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- 저자 : Zhang Qiqiong (검색결과 3 건)
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Yang Lei,Zhang Qiqiong,Yang Qiuye 한국유전학회 2022 Genes & Genomics Vol.44 No.11
Background: Oral squamous cell carcinoma (OSCC) is a frequently-diagnosed malignancy with high potential for proliferation and invasion. Histone methylation is known as a crucial mechanism that regulates pathological processes in various cancers, including OSCC. Objective: This study sought to delve into the molecular mechanism of lysine demethylase 3 A (KDM3A) in OSCC cell proliferation and invasion. Methods: Expression levels of KDM3A, lysin-9 of di-methylated histone H3 (H3K9me2), and doublecortin-like kinase 1 (DCLK1) in cells were determined by reverse-transcription quantitative polymerase chain reaction or Western blot analysis. Cell proliferation and invasion were evaluated by cell counting kit-8, colony formation, and Transwell assays. The enrichment of KDM3A and H3K9me2 on the DCLK1 promoter was determined by chromatin immunoprecipitation assay. The functional rescue experiment was performed with DCLK1 overexpression vector and si-KDM3A in CAL-27 and SCC-9 cells. Results: KDM3A was elevated in OSCC cells. KDM3A knockdown suppressed OSCC proliferation and invasion, along with increased H3K9me2 level in OSCC cells. KDM3A and H3K9me2 were enriched on the DCLK1 promoter and inhibiting H3K9me2 improved DCLK1 expression levels. DCLK1 overexpression neutralized the inhibition of KDM3A knockdown on OSCC proliferation and invasion. Conclusions: KDM3A facilitated OSCC proliferation and invasion by eliminating H3K9me2 to upregulate DCLK1 expression levels.
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Regularization Parameter Selection for Total Variation Model Based on Local Spectral Response
Yuhui Zheng,Kai Ma,Qiqiong Yu,Jianwei Zhang,Jin Wang 한국정보처리학회 2017 Journal of information processing systems Vol.13 No.5
In the past decades, various image regularization methods have been introduced. Among them, total variationmodel has drawn much attention for the reason of its low computational complexity and well-understoodmathematical behavior. However, regularization parameter estimation of total variation model is still an openproblem. To deal with this problem, a novel adaptive regularization parameter selection scheme is proposedin this paper, by means of using the local spectral response, which has the capability of locally selecting theregularization parameters in a content-aware way and therefore adaptively adjusting the weights between thetwo terms of the total variation model. Experiment results on simulated and real noisy image show the goodperformance of our proposed method, in visual improvement and peak signal to noise ratio value.
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Regularization Parameter Selection for Total Variation Model Based on Local Spectral Response
Zheng, Yuhui,Ma, Kai,Yu, Qiqiong,Zhang, Jianwei,Wang, Jin Korea Information Processing Society 2017 Journal of information processing systems Vol.13 No.5
In the past decades, various image regularization methods have been introduced. Among them, total variation model has drawn much attention for the reason of its low computational complexity and well-understood mathematical behavior. However, regularization parameter estimation of total variation model is still an open problem. To deal with this problem, a novel adaptive regularization parameter selection scheme is proposed in this paper, by means of using the local spectral response, which has the capability of locally selecting the regularization parameters in a content-aware way and therefore adaptively adjusting the weights between the two terms of the total variation model. Experiment results on simulated and real noisy image show the good performance of our proposed method, in visual improvement and peak signal to noise ratio value.
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