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Refining biome labeling for large-scale microbial community samples:Leveraging neural networks and transfer learning

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Environmental Science and Ecotechnology 2024年第1期17卷 128-137页

作者： Nan Wang Teng Wang kang Ning Key Laboratory of Molecular Biophysics of the Ministry of Education Hubei Key Laboratory of Bioinformatics and Molecular-imagingCenter of AI BiologyDepartment of Bioinformatics and Systems BiologyCollege of Life Science and TechnologyHuazhong University of Science and TechnologyWuhan430074HubeiChina

Microbiome research has generated an extensive amount of data,resulting in a wealth of publicly accessible *** annotation of these samples is crucial for effectively utilizing microbiome data across scientific ***,a notable challenge arises from the lack of essential annotations,particularly regarding collection location and sample biome information,which significantly hinders environmental microbiome *** this study,we introduce Meta-Sorter,a novel approach utilizing neural networks and transfer learning,to enhance biome labeling for thousands of microbiome samples in the MGnify database that have incomplete *** findings demonstrate that Meta-Sorter achieved a remarkable accuracy rate of 96.7%in classifying samples among the 16,507 lacking detailed biome ***,Meta-Sorter provides precise classifications for representative environmental samples that were previously ambiguously labeled as“Marine”in MGnify,thereby elucidating their specific origins in benthic and water column ***,Meta-Sorter effectively distinguishes samples derived from human-environment interactions,enabling clear differentiation between environmental and human-related *** improving the completeness of biome label information for numerous microbial community samples,our research facilitates more accurate knowledge discovery across diverse disciplines,with particular implications for environmental research.

关键词： Microbial community Transfer learning Sample classification Environmental scientific research Novel knowledge discovery

Lecithin-cholesterol acyltransferase is a potential tumor suppressor and predictive marker for hepatocellular carcinoma metastasis

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World Journal of Gastrointestinal Oncology 2024年第8期16卷 3651-3671页

作者： Yan Li Li-Na Jiang Bo-kang Zhao Mei-Ling Li Yi-Yun Jiang Yi-Si Liu Shu-hong Liu Li Zhu Xin Ye Jing-Min Zhao Department of Pathology and Hepatology The Fifth Medical Center of Chinese PLA General HospitalBeijing 100039China Department of Hepatology Center of Infectious Diseases and Pathogen BiologyThe First Hospital of Jilin UniversityChangchun 130061Jilin ProvinceChina First Department of Liver Disease Center Beijing Youan HospitalCapital Medical UniversityBeijing 100069China Key Laboratory of Pathogenic Microbiology and Immunology Institute of MicrobiologyChinese Academy of SciencesBeijing 100101China Savaid Medical School University of Chinese Academy of SciencesBeijing 100190China Department of Pathology The Fifth Medical Center of Chinese PLA General HospitalBeijing 100039China

BACKGROUND Hepatocellular carcinoma(HCC)is a major cause of cancer mortality worldwide,and metastasis is the main cause of early recurrence and poor ***,the mechanism of metastasis remains poorly *** To determine the possible mechanism affecting HCC metastasis and provide a possible theoretical basis for HCC *** The candidate molecule lecithin-cholesterol acyltransferase(LCAT)was screened by gene microarray and bioinformatics *** expression levels of LCAT in clinical cohort samples was detected by quantitative realtime polymerase chain reaction and western *** proliferation,migration,invasion and tumor-forming ability were measured by Cell Counting Kit-8,Transwell cell migration,invasion,and clonal formation assays,*** formation was detected in nude mice after LCAT gene knockdown or *** immunohistochemistry for Ki67,E-cadherin,N-cadherin,matrix metalloproteinase 9 and vascular endothelial growth factor were performed in liver tissues to assess the effect of LCAT on *** set enrichment analysis(GSEA)on various gene signatures were analyzed with GSEA version *** machine-learning algorithms(random forest,support vector machine,and logistic regression)were applied to predict HCC metastasis in The Cancer Genome Atlas and GEO *** LCAT was identified as a novel gene relating to HCC metastasis by using gene microarray in HCC *** was significantly downregulated in HCC tissues,which is correlated with recurrence,metastasis and poor outcome of HCC *** analysis indicated that LCAT inhibited HCC cell proliferation,migration and invasion both in vitro and in *** data showed that LCAT was negatively associated with HCC size and metastasis(HCC size≤3 cm vs 3-9 cm,P9 cm,P<0.01;metastatic-free HCC vs extrahepatic metastatic HCC,P<0.05).LCAT suppressed the growth,migration and invasion of HCC cell lines via PI3K/A

