基于人群健康效应机制链条与高通量分析的沙尘PM2.5心血管毒性组分识别及毒性效应演变研究
结题报告
批准号:
92143202
项目类别:
重大研究计划
资助金额:
100.0 万元
负责人:
李湉湉
学科分类:
环境毒理与健康
结题年份:
2023
批准年份:
2021
项目状态:
已结题
项目参与者:
李湉湉
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中文摘要
沙尘期间PM2.5毒性增强,但沙尘PM2.5中何种组分具有毒性仍难以回答。现有技术多通过细胞或动物实验识别毒性组分,通量较低且人群健康影响代表性不足。亟需建立基于人群健康效应的技术方法以识别沙尘PM2.5关键毒性组分。本项目以人群心血管健康为切入点,①基于多中心健康大数据阐明我国沙尘PM2.5与人群心血管疾病多维度结局的关系,为毒性研究提供流行病学证据支撑;②依托并串联高通量化学分析、多样本多因子免疫检测、环境健康大数据高速计算、毒理学实验四个平台,建立一套基于人群健康效应机制链条及高通量分析的毒性组分识别技术体系;③开发远程实时监测技术对真实世界沙尘PM2.5及人群健康效应展开追踪;④应用已建立的识别技术,基于真实世界沙尘PM2.5组分及人群健康数据,识别出沙尘PM2.5心血管毒性关键组分及其机制,厘清毒性效应时空演变特征,为科学精准防范沙尘心血管健康风险提供依据。
英文摘要
The toxicity of PM2.5 increases during periods of high dust activity, but it is difficult to pinpoint which components in dust PM2.5 are toxic. Existing technology mostly identifies toxic components through cell or animal experiments, but the throughput is low and the impact on human health cannot be confirmed. It is urgent to establish a technical method based on population health effects to identify the key toxic components of dust PM2.5. This project uses population cardiovascular health as the starting point, and the main research contents include: ① Using a multi-center big data approach to identify the relationship between PM2.5 and multidimensional outcomes of cardiovascular disease in China, which will be clarified to provide epidemiologic evidence in support of toxicity research; ② Relying on the four platforms of high-throughput chemical analysis, multi-factor immunoassay, high-speed computing of environmental health big data, and toxicology experiment, a toxic component identification technology system based on population health effect chains and high-throughput analyses will be established; ③ An integrated system based on remote real-time monitoring technology will be developed to track dust PM2.5 and population health effects in the real world; ④ Based on the real-world dust PM2.5 components and population health data, the established identification technology will finally be used to identify the key components and mechanisms of cardiovascular toxicity of dust PM2.5, and to clarify the temporal and spatial evolution characteristics of toxicity effects. This study can ultimately provide a basis for the scientific and accurate prevention of cardiovascular health risks from dust.
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DOI:10.1016/j.xpro.2023.102090
发表时间:2023-03-17
期刊:STAR PROTOCOLS
影响因子:--
作者:Lu, Kailai;Ban, Jie;Wang, Qing;Li, Tiantian
通讯作者:Li, Tiantian
DOI:10.1016/j.ecoenv.2022.114149
发表时间:2022
期刊:Ecotoxicology and Environmental Safety
影响因子:--
作者:Yi Zhang;Wei Li;Ning Jiang;Shudan Liu;Jingyuan Liang;Nana Wei;Yuanyuan Liu;Yaohua Tian;Da Feng;Jinxi Wang;Chen Wei;Xun Tang;Tiantian Li;Pei Gao
通讯作者:Pei Gao
DOI:10.1038/s41467-023-42530-w
发表时间:2023-10-27
期刊:NATURE COMMUNICATIONS
影响因子:16.6
作者:Zhang, Can;Yan, Meilin;Du, Hang;Ban, Jie;Chen, Chen;Liu, Yuanyuan;Li, Tiantian
通讯作者:Li, Tiantian
DOI:10.1016/j.xinn.2023.100427
发表时间:2023-05-15
期刊:INNOVATION
影响因子:32.1
作者:Li, Tiantian;Zhang, Can;Ban, Jie;Du, Peng;Ma, Runmei;Kinney, Patrick L.
通讯作者:Kinney, Patrick L.
DOI:10.1126/sciadv.abm4097
发表时间:2022-07-01
期刊:SCIENCE ADVANCES
影响因子:13.6
作者:Ban, Jie;Su, Wenjing;Li, Tiantian
通讯作者:Li, Tiantian
国内基金
海外基金