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Mixed-decomposed convolutional network:A lightweight yet efficient convolutional neural network for ocular disease recognition
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作者 Xiaoqing Zhang Xiao Wu +5 位作者 Zunjie Xiao Lingxi Hu Zhongxi Qiu qingyang sun Risa Higashita Jiang Liu 《CAAI Transactions on Intelligence Technology》 SCIE EI 2024年第2期319-332,共14页
Eye health has become a global health concern and attracted broad attention.Over the years,researchers have proposed many state-of-the-art convolutional neural networks(CNNs)to assist ophthalmologists in diagnosing oc... Eye health has become a global health concern and attracted broad attention.Over the years,researchers have proposed many state-of-the-art convolutional neural networks(CNNs)to assist ophthalmologists in diagnosing ocular diseases efficiently and precisely.However,most existing methods were dedicated to constructing sophisticated CNNs,inevitably ignoring the trade-off between performance and model complexity.To alleviate this paradox,this paper proposes a lightweight yet efficient network architecture,mixeddecomposed convolutional network(MDNet),to recognise ocular diseases.In MDNet,we introduce a novel mixed-decomposed depthwise convolution method,which takes advantage of depthwise convolution and depthwise dilated convolution operations to capture low-resolution and high-resolution patterns by using fewer computations and fewer parameters.We conduct extensive experiments on the clinical anterior segment optical coherence tomography(AS-OCT),LAG,University of California San Diego,and CIFAR-100 datasets.The results show our MDNet achieves a better trade-off between the performance and model complexity than efficient CNNs including MobileNets and MixNets.Specifically,our MDNet outperforms MobileNets by 2.5%of accuracy by using 22%fewer parameters and 30%fewer computations on the AS-OCT dataset. 展开更多
关键词 artificial intelligence deep learning deep neural networks image analysis image classification medical applications medical image processing
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KHK-A promotes fructose-dependent colorectal cancer liver metastasis by facilitating the phosphorylation and translocation of PKM2
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作者 Chaofan Peng Peng Yang +7 位作者 Dongsheng Zhang Chi Jin Wen Peng Tuo Wang qingyang sun Zhihao Chen Yifei Feng Yueming sun 《Acta Pharmaceutica Sinica B》 SCIE CAS CSCD 2024年第7期2959-2976,共18页
Excessive fructose diet is closely associated with colorectal cancer(CRC)progression.Nevertheless,fructose’s specific function and precise mechanism in colorectal cancer liver metastasis(CRLM)is rarely known.Here,thi... Excessive fructose diet is closely associated with colorectal cancer(CRC)progression.Nevertheless,fructose’s specific function and precise mechanism in colorectal cancer liver metastasis(CRLM)is rarely known.Here,this study reported that the fructose absorbed by primary colorectal cancer could accelerate CRLM,and the expression of KHK-A,not KHK-C,in liver metastasis was higher than in paired primary tumors.Furthermore,KHK-A facilitated fructose-dependent CRLM in vitro and in vivo by phosphorylating PKM2 at Ser37.PKM2 phosphorylated by KHK-A inhibited its tetramer formation and pyruvic acid kinase activity but promoted the nuclear accumulation of PKM2.EMT and aerobic glycolysis activated by nuclear PKM2 enhance CRC cells’migration ability and anoikis resistance during CRLM progression.TEPP-46 treatment,targeting the phosphorylation of PKM2,inhibited the pro-metastatic effect of KHK-A.Besides,c-myc activated by nuclear PKM2 promotes alternative splicing of KHK-A,forming a positive feedback loop. 展开更多
关键词 CRC CRLM FRUCTOSE KHK-A PKM2
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