Objective:To explore the effects of N6-methyladenine(m^(6)A)modification-related genes,methyltransferase 14(METTL14),and YTH domain family protein 1(YTHDF1),on the proliferation,migration and apoptosis capabilities of...Objective:To explore the effects of N6-methyladenine(m^(6)A)modification-related genes,methyltransferase 14(METTL14),and YTH domain family protein 1(YTHDF1),on the proliferation,migration and apoptosis capabilities of cervical cancer cells and investigate their correlation with programmed cell death-ligand 1(PD-L1)expression.Methods:The expression levels of METTL14,YTHDF1 and PD-L1 in cervical cancer tissues and normal cervical tissues were analyzed using immunohistochemistry.Small interfering RNA(siRNA)was used to knock down the expression of METTL14 and YTHDF1 genes in cervical cancer cells,and the knockdown efficiency was validated by real-time fluorescent quantitative PCR(qPCR).After knockdown of METTL14 and YTHDF1,cell proliferation was assessed by CCK-8 assay,cell migration was examined by Transwell assay,cell apoptosis was detected by flow cytometry,and PD-L1 mRNA and protein expression were evaluated using qPCR and Western blotting,respectively.Results:Immunohistochemistry results demonstrated high expression of METTL14,YTHDF1,and PD-L1 in cervical cancer tissues.Knockdown of METTL14 and YTHDF1 significantly inhibited the proliferation and migration capabilities of cervical cancer cells,increased apoptosis,and downregulated PD-L1 mRNA and protein expression levels.Conclusion:m^(6)A methylation modification can affect the proliferation,migration and apoptosis of cervical cancer cells by regulating the expression of PD-L1 in cervical cancer cells.展开更多
为进一步提高文本相似度计算的准确性,提出基于句向量的文本相似函数(part of speech and order smooth inverse frequency,PO-SIF),从词性和词序方面优化了平滑反频率(smooth inverse frequency,SIF)计算方法,SIF算法的核心是通过加权...为进一步提高文本相似度计算的准确性,提出基于句向量的文本相似函数(part of speech and order smooth inverse frequency,PO-SIF),从词性和词序方面优化了平滑反频率(smooth inverse frequency,SIF)计算方法,SIF算法的核心是通过加权和去除噪声得到句向量来计算句子相似度。在具体计算时,一方面通过增加词性消减因子调节SIF句向量计算权重参数,获得带有词性信息的句向量,另一方面通过将词序相似度与SIF句向量相似度算法进行线性加权优化句子相似度得分。实验结果表明,增加词性和词序的方法可以提升算法准确率。展开更多
基金National Natural Science Foundation of China (No.81472431)Jiangsu Provincial Medical Key Talent Fund (No.ZDRCA2016072)Natural Science Foundation of Nanjing University of Traditional Chinese Medicine (No.XZR2020070)。
文摘Objective:To explore the effects of N6-methyladenine(m^(6)A)modification-related genes,methyltransferase 14(METTL14),and YTH domain family protein 1(YTHDF1),on the proliferation,migration and apoptosis capabilities of cervical cancer cells and investigate their correlation with programmed cell death-ligand 1(PD-L1)expression.Methods:The expression levels of METTL14,YTHDF1 and PD-L1 in cervical cancer tissues and normal cervical tissues were analyzed using immunohistochemistry.Small interfering RNA(siRNA)was used to knock down the expression of METTL14 and YTHDF1 genes in cervical cancer cells,and the knockdown efficiency was validated by real-time fluorescent quantitative PCR(qPCR).After knockdown of METTL14 and YTHDF1,cell proliferation was assessed by CCK-8 assay,cell migration was examined by Transwell assay,cell apoptosis was detected by flow cytometry,and PD-L1 mRNA and protein expression were evaluated using qPCR and Western blotting,respectively.Results:Immunohistochemistry results demonstrated high expression of METTL14,YTHDF1,and PD-L1 in cervical cancer tissues.Knockdown of METTL14 and YTHDF1 significantly inhibited the proliferation and migration capabilities of cervical cancer cells,increased apoptosis,and downregulated PD-L1 mRNA and protein expression levels.Conclusion:m^(6)A methylation modification can affect the proliferation,migration and apoptosis of cervical cancer cells by regulating the expression of PD-L1 in cervical cancer cells.
文摘为进一步提高文本相似度计算的准确性,提出基于句向量的文本相似函数(part of speech and order smooth inverse frequency,PO-SIF),从词性和词序方面优化了平滑反频率(smooth inverse frequency,SIF)计算方法,SIF算法的核心是通过加权和去除噪声得到句向量来计算句子相似度。在具体计算时,一方面通过增加词性消减因子调节SIF句向量计算权重参数,获得带有词性信息的句向量,另一方面通过将词序相似度与SIF句向量相似度算法进行线性加权优化句子相似度得分。实验结果表明,增加词性和词序的方法可以提升算法准确率。