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| 1 | Liver cancer incidence and mortality in China: Temporal trends and projections to 2030显示文摘Objective: Liver cancer is one of the most common cancers and major cause of cancer deaths in China,which accounts for over 50% of new cases and deaths worldwide.The systematic liver cancer statistics including of projection through 2030 could provide valuable information for prevention and control strategies in China,and experience for other countries.Methods: The burden of liver cancer in China in 2014 was estimated using 339 cancer registries' data selected from Chinese National Cancer Center(NCC).Incident cases of 22 cancer registries were applied for temporal trends from 2000 to 2014.The burden of liver cancer through 2030 was projected using age-period-cohort model.Results: About 364,800 new cases of liver cancer(268,900 males and 95,900 females) occurred in China,and about 318,800 liver cancer deaths(233,500 males and 85,300 females) in 2014.Western regions of China had the highest incidence and mortality rates.Incidence and mortality rates decreased by about 2.3% and 2.6% per year during the period of 2000-2014,respectively,and would decrease by more than 44% between 2014 and 2030 in China.The young generation,particularly for those aged under 40 years,showed a faster down trend.Conclusions: Based on the analysis,incidence and mortality rates of liver cancer are expected to decrease through 2030,but the burden of liver cancer is still serious in China,especially in rural and western areas.Most cases of liver cancer in China can be prevented through vaccination and more prevention efforts should be focused on high risk groups. | Rongshou Zheng Chunfeng Qu Siwei Zhang Hongmei Zeng Kexin Sun Xiuying Gu Changfa Xia Zhixun Yang He Li Wenqiang Wei Wanqing Chen Jie He | 2018 | Chinese Journal of Cancer Research2018，30，6： | 132 |
| 2 | Effective Vietnamese Sentiment Analysis Model Using Sentiment Word Embedding and Transfer Learning显示文摘Sentiment analysis is one of the most popular fields in NLP,and with the development of computer software and hardware,its application is increasingly extensive.Supervised corpus has a positive effect on model training,but these corpus are prohibitively expensive to manually produce.This paper proposes a deep learning sentiment analysis model based on transfer learning.It represents the sentiment and semantics of words and improves the effect of Vietnamese sentiment analysis model by using English corpus.It generated semantic vectors through Word2Vec,an open-source tool,and built sentiment vectors through LSTM with attention mechanism to get sentiment word vector.With the method of sharing parameters,the model was pre-training with English corpus.Finally,the sentiment of the text was classified by stacked Bi-LSTM with attention mechanism,with input of sentiment word vector.Experiments show that the model can effectively improve the performance of Vietnamese sentiment analysis under small language materials. | Yong Huang Siwei Liu Liangdong Qu Yongsheng Li | 2020 | 国际计算机前沿大会会议论文集2020，，2： | 0 |
| 3 | Dynamic changes of autophagy during hypertrophic scar formation and the role of autophagy intervention显示文摘Background:The role of autophagy in the formation of hypertrophic scars(HS)remains unclear.This study aimed to explore the role and potential mechanism of autophagy during the development of HS.Methods:RNA and protein expression levels of Beclin-1,p62,and LC3II in normal skin tissues and HS specimens from different patients were examined.Autophagy inducers and inhibitors were used to cure established HS in rabbit ears,and the expression of Beclin-1,p62,and LC3II at the RNA and protein level was determined.Lastly,the effects of autophagy inducers and inhibitors on HS development were analyzed.Results:Compared to normal skin tissues,the expression of LC3II and Beclin-1 was higher(P<0.05),while that of p62 was lower(P<0.05)in HS tissues.In addition,the LC3II/LC3I ratio was increased during HS formation,and the altered expression of the three proteins stabilized after one year.Administration of autophagy inducers enhanced the formation of HS as well as the expression levels of LC3II and Beclin-1 but decreased p62 expression.Meanwhile,administration of autophagy inhibitors increased the expression of LC3II,Beclin-1,and p62,along with reduced HS formation.Conclusion:Autophagic activity increased during HS initiation and subsequent stabilization.In addition,autophagy inhibitors were able to inhibit HS formation by suppressing autophagy,whereas autophagy inducers promoted scar hyperplasia by enhancing autophagy。 | Yu Liu Xiaoxia Chen Yuan Fang Yu Yan Bin He Junlin Liao Ke Cao Xi Zhang Siwei Qu Jianda Zhou | 2021 | Chinese Journal Of Plastic and Reconstructive Surgery2021，3，3： | 0 |
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