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您的检索式：作者名="LIN Shaodan"
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| 1 | Comparison of KRAS/BRAF mutations between primary tumors and serum incolorectal cancer: Biological and clinical implications显示文摘 | Xingxiang Pu Zhizhong Pan Ying Huang Ying Tian Hongqiang Guo Lin Wu Xuexing He Xinggui Chen Shaodan Zhang Tongyu Lin | 2013 | Oncology Letters2013，，1： | 1 |
| 2 | Target prediction and activity verification for the antidepressant action of Huangqin(Radix Scutellariae Baicalensis)显示文摘OBJECTIVE:To decipher the antidepressant targets and mechanisms of Huangqin(Radix Scutellariae Baicalensis)(RSB)by a novel computational system based on prediction and experimental verification.METHODS:The putative targets of RSB against depression were identified from Traditional Chinese Medicine Systems Pharmacology(TCMSP)and Drug Bank.Next,protein-protein interaction network of the anti-depression targets of RSB were identified,and differentially expressed genes(DEGs)of depression were mined from the NCBI database.Then,Kyoto Encyclopedia of Genes and Genomes and Gene Ontology were used to analysis the common targets.Finally,the selected pathways and functions were verified by experimentation.RESULTS:Thirty active compounds in RSB were predicted with high confidence by TCMSP and DrugBank,and seventy-one DEGs were identified in the GEO database.Besides,eight core target proteins were screened out by descending order of degree value,including ACHE,IL6,SLC6A4,FOS,SLC6A3,MAOB,DPP4,and JUN.These target genes were further found to be associated with pathways involved in neuronal apoptosis,such as pathways in cancer,Toll-like receptor signaling pathway,and TNF signaling.The cell proliferation assay and wound-healing assay results showed that RSB does not affect PC12 cell proliferation and chemotaxis.Unexpectedly,RSB protected PC12 cells from oxidative stress induced by H2O2 via inhibiting autophagy and apoptosis.We revealed significant changes in mice treated with 400 mg/kg RSB compared with the lipopolysaccharide mice.The possible mechanism for the antidepressive action of RSB is by reducing the expression of LC3-B in CA1 neurons.CONCLUSIONS:Our research partially expounds the mechanism of the antidepressant effect of RSB by the combination of network pharmacology prediction and experimental verification.Furthermore,it is also conducive to the application of Traditional Chinese Medicine within modern medicine. | LI Ganggang LU Ye HE Pei ZHANG Shiyue CHENG Yating ZHANG Shaodan PEI Lin | 2021 | Journal of Traditional Chinese Medicine2021，41，6： | 0 |
| 3 | Application of UAV-Based Imaging and Deep Learning in Assessment of Rice Blast Resistance显示文摘Rice blast is regarded as one of the major diseases of rice.Screening rice genotypes with high resistance to rice blast is a key strategy for ensuring global food security.Unmanned aerial vehicles(UAV)-based imaging,coupled with deep learning,can acquire high-throughput imagery related to rice blast infection.In this study,we developed a segmented detection model(called RiceblastSegMask)for rice blast detection and resistance evaluation.The feasibility of different backbones and target detection models was further investigated.RiceblastSegMask is a two-stage instance segmentation model,comprising an image-denoising backbone network,a feature pyramid,a trinomial tree fine-grained feature extraction combination network,and an image pixel codec module.The results showed that the model combining the image-denoising and fine-grained feature extraction based on the Swin Transformer and the feature pixel matching feature labels with the trinomial tree recursive algorithm performed the best.The overall accuracy for instance segmentation of RiceblastSegMask reached 97.56%,and it demonstrated a satisfactory accuracy of 90.29%for grading unique resistance to rice blast.These results indicated that low-altitude remote sensing using UAV,in conjunction with the proposed RiceblastSegMask model,can efficiently calculate the extent of rice blast infection,offering a new phenotypic tool for evaluating rice blast resistance on a field scale in rice breeding programs. | LIN Shaodan YAO Yue LI Jiayi LI Xiaobin MA Jie WENG Haiyong CHENG Zuxin YE Dapeng | 2023 | Rice science2023，30，6： | 0 |
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