5篇
您的检索式：作者名="Mei Shaohui"
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| 1 | A botanical medicine dragon’s blood exhibited clinical antithrombosis efficacy similar to low molecular weight heparin显示文摘Deep vein thrombosis(DVT)is a common complication following traumatic fracture with a 0.5%–1%annual incidence.Low molecular weight heparin(LMWH)is the most commonly used anticoagulation drug for DVT prevention,but treatment with LMWH is invasive.Our aim is to compare the antithrombotic effect of dragon’s blood,an oral botanical anticoagulant medicine approved by the Chinese FDA,with LMWH in patients undergoing hip fracture surgery and to explore the molecular mechanisms of anticoagulation treatment.Our study recruited patients and divided them into LMWH and dragon’s blood treatment group.Coagulation index tests,Doppler ultrasound and mRNA sequencing were performed before and after anticoagulation therapy.There was no significant difference in postoperative DVT incidence between the two groups(23.1%versus 15.4%,P=0.694).D-dimer(D-D)and fibrinogen degradation product(FDP)showed significant reductions in both groups after anticoagulation treatments.We identified SLC4A1,PROS1,PRKAR2B and seven other genes as being differentially expressed during anticoagulation therapy in both groups.Genes correlated with coagulation indexes were also identified.Dragon’s blood and LMWH showed similar effects on DVT and produced similar gene expression changes in patients undergoing hip fracture surgery,indicating that dragon’s blood is a more convenient antithrombosis medicine(oral)than LMWH(hypodermic injection). | Jiangbin Liang Song Mei Xiangyu Qiao Wei Pan Yan Zhao Shaohui Shi Yaling Zhai Haizhao Wen Guoping Wu Chengyu Jiang | 2021 | Science China(Life Sciences)2021，64，10： | 4 |
| 2 | Learning hyperspectral images from RGB images via a coarse-to-fine CNN显示文摘Hyperspectral remote sensing is well-known for its extraordinary spectral distinguishability to discriminate different materials.However,the cost of hyperspectral image(HSI)acquisition is much higher compared to traditional RGB imaging.In addition,spatial and temporal resolutions are sacrificed to obtain very high spectral resolution owing to the limitations of sensor technologies.Therefore,in this paper,HSIs are reconstructed using easily acquired RGB images and a convolutional neural network(CNN).As a result,high spatial and temporal resolution RGB images can be inherited to HSIs.Specifically,a two-stage CNN,referred to as the spectral super-resolution network(SSR-Net),is designed to learn the transformation model between RGB images and HSIs from training data,including a band prediction network(BP-Net)to estimate hyperspectral bands from RGB images and a refinement network(RF-Net)to further reduce spectral distortion in the band prediction step.As a result,the learned joint features in the proposed SSR-Net can directly predict HSIs from their corresponding scenes in RGB images without prior knowledge.Experimental results obtained on several benchmark datasets demonstrate that the proposed SSR-Net outperforms several state-of-the-art methods by ensuring higher quality in HSI reconstruction,and significantly improves the performance of traditional RGB images in classification. | Shaohui MEI Yunhao GENG Junhui HOU Qian DU | 2022 | Science China(Information Sciences)2022，65，5： | 3 |
| 3 | Spatial Purity Based Endmember Extraction for Spectral Mixture Analysis显示文摘 | MEI Shaohui HE Mingyi WANG Zhiyong | 2010 | IEEE Transaction on Geoscience and Remote Sensing2010，48，9： | 1 |
| 4 | Mixture Analysis by Multichannel Hopfield Neural Network显示文摘 | Mei Shaohui He Mingyi Wang Zhiyong Dagan Feng | 2010 | IEEE Geoscience and Remote Sensing Letters2010，7，3： | 1 |
| 5 | Optimizing Hopfield neural network for spectral mixture unmixing on GPU platform显示文摘 | Mei Shaohui He Mingyi Shen Zhiming | 2014 | IEEE Geoscience and Remote Sensing Letters2014，11，4： | 1 |
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