2篇
您的检索式：作者名="Chuchu Lin"
|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | Biodegradable calcium sulfide-based nanomodulators for H_(2)S-boosted Ca^(2+)-involved synergistic cascade cancer therapy显示文摘Hydrogen sulfide(H_(2)S)is the most recently discovered gasotransmitter molecule that activates multiple intracellular signaling pathways and exerts concentration-dependent antitumor effect by interfering with mitochondrial respiration and inhibiting cellular ATP generation.Inspired by the fact that H_(2)S can also serve as a promoter for intracellular Ca^(2+)influx,tumor-specific nanomodulators(I-CaS@PP)have been constructed by encapsulating calcium sulfide(CaS)and indocyanine green(ICG)into methoxy poly(ethylene glycol)-b-poly(lactide-co-glycolide)(PLGA-PEG).I-CaS@PP can achieve tumor-specific biodegradability with high biocompatibility and pH-responsive H_(2)S release.The released H_(2)S can effectively suppress the catalase(CAT)activity and synergize with released Ca^(2+)to facilitate abnormal Ca^(2+)retention in cells,thus leading to mitochondria destruction and amplification of oxidative stress.Mitochondrial dysfunction further contributes to blocking ATP synthesis and downregulating heat shock proteins(HSPs)expression,which is beneficial to overcome the heat endurance of tumor cells and strengthen ICG-induced photothermal performance.Such a H_(2)S-boosted Ca^(2+)-involved tumor-specific therapy exhibits highly effective tumor inhibition effect with almost complete elimination within 14-day treatment,indicating the great prospect of CaS-based nanomodulators as antitumor therapeutics. | Chuchu Lin Chenyi Huang Zhaoqing Shi Meitong Ou Shengjie Sun Mian Yu Ting Chen Yunfei Yi Xiaoyuan Ji Feng Lv Meiying Wu Lin Mei | 2022 | Acta Pharmaceutica Sinica B2022，12，12： | 0 |
| 2 | Improving sentiment analysis accuracy with emoji embedding显示文摘Due to the diversity and variability of Chinese syntax and semantics,accurately identifying and distinguishing individual emotions from online texts is challenging.To overcome this limitation,we incorporate a new source of individual sentiment,emojis,which contain thousands of graphic symbols and are increasingly being used for expressing emotion in online conversations.We examined popular sentiment analysis algorithms,including rule-based and classification algorithms,to evaluate the impact of supplementing emojis as additional features to improve the algorithm performance.Emojis were also translated into corresponding sentiment words when con-structing features for comparison with those directly generated from emoji label words.In addition,considering different functions of emojis in texts,we classified all posts in the dataset by their emoji usage and examined the changes in algorithm performance.We found that emojis are effective as expanding features for improving the accuracy of sentiment analysis algorithms,and the algorithm performance can be further increased by taking different emoji usages into consideration.In this study,we developed an improved emoji-embedding model based on Bi-LSTM(namely,CEmo-LSTM),which achieves the highest accuracy(around 0.95)when analyzing online Chinese texts.We applied the CEmo-LSTM algorithm to a large dataset collected from Weibo from December 1,2019 to March 20,2020 to understand the sentiment evolution of online users during the COVID-19 pandemic.We found that the pandemic remarkably impacted individual sentiments and caused more passive emotions(e.g.,horror and sadness).Our novel emoji-embedding algorithm creatively combined emojis as well as emoji usage with the sentiment analysis model and can handle emotion mining tasks more effectively and efficiently. | Chuchu Liu Fan Fang Xu Lin Tie Cai Xu Tan Jianguo Liu Xin Lu | 2021 | Journal of Safety Science and Resilience2021，2，4： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员