机器学习查和验证毒症相关基因签名在败血症中的验证
Jingjing Xu1, Mingyu Zhu1, Pengxiang Luo2
1Department of Intensive Care Unit, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, People's Republic of China.
Journal of inflammation research
|July 25, 2024
概括
细胞死亡过程PANoptosis与败血症有关,影响免疫反应. 鉴定与PANoptosis相关的基因为败血症提供了新的诊断和治疗策略.
科学领域:
- 免疫学 免疫学 免疫学
- 分子生物学分子生物学
- 遗传学 是一个遗传学.
背景情况:
- 败血症是一种危及生命的疾病,其特点是器官功能障碍和免疫失调.
- 涉及相互连接的编程细胞死亡途径的PANoptosis是一个新的概念,在败血症中没有明确的作用.
- 了解败血症中的PANoptosis对于开发新的治疗策略至关重要.
研究的目的:
- 为了调查与PANoptosis相关的基因 (PRG) 在败血症中的作用.
- 为了确定与败血症中PRG相关的免疫特征.
- 开发基于PRG的败血症预测模型.
主要方法:
- 利用GSE65682数据集来识别PRG和免疫特征.
- 基于PRG的败血症样本分类的员工共识ClusterPlus.
- 应用权重基因共同表达网络分析 (WGCNA) 以确定枢纽基因.
- 开发和验证机器学习模型,包括SVM,用于败血症预测.
主要成果:
- 在败血症患者中,PRG表达失调,与免疫细胞透相关.
- 确定了两种与PANoptosis相关的不同群体,与免疫通路有关.
- SVM模型显示出高预测准确性 (AUC=0.967内部,0.989外部),并通过名谱和生存分析得到验证.
结论:
- 泛性亡与败血症密切相关,影响免疫反应.
- PRG可以作为毒症诊断的潜在生物标志物.
- 这项研究提供了对败血症潜在治疗点的见解.
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