidative phosphorylation OXPHOS, age, senescence, bioenergetic cluster analysis BCA, meta-analysis, normalization, high-resolution respirometry HRR, Oroboros O2k, Seahorse XF Analyzer, outlier-skewness index OSI, regression analysis

关键词：人真皮成纤维细胞 HDF，活细胞 ce，细胞呼吸，耦合控制，氧化磷酸化 OXPHOS，年龄，衰老，生物能簇分析 BCA，荟萃分析，归一化，高分辨率呼​​吸测量 HRR，Oroboros O2k，Seahorse XF 分析仪，离群偏度指数 OSI，回归分析 
作者：Gnaiger Erich
出版期刊：《MitoFit Preprints 》（2021.8）

Abstract：

Cell respiration reflects mitochondrial fitness and plays a pivotal role in health and disease. Despite the rapidly increasing number of applications of cell respirometry to address current challenges in biomedical research, cross-references are rare between respirometric projects and platforms. Evaluation of accuracy and reproducibility between laboratories requires presentation of results in a common format independent of the applied method. When cell respiration is expressed as oxygen consumption rate in an experimental chamber, normalization is mandatory for comparability of results. Concept-driven normalization and regression analysis are key towards bioenergetic cluster analysis presented as a graphical tool to identify discrete data populations.
 

文章摘要：

细胞呼吸反映了线粒体的健康状况，并在健康和疾病中发挥着关键作用。尽管细胞呼吸测量的应用数量迅速增加，以解决当前生物医学研究中的挑战，但呼吸测量项目和平台之间的交叉引用很少见。评估实验室之间的准确性和再现性需要以独立于所应用方法的通用格式呈现结果。当细胞呼吸表示为实验室中的耗氧率时，为了结果的可比性，必须进行标准化。概念驱动的归一化和回归分析是生物能聚类分析的关键，它作为一种图形工具来识别离散数据群。

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文章题目、关键词与摘要译文仅用于参考。