关键词： Lecithin-cholesterol acyltransferase Tumor suppressor gene Hepatocellular carcinoma PI3K/AKT/mTOR Predicting model

Liver transplantation following two conversions in a patient with huge hepatocellular carcinoma and portal vein invasion:A case report

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World Journal of Gastroenterology 2024年第36期30卷 4071-4077页

作者： Li-Cong Liang Wen-Sou Huang Zhao-Xiong Guo hong-Ji You Yong-Jian Guo Ming-Yue Cai Li-Teng Lin Guo-Ying Wang kang-Shun Zhu Department of Minimally Invasive Interventional Radiology The Second Affiliated Hospital of Guangzhou Medical UniversityGuangzhou 510260Guangdong ProvinceChina Department of Nuclear Medicine The Second Affiliated Hospital of Guangzhou Medical UniversityGuangzhou 510260Guangdong ProvinceChina Department of Hepatobiliary Surgery The First Affiliated Hospital of Guangzhou Medical UniversityGuangzhou 510120Guangdong ProvinceChina

BACKGROUND Surgical resection and liver transplantation(LT)are the most effective curative options for hepatocellular carcinoma(HCC).However,few patients with huge HCC(>10 cm in diameter),especially those with portal vein tumor thrombus(PVTT),can receive these *** internal radiation therapy(SIRT)can be used as a conversion therapy for them because it has the dual benefit of shrinking tumors and increasing residual hepatic ***,in patients with huge HCC,high lung absorbed dose often prevents them from receiving *** SUMMARY A 35-year-old man was admitted because of emaciation and pain in the hepatic region for about 1 *** computed tomography scan showed a 20.2 cm×19.8 cm tumor located in the right lobe–left medial lobes with right portal vein and right hepatic vein *** the pathological type of HCC was confirmed by biopsy,two conversions were *** first one was drug-eluting bead transarterial chemoembolization plus hepatic arterial infusion chemotherapy and lenvatinib and sintilimab,converted to SIRT,and the second one was sequential SIRT with continued systemic *** tumor size significantly decreased from 20.2 cm×19.8 cm to 16.2 cm×13.8 cm,then sequentially to 7.8 cm×6.8 *** the meantime,the ratio of spared volume to total liver volume increased gradually from 34.4%to 55.7%,then to 62.9%.Furthermore,there was visualization of the portal vein,indicating regression of the tumor ***,owing to the new tumor in the left lateral lobe,the patient underwent LT instead of resection without major *** Patients with inoperable huge HCC with PVTT could be converted to SIRT first and accept surgery sequentially.

关键词： Hepatocellular carcinoma Two conversions Liver transplantation Yttrium-90 resin microspheres Transarterial chemoembolization Hepatic arterial infusion chemotherapy Case report

A Hybrid Level Set Optimization Design Method of Functionally Graded Cellular Structures Considering Connectivity

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Computers, Materials & Continua 2024年第4期79卷 1-18页

作者： Yan Dong kang Zhao Liang Gao Hao Li The State Key Lab of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan430074China Institute of Systems Engineering China Academy of Engineering PhysicsMianyang621900China

