DPCDI:心力衰竭可药性程序性细胞死亡指数数据表1
DPCDI相关研究的数据表,包含基因筛选、亚型分类、单细胞分析及实验验证结果,用于心力衰竭诊断分层和治疗。

基本信息
资源简介
DPCDI:心力衰竭可药性程序性细胞死亡指数数据表1
【一句话概览】
本数据集是 figshare 公开的结构化表格数据集,收录 1 个文件、合计 3.53 MB,主题涵盖 bioinformatics、cell death、heart failure、machine learning、multi-omics,可用于统计建模、特征工程与队列分析,CC BY 4.0 许可开放获取。
【数据集背景】
本数据集源站标题为《Data Sheet 1_DPCDI: an artificial intelligent-derived indicator interpreting the diagnostic, stratification, and therapeutic implications of druggability programmed cell death in heart failure.docx》。配套论文《Fundamental Mechanisms of Regulated Cell Death and Implications for Heart Disease》发表于 Physiological Reviews(2019),DOI:10.1152/physrev.00022.2018。源站首次发布:2026-01-29。
【数据内容】
源站原始描述:Programmed cell death (PCD) pathways with druggable potential represent a promising but still underexplored frontier in heart failure (HF) research for diagnosis, prognosis, and therapy. To address this gap, we developed a Druggable Programmed Cell Death Index (DPCDI) through an integrative machine learning framework. An optimal combination of Lasso and Random Forest algorithms identified 15 pivotal genes (CALCOCO2, VPS13D, CLU, STAT3, OPTN, UBB, CXCL12, PPP1R15A, ATF4, IVNS1ABP, HMGB2, JAK2, EX…
【数据结构与技术规格】
文件数 1 个,合计 3.53 MB。Data Sheet 1_DPCDI: an artificial intelligent-derived indicator interpreting the diagnostic, stratification, and therapeutic implications of druggabil.docx:application/vnd.openxmlformats-officedocument.wordprocessingml.document,3.53 MB。数据集 DOI:10.3389/fgene.2025.1753636.s001。
【主题与分类】
源站学科分类:Genetics。主题标签:bioinformatics、cell death、heart failure、machine learning、multi-omics。
【适用方向】
结构化表格数据可直接用于统计建模、特征工程与队列分析。
【获取与许可】
源站页面:https://frontiersin.figshare.com/articles/dataset/Data_Sheet_1_DPCDI_an_artificial_intelligent-derived_indicator_interpreting_the_diagnostic_stratification_and_therapeutic_implications_of_druggability_programmed_cell_death_in_heart_failure_docx/31184884
使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。
规范引用:Zhang, Lili; Zhu, Yihao; Fang, Yuan; Yang, Yanping; Yu, Yin; Wang, Hanshi; et al. (2026). Data Sheet 1_DPCDI: an artificial intelligent-derived indicator interpreting the diagnostic, stratification, and therapeutic implications of druggability programmed cell death in heart failure.docx. Frontiers.…
下载信息
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公开数据集受托下载与技术交付服务。
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暂未开放当前数据集主要来源为 Kaggle 公开托管,完整影像包建议通过原始链接或 Kaggle API 获取。
使用方式
数据集获取(Figshare)
- 源站标题:Data Sheet 1_DPCDI: an artificial intelligent-derived indicator interpreting the diagnostic, stratification, and therapeutic implications of druggability programmed cell death in heart failure.docx
- DOI:10.3389/fgene.2025.1753636.s001
- 发布日期:2026-01-29
- 文件数:1 个
- 文件总体积:3.53 MB
- 源站页面:https://frontiersin.figshare.com/articles/dataset/Data_Sheet_1_DPCDI_an_artificial_intelligent-derived_indicator_interpreting_the_diagnostic_stratification_and_therapeutic_implications_of_druggability_programmed_cell_death_in_heart_failure_docx/31184884
命令行下载
curl -L -o "Data Sheet 1_DPCDI: an artificial intelligent-derived indicator interpreting the diagnostic, stratification, and therapeutic implications of druggabil.docx" "https://ndownloader.figshare.com/files/61461982"
文件清单
Data Sheet 1_DPCDI: an artificial intelligent-derived indicator interpreting the diagnostic, stratification, and therapeutic implications of druggabil.docx(3.53 MB)
文件总体积 3.53 MB(源站 API 实测)。
数据说明
Programmed cell death (PCD) pathways with druggable potential represent a promising but still underexplored frontier in heart failure (HF) research for diagnosis, prognosis, and therapy. To address this gap, we developed a Druggable Programmed Cell Death Index (DPCDI) through an integrative machine learning framework. An optimal combination of Lasso and Random Forest algorithms identified 15 pivotal genes (CALCOCO2, VPS13D, CLU, STAT3, OPTN, UBB, CXCL12, PPP1R15A, ATF4, IVNS1ABP, HMGB2, JAK2, EXOC7, ENO1, TPCN1) for DPCDI construction. Non-negative matrix factorization (NMF) analysis stratified HF patients into two distinct subtypes, with Subtype 2 exhibiting elevated apoptosis and mitophagy activity. Single-cell RNA sequencing revealed dynamic JAK2 and IVNS1ABP expression during cardiomyocyte state transitions, while CXCL12 showed stage-specific regulation in endothelial cells. Mendelian randomization analysis indicated that genetic predisposition to elevated JAK2 and STAT3 expression was associated with reduced HF risk, whereas CXCL12 overexpression increased susceptibility. Experimental validation in HF mouse models confirmed increased Cxcl12 and Jak2 expression and decreased Stat3 levels. Furthermore, knockout of Cxcl12, Jak2, and Stat3 induced HF phenotypes. Molecular docking identified pifithrin-α as a potent ligand for CXCL12 and strophanthidin for STAT3. Collectively, DPCDI provides a comprehensive framework for HF diagnosis, risk stratification, and targeted therapeutic development.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.3389/fgene.2025.1753636.s001(source: https://frontiersin.figshare.com/articles/dataset/Data_Sheet_1_DPCDI_an_artificial_intelligent-derived_indicator_interpreting_the_diagnostic_stratification_and_therapeutic_implications_of_druggability_programmed_cell_death_in_heart_failure_docx/31184884)。
数据缺失?
依托陕西、四川两大基地,我们与超过十家三甲医院建立直接合作关系,覆盖合规授权、采集治理、专业标注、数据交付的全流程,为AI医疗团队提供即拿即用的高质量临床数据。
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