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Li, Yao-Ping,Tian, Fu-Guo,Shi, Peng-Cheng,Guo, Ling-Yun,Wu, Hai-Ming,Chen, Run-Qi,Xue, Jin-Ming Asian Pacific Journal of Cancer Prevention 2014 Asian Pacific journal of cancer prevention Vol.15 No.23
4-Hydroxynonenal (4-HNE) is a stable end product of lipid peroxidation, which has been shown to play an important role in cell signal transduction, while increasing cell growth and differentiation. 4-HNE could inhibit phosphatase and tensin homolog (PTEN) activity in hepatocytes and increased levels have been found in human invasive breast cancer. Here we report that 4-HNE increased the cell growth of breast cancer cells as revealed by colony formation assay. Moreover, vascular endothelial growth factor (VEGF) expression was elevated, while protein levels of hypoxia inducible factor 1 alpha (HIF-$1{\alpha}$) were up-regulated. Sirtuin-3 (SIRT3), a major mitochondria NAD+-dependent deacetylase, is reported to destabilize HIF-$1{\alpha}$. Here, 4-HNE could inhibit the deacetylase activity of SIRT3 by thiol-specific modification. We further demonstrated that the regulation by 4-HNE of levels of HIF-$1{\alpha}$ and VEGF depends on SIRT3. Consistent with this, 4-HNE could not increase the cell growth in SIRT3 knockdown breast cancer cells. Additionally, 4-HNE promoted angiogenesis and invasion of breast cancer cells in a SIRT3-dependent manner. In conclusion, we propose that 4-HNE promotes growth, invasion and angiogenesis of breast cancer cells through the SIRT3-HIF-$1{\alpha}$-VEGF axis.
Discrimination of neutrons and gamma-rays in plastic scintillator based on spiking cortical model
Liu Bing-Qi,Liu Hao-Ran,Chang Lan,Cheng Yu-Xin,Zuo Zhuo,Li Peng 한국원자력학회 2023 Nuclear Engineering and Technology Vol.55 No.9
In this study, a spiking cortical model (SCM) based n-g discrimination method is proposed. The SCMbased algorithm is compared with three other methods, namely: (i) the pulse-coupled neural network (PCNN), (ii) the charge comparison, and (iii) the zero-crossing. The objective evaluation criteria used for the comparison are the FoM-value and the time consumption of discrimination. Experimental results demonstrated that our proposed method outperforms the other methods significantly with the highest FoM-value. Specifically, the proposed method exhibits a 34.81% improvement compared with the PCNN, a 50.29% improvement compared with the charge comparison, and a 110.02% improvement compared with the zero-crossing. Additionally, the proposed method features the second-fastest discrimination time, where it is 75.67% faster than the PCNN, 70.65% faster than the charge comparison and 38.4% slower than the zero-crossing. Our study also discusses the role and change pattern of each parameter of the SCM to guide the selection process. It concludes that the SCM's outstanding ability to recognize the dynamic information in the pulse signal, improved accuracy when compared to the PCNN, and better computational complexity enables the SCM to exhibit excellent n-g discrimination performance while consuming less time.