With the continuous advancement in topology optimization and additive manufacturing(AM)technology,the capability to fabricate functionally graded materials and intricate cellular structures with spatially varying microstructures has grown ***,a critical challenge is encountered in the design of these structures–the absence of robust interface connections between adjacent microstructures,potentially resulting in diminished efficiency or macroscopic failure.A Hybrid Level Set Method(HLSM)is proposed,specifically designed to enhance connectivity among non-uniform microstructures,contributing to the design of functionally graded cellular *** HLSM introduces a pioneering algorithm for effectively blending heterogeneous microstructure ***,an interpolation algorithm is presented to construct transition microstructures seamlessly connected on both ***,the algorithm enables the morphing of non-uniform unit cells to seamlessly adapt to interconnected adjacent *** method,seamlessly integrated into a multi-scale topology optimization framework using the level set method,exhibits its efficacy through numerical examples,showcasing its prowess in optimizing 2D and 3D functionally graded materials(FGM)and multi-scale topology *** essence,the pressing issue of interface connections in complex structure design is not only addressed but also a robust methodology is introduced,substantiated by numerical evidence,advancing optimization capabilities in the realm of functionally graded materials and cellular structures.

关键词： Hybrid level set method functionally graded cellular structure connectivity interpolated transition optimization design

Biotic and abiotic stresses on honeybee health

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Integrative Zoology 2024年第3期19卷 442-457页

作者： Zheguang LIN Siyi SHEN kang WANG Ting JI Apicultural Research Institute College of Animal Science and TechnologyYangzhou UniversityYangzhouChina

Honeybees are the most critical pollinators providing key ecosystem services that underpin crop production and sustainable *** a backdrop of rapid global change,this eusocial insect encounters a succession of stressors during nesting,foraging,and *** mites,together with vectored viruses,have been recognized as central biotic threats to honeybee health,while the spread of invasive giant hornets and small hive beetles also increasingly threatens colonies *** of agrochemicals,including acaricides used for mite treatment,and other pollutants of the environment have been widely documented to affect bee health in various ***,expanding urbanization,climate change,and agricultural intensification often result in the destruction or fragmentation of flower-rich bee *** anthropogenic pressures exerted by beekeeping management practices affect the natural selection and evolution of honeybees,and colony translocations facilitate alien species invasion and disease *** this review,the multiple biotic and abiotic threats and their interactions that potentially undermine bee colony health are discussed,while taking into consideration the sensitivity,large foraging area,dense network among related nestmates,and social behaviors of honeybees.

关键词： abiotic stressor Apis biotic stressor colony losses interaction effect pollinator decline

Physics-informed deep Koopman operator for Lagrangian dynamic systems

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Science China(Information Sciences) 2024年第9期67卷 146-163页

作者： Xuefeng WANG Yang CAO Shaofeng CHEN Yu kang Department of Automation University of Science and Technology of China State Key Laboratory of Fire Science University of Science and Technology of China Institute of Advanced Technology University of Science and Technology of China

Accurate mechanical system models are crucial for safe and stable control. Unlike linear systems,Lagrangian systems are highly nonlinear and difficult to optimize because of their unknown system *** research thus used deep neural networks to generate linear models of original systems by mapping nonlinear dynamic systems into a linear space with a Koopman observable function encoder. The controller then relies on the Koopman linear model. However, without physical information constraints, ensuring control consistency between the original nonlinear system and the Koopman system is tough, as the learning process of the Koopman observation function is unsupervised. This paper thus proposes a two-stage learning algorithm that uses structural subnetworks to build a physics-informed network topology to simultaneously learn the Koopman observable functions and the system energy representation. In the Koopman matrix learning session, a quadratic-constrained optimization problem is solved to ensure that the Koopman representation satisfies the energy difference matching hard constraint. The proposed energy-preserving deep Lagrangian Koopman(EPDLK) framework effectively represents the dynamics of the Lagrangian system while ensuring control consistency. The effectiveness of EPDLK is compared with those of various Koopman observable function construction methods in multistep prediction and trajectory tracking tasks. EPDLK achieves better control consistency by guaranteeing energy difference matching, which facilitates the application of the control law generated on the Koopman system directly to the original nonlinear Lagrangian system.

