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31 results on '"Zhang, Jie‐Xin"'

3. Innate Root Exudates Contributed to Contrasting Coping Strategies in Response to Ralstonia solanacearum in Resistant and Susceptible Tomato Cultivars

Author

Liu, Chong, primary, Geng, Hao-Yang, additional, Li, Wang-Xi, additional, Li, Ya-Ying, additional, Lu, Yu-Sheng, additional, Xie, Kai-Zhi, additional, Sun, Li−Li, additional, Zhang, Jie-Xin, additional, Peng, Huan-Long, additional, Shi, Chao-Hong, additional, Li, Wan-Ling, additional, Zhou, Chang-Min, additional, Gu, Wen-Jie, additional, and Wang, Dan, additional

Published
2023
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8. Innate Root Exudates Contributed to Contrasting Coping Strategies in Response to Ralstonia solanacearumin Resistant and Susceptible Tomato Cultivars

Author

Liu, Chong, Geng, Hao-Yang, Li, Wang-Xi, Li, Ya-Ying, Lu, Yu-Sheng, Xie, Kai-Zhi, Sun, Li−Li, Zhang, Jie-Xin, Peng, Huan-Long, Shi, Chao-Hong, Li, Wan-Ling, Zhou, Chang-Min, Gu, Wen-Jie, and Wang, Dan

Abstract

Tomato cultivars with contrasting resistance to pathogens regulate root exudates differentially in response to Ralstonia solanacearumattacks. However, strategies using innate root exudates against infection remain unknown. This study analyzed the innate root exudates of two tomato cultivars and their functions in regulating R. solanacearuminfection. The innate root exudates differed between the two cultivars. Astaxanthin released from resistant plants inhibited colonization by R. solanacearumbut promoted motility, while neferine released from susceptible plants suppressed motility and colonization. The secretion of astaxanthin in resistant tomatoes promoted the growth of biocontrol fungi in soil and reduced the abundance of pathogenic fungi. Neferine secreted by the susceptible cultivar inhibited the relative abundance of the bacterial-biocontrol-related Bacillusgenus, indirectly reducing the soil’s immune capacity. This study revealed contrasting strategies using root exudates in resistant and susceptible tomato cultivars to cope with R. solanacearuminfection, providing a basis for breeding disease-resistant cultivars.

Published
2023
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13. 5-Methylcytosine (m5C) Modification Patterns and Tumor Immune Infiltration Characteristics in Clear Cell Renal Cell Carcinoma.

Author

Chen, Can, Chen, Lin-Yuan, Zhang, Jie-Xin, and Xu, Hua-Guo

Subjects
METHYLCYTOSINE, RENAL cell carcinoma, CANCER prevention, CANCER treatment, PRINCIPAL components analysis
Abstract

Recently, studies have revealed the prognostic value of 5-methylcytosine (m5C) in clear cell renal cell carcinoma (ccRCC). However, the role of m5C methylation in ccRCC immune infiltration and the immunotherapeutic response remains unknown. Based on the mRNA expressions of 14 m5C regulators, we evaluated the m5C modification patterns of 530 tumor samples from the TCGA-ccRCC database. We used the principal component analysis (PCA) algorithm to construct individual patient m5Cscores to facilitate individual analysis of m5C modification patterns in ccRCC patients. We finally defined three different m5C modification patterns. Different clinical features and immune heterogeneity existed among the three patterns, and their immune infiltration characteristics could correspond to different immune phenotypes, including the immune-inflamed, immune-excluded, and immune-desert phenotype. We designed the m5Cscore calculated by the PCA algorithm to measure individual patients' m5C modification patterns. The low m5Cscore group presented with a positive prognosis, increased TMB, and immune activation. Additionally, low m5Cscore patients showed an increased response to immune checkpoint inhibitors. We further the value of the m5Cscore in predicting OS verified in four other tumor cohorts. Our findings revealed that m5C methylation modifications are essential in regulating ccRCC immune infiltration. Assessing single ccRCC patients' m5C modification patterns can fully improve our comprehension of tumor immune characteristics and be used to provide effective personalized immunotherapy strategies for clinical use. [ABSTRACT FROM AUTHOR]

Published
2023
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26. State-of-charge estimation based on Immune Evolutionary networks

Author

Cheng Bo, Lin Liqiao, Cao Binggang, Zhang Jie-xin, and Cao Houli

Subjects
Engineering, State of charge, Artificial neural network, business.industry, Control theory, Feedforward neural network, Algorithm design, business, Evolution strategy, Evolutionary computation, Second derivative, Premature convergence
Abstract

Based on Clonal Selection Theory, an adaptive Parallel Immune Evolutionary Strategy (PIES) is presented. Compared with conventional evolutionary strategy algorithm (CESA) and immune monoclonal strategy algorithm (IMSA), experimental results show that PIES is of high efficiency and can effectively prevent premature convergence. A three-layer feed-forward neural network is presented to predict state of charge (SOC) of Ni-MH batteries. Initially, partial least square regression (PLSR) is used to select input variables. Then, five variables, battery terminal voltage, voltage derivative, voltage second derivative, discharge current and battery temperature, are selected as the inputs of NN. In order to overcome the weakness of BP algorithm, PIES is adopted to train weights. Finally, under the state of dynamic power cycle, the predicted SOC and the actual SOC are compared to verify the proposed neural network with acceptable accuracy (5%).

Published
2009

27. Study on Multidisciplinary Collaborative Design Based on Regression Analysis

Author

Zhang Jie-xin and Zhu Bin

Subjects
Product design specification, Product design, Multidisciplinary approach, Computer science, Process (engineering), Product (mathematics), Regression analysis, Data mining, computer.software_genre, computer
Abstract

The development process of a complex product is often related to many different domains, such as mechanics, dynamics, and cybernetics, hydraulics, and usually in separate locations. While applying traditional design method to solve multidisciplinary design problems, frequently redesign may be taken place due to the fact that the inherent relations between parameters and product specifications can not be represented intuitively and quantitatively. This paper analyzes the mapping relationship between parameters and product specifications according to statistical theory. And by applying the idea of regression analysis, the method of supporting multidisciplinary collaborative design based on the regression relevant model is proposed, with which inherent relationship between parameters and product specifications can be represented quantitatively. Finally, the headstock of the grinding machine is taken as an example to validate the validity of the method.

Published
2009

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