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Your search keyword '"Zhai, Yuhong"' showing total 36 results
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36 results on '"Zhai, Yuhong"'

20. Targeting NEAT1 in heart disease

Author

Zhang, Mengting, primary, Yang, Jun, additional, Zhang, Jing, additional, Yang, Jian, additional, Liu, Haiyin, additional, Zhai, Yuhong, additional, and Zhang, Peiyue, additional

Published
2021
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31. High-Resolution Spatiotemporal Modeling for PM2.5Major Components in the Pearl River Delta and Its Implications for Epidemiological Studies

Author

Wen, Li, Kang, Ning, Wang, Lijie, Wei, Qiannan, Zhang, Hedi, Shen, Jianling, Yue, Dingli, Zhai, Yuhong, and Lin, Weiwei

Abstract

Distinguishing the effects of different fine particulate matter components (PMCs) is crucial for mitigating their effects on human health. However, the sparse distribution of locations where PM is collected for component analysis makes it challenging to investigate the relevant health effects. This study aimed to investigate the agreement between data-fusion-enhanced exposure assessment and site monitoring data in estimating the effects of PMCs on gestational diabetes mellitus (GDM). We first improved the spatial resolution and accuracy of exposure assessment for five major PMCs (EC, OM, NO3–, NH4+, and SO42–) in the Pearl River Delta region by a data fusion model that combined inputs from multiple sources using a random forest model (10-fold cross-validation R2: 0.52 to 0.61; root mean square error: 0.55 to 2.26 μg/m3). Next, we compared the associations between exposures to PMCs during pregnancy and GDM in a hospital-based cohort of 1148 pregnant women in Heshan, China, using both site monitoring data and data-fusion model estimates. The comparative analysis showed that the data-fusion-based exposure generated stronger estimates of identifying statistical disparities. This study suggests that data-fusion-enhanced estimates can improve exposure assessment and potentially mitigate the misclassification of population exposure arising from the utilization of site monitoring data.

Published
2024
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35. High-Resolution Spatiotemporal Modeling for PM 2.5 Major Components in the Pearl River Delta and Its Implications for Epidemiological Studies.

Author

Wen L, Kang N, Wang L, Wei Q, Zhang H, Shen J, Yue D, Zhai Y, and Lin W

Subjects
Humans, China, Female, Rivers chemistry, Pregnancy, Air Pollutants analysis, Environmental Monitoring methods, Epidemiologic Studies, Environmental Exposure, Diabetes, Gestational epidemiology, Particulate Matter analysis
Abstract

Distinguishing the effects of different fine particulate matter components (PMCs) is crucial for mitigating their effects on human health. However, the sparse distribution of locations where PM is collected for component analysis makes it challenging to investigate the relevant health effects. This study aimed to investigate the agreement between data-fusion-enhanced exposure assessment and site monitoring data in estimating the effects of PMCs on gestational diabetes mellitus (GDM). We first improved the spatial resolution and accuracy of exposure assessment for five major PMCs (EC, OM, NO 3 - , NH 4 + , and SO 4 2- ) in the Pearl River Delta region by a data fusion model that combined inputs from multiple sources using a random forest model (10-fold cross-validation R 2 : 0.52 to 0.61; root mean square error: 0.55 to 2.26 μg/m 3 ). Next, we compared the associations between exposures to PMCs during pregnancy and GDM in a hospital-based cohort of 1148 pregnant women in Heshan, China, using both site monitoring data and data-fusion model estimates. The comparative analysis showed that the data-fusion-based exposure generated stronger estimates of identifying statistical disparities. This study suggests that data-fusion-enhanced estimates can improve exposure assessment and potentially mitigate the misclassification of population exposure arising from the utilization of site monitoring data.

Published
2024
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36. Molecular regulatory mechanism of LILRB4 in the immune response.

Author

Liu H, Yang J, Zhang J, Zhang P, Zhang M, Yang C, Liu L, Huang C, Wang W, Zhai Y, and Yang J

Abstract

Immune diseases are caused by the imbalance of immune regulation. This imbalance is regulated by many factors, both negative and positive. Leukocyte immunoglobulin-like receptor B4 (LILRB4) is a member of leukocyte immunoglobulin-like receptors (LILRs). LILRs are expressed constitutively on the surface of multiple immune cells which associate with membrane adaptors to signal through multi- ple cytoplasmic immunoreceptor tyrosine-based inhibitory motifs (ITIMs) or immunoreceptor tyro-sine-based activation motifs (ITAMs). Through ITIM, LILRB4 could recruit the src homology domain type-2-containing tyrosine phosphatase 1 or 2 (SHP-1 or SHP-2) into the cell membrane. In addition, many factors can induce the expression of LILRB4, such as vitamin D, interferon and so on. Studies have demonstrated that LILRB4 had a negative regulatory role in various of immune diseases. The present review intends to expound the structure and function of LILRB4, as well as its regulators and receptors in the immune cells, so as to provide a theoretical basis for immune disease therapy., Competing Interests: The authors declare no conflict of interest., (Copyright © 2023 Termedia.)

Published
2023
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