关键词： Koopman operator Lagrangian physics-informed nonlinear model predictive control (MPC)

Deep Global Multiple-Scale and Local Patches Attention Dual-Branch Network for Pose-Invariant Facial Expression Recognition

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 405-440页

作者： Chaoji Liu Xingqiao Liu Chong Chen kang Zhou School of Electrical and Information Engineering Jiangsu UniversityZhenjiang212013China School of Electrical Engineering Yancheng Institute of TechnologyYancheng224051China

Pose-invariant facial expression recognition(FER)is an active but challenging research topic in computer *** with the involvement of diverse observation angles,FER makes the training parameter models inconsistent from one view to *** study develops a deep global multiple-scale and local patches attention(GMS-LPA)dual-branch network for pose-invariant FER to weaken the influence of pose variation and selfocclusion on recognition *** this research,the designed GMS-LPA network contains four main parts,i.e.,the feature extraction module,the global multiple-scale(GMS)module,the local patches attention(LPA)module,and the model-level fusion *** feature extraction module is designed to extract and normalize texture information to the same *** GMS model can extract deep global features with different receptive fields,releasing the sensitivity of deeper convolution layers to pose-variant and *** LPA module is built to force the network to focus on local salient features,which can lower the effect of pose variation and self-occlusion on recognition ***,the extracted features are fused with a model-level strategy to improve recognition *** experimentswere conducted on four public databases,and the recognition results demonstrated the feasibility and validity of the proposed methods.

关键词： Pose-invariant FER global multiple-scale(GMS) local patches attention(LPA) model-level fusion

Experimental investigation on fluid-induced slip behavior of fault filled with fault gouge

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第9期16卷 3661-3672页

作者： Yongshui kang Zhi Geng Bin Liu Youqi Huang State Key Laboratory of Geomechanics and Geotechnical Engineering Institute of Rock and Soil MechanicsChinese Academy of SciencesWuhan430071China University of Chinese Academy of Sciences Beijing100049China

Fault zones are usually filled with fault gouge and accompanied by fault *** coupled effect of fault gouge and water significantly impacts the slip behavior of the fault,which may weaken the fault structure and further induce rupture propagation and *** this study,we carried out a laboratory experiment to investigate the fluid-induced slip behavior of fault filled with *** friction evolution characteristic associated with fluid pressure and effective stress was investigated during the slip *** addition,the role transformation process of the gouge on the slip behavior of fault was *** experimental result indicates that the friction on the filled fault surface is significantly affected by fault *** rupture of the gouge promotes fault slip and the fluid pressure plays a vital role in the initiation of fault *** fault gouge enhances the shearing strength of the fault and acts as a barrier before the initial slip under fluid ***,the fault gouge would accelerate the fault slip and transform into lubricant after the initial slip.

关键词： Fault gouge Fluid Slip behavior Friction Shear strength

Autonomous multi-drone racing method based on deep reinforcement learning

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Science China(Information Sciences) 2024年第8期67卷 35-48页

作者： Yu kang Jian DI Ming LI Yunbo ZHAO Yuhui WANG Department of Automation University of Science and Technology of China Institute of Advanced Technology University of Science and Technology of China Institute of Artificial Intelligence Hefei Comprehensive National Science Center College of Automation Engineering Nanjing University of Aeronautics and Astronautics

Racing drones have attracted increasing attention due to their remarkable high speed and excellent maneuverability. However, autonomous multi-drone racing is quite difficult since it requires quick and agile flight in intricate surroundings and rich drone interaction. To address these issues, we propose a novel autonomous multi-drone racing method based on deep reinforcement learning. A new set of reward functions is proposed to make racing drones learn the racing skills of human experts. Unlike previous methods that required global information about tracks and track boundary constraints, the proposed method requires only limited localized track information within the range of its own onboard sensors. Further, the dynamic response characteristics of racing drones are incorporated into the training environment, so that the proposed method is more in line with the requirements of real drone racing scenarios. In addition, our method has a low computational cost and can meet the requirements of real-time racing. Finally, the effectiveness and superiority of the proposed method are verified by extensive comparison with the state-of-the-art methods in a series of simulations and real-world experiments.

关键词： racing drone autonomous multi-drone racing sim-to-real deep reinforcement learning Markov game