通过综合生物信息学和机器学习算法与RT-qPCR验证来识别川崎病的编程细胞死亡和线粒体相关生物标志物

Tengyang Wang1, Chengyi Wang2, Yiwei Chen1

  • 1Department of Cardiology, Fujian Children's Hospital (Fujian Branch of Shanghai Children's Medical Center), College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, Fujian, China.

Frontiers in genetics
|February 26, 2026
PubMed
概括

这项研究确定了五种生物标志物,这些生物标志物将线粒体功能障碍和川崎病的细胞死亡联系起来,从而提高了诊断准确度. 临床验证证实了潜在的向治疗的三个关键生物标志物.

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