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您的检索式：作者名="Ruixuan Pan"
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| 1 | Digital Gene Expression Analysis of Huanglongbing Affected Mandarins(Citrus reticulata Blanco)In Response to Thermotherapy显示文摘Huanglongbing(HLB),which is mainly associated with“Candidatus Liberibacter asiaticus”(CLas),is currently threatening citrus production around the world.This destructive century-old disease results in callose deposition in phloem plasmodesmata and starch overaccumulation in leaf chloroplasts.Heat treatment with high humidity has proven to be effective in eliminating the CLas titers in potted citrus trees.This study explored the curative mechanisms and impact of heat treatment(from 32 to 48°C with 75%±5%relative humidity,14h in light and 10h in dark for four days)on mandarin trees(Citrus reticulata Blanco)that were severely infected by CLas using Solexa/Illumina’s digital gene expression(DGE)profiling.A total of 838 differentially expressed genes(DEGs)were identified,of which 510 were downregulated.Proteinprotein interaction analysis of the DEGs indicated that the thermotherapy of HLB trees downregulated the circadian clock related genes in chloroplasts and upregulated the RNA-editing process in the mitochondria,characterized by 141 genes encoding pentatricopeptide repeatcontaining proteins(PPR)being all upregulated.Furthermore,the expression of phenylpropanoid and flavonoid biosynthesis genes,and auxininduced genes were suppressed.The defense response pathway of the thermotherapy treated diseased trees was apparently disrupted,as indicated by the downregulation of LRR receptor-like serine/threonine-protein kinase FLS2 gene.This study improves our understanding of the curative mechanisms of heat treatment on HLB trees and CLas biological regulation.Importantly,this provides new insights on the involvement of RNA modification by PPR genes and changes in the circadian clock after the heat stress treatment of CLas-infected citrus. | Ruixuan Pan Yanling Chen Xiaoling Deng Meirong Xu | 2021 | Horticultural Plant Journal2021，7，1： | 2 |
| 2 | Research on the improvement of the LaneGCN trajectory prediction algorithm显示文摘The LaneGCN proposed by Uber has achieved good performance in trajectory prediction, but it has shortcomings in capturing longrange information, expressing road information and modelling the strong and weak relationships of interaction between actors. Inthis paper, the LaneGCN is improved from three parts. Firstly, multi-scale long short-term memory is introduced to encode multiscaletrajectory information. Secondly, relative distance information is added to enhance the spatial expressive capacity of themodelin the process of road information encoding. Finally, we build a weighted interaction model based on Graph Attention Networksin the process of road information encoding. In order to verify the performance of the improved model, ablation and comparisonexperiments are designed in this paper. The results showed that all the evaluation metrics are lower than the LaneGCN and theoverall performance of the model is improved. | Bing Zhou Junjun Zou Xiaojian Wu Tian Chai Renjie Zhou Qianxi Pan Ruixuan Zhou | 2022 | Transportation Safety and Environment2022，4，4： | 0 |
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