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Leveraging diverse cell-death patterns to predict the clinical outcome of immune checkpoint therapy in lung adenocarcinoma:Based on muti-omics analysis and vitro assay

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Oncology Research 2024年第2期32卷 393-407页

作者： HONGYUAN LIANG YANQIU LI YONGGANG QU lingyun zhang Department of Radiology Shengjing Hospital of China Medical UniversityShenyangChina Department of Nephrology The First Affiliated Hospital of China Medical UniversityShenyangChina Department of Clinical Medicine China Medical UniversityShenyangChina Department of Medical Oncology The First Hospital of China Medical UniversityShenyangChina

Advanced LUAD shows limited response to treatment including immune therapy.With the development of sequencing omics,it is urgent to combine high-throughput multi-omics data to identify new immune checkpoint therapeutic response markers.Using GSE72094(n=386)and GSE31210(n=226)gene expression profile data in the GEO database,we identified genes associated with lung adenocarcinoma(LUAD)death using tools such as“edgeR”and“maftools”and visualized the characteristics of these genes using the“circlize”R package.We constructed a prognostic model based on death-related genes and optimized the model using LASSO-Cox regression methods.By calculating the cell death index(CDI)of each individual,we divided LUAD patients into high and low CDI groups and examined the relationship between CDI and overall survival time by principal component analysis(PCA)and Kaplan-Meier analysis.We also used the“ConsensusClusterPlus”tool for unsupervised clustering of LUAD subtypes based on model genes.In addition,we collected data on the expression of immunomodulatory genes and model genes for each cohort and performed tumor microenvironment analyses.We also used the TIDE algorithm to predict immunotherapy responses in the CDI cohort.Finally,we studied the effect of PRKCD on the proliferation and migration of LUAD cells through cell culture experiments.The study utilized the TCGA-LUAD cohort(n=493)and identified 2,901 genes that are differentially expressed in patients with LUAD.Through KEGG and GO enrichment analysis,these genes were found to be involved in a wide range of biological pathways.The study also used univariate Cox regression models and LASSO regression analyses to identify 17 candidate genes that were best associated with mortality prognostic risk scores.By comparing the overall survival(OS)outcomes of patients with different CDI values,it was found that increased CDI levels were significantly associated with lower OS rates.In addition,the study used unsupervised cluster analysis to divide 115 LUAD patients into two distinct cluste

关键词： Lung adenocarcinoma Programmed cell death Iron-death Drug sensitivity Cancer therapy

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Emerging two-dimensional Mo-based materials for rechargeable metal-ion batteries:Advances and perspectives

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Journal of Energy Chemistry 2024年第2期89卷 487-518,I0012页

作者： Qingqing Ruan Yuehua Qian Mengda Xue lingyun Chen Qichun zhang Department of Applied Chemistry School of Chemistry and Chemical EngineeringChongqing UniversityChongqing 401331China Department of Materials Science and Engineering City University of Hong Kong999077Hong KongChina

With the rapid development of rechargeable metal-ion batteries(MIBs)with safety,stability and high energy density,significant efforts have been devoted to exploring high-performance electrode materials.In recent years,two-dimensional(2D)molybdenum-based(Mo-based)materials have drawn considerable attention due to their exceptional characteristics,including low cost,unique crystal structure,high theoretical capacity and controllable chemical compositions.However,like other transition metal compounds,Mo-based materials are facing thorny challenges to overcome,such as slow electron/ion transfer kinetics and substantial volume changes during the charge and discharge processes.In this review,we summarize the recent progress in developing emerging 2D Mo-based electrode materials for MIBs,encompassing oxides,sulfides,selenides,carbides.After introducing the crystal structure and common synthesis methods,this review sheds light on the charge storage mechanism of several 2D Mo-based materials by various advanced characterization techniques.The latest achievements in utilizing 2D Mo-based materials as electrode materials for various MIBs(including lithium-ion batteries(LIBs),sodium-ion batteries(SIBs)and zinc-ion batteries(ZIBs))are discussed in detail.Afterwards,the modulation strategies for enhancing the electrochemical performance of 2D Mo-based materials are highlighted,focusing on heteroatom doping,vacancies creation,composite coupling engineering and nanostructure design.Finally,we present the existing challenges and future research directions for 2D Mo-based materials to realize high-performance energy storage systems.

关键词： Molybdenum-based materials Two-dimensional materials Lithium-ion batteries Sodium-ion batteries Zinc-ion batteries

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Environmentally persistent free radicals in PM_(2.5)from a typical Chinese industrial city during COVID-19 lockdown:The unexpected contamination level variation

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Journal of Environmental Sciences 2024年第1期135卷 424-432页

作者： lingyun Wang Wuduo Zhao Peiru Luo Qingyun He Wenfen zhang Chuan Dong Yanhao zhang College of Chemistry Zhengzhou UniversityZhengzhou 450001China Center of Advanced Analysis and Gene Sequencing Key Laboratory of Molecular Sensing and Harmful Substances Detection TechnologyZhengzhou UniversityZhengzhou 450001China State Key Laboratory of Environmental and Biological Analysis Department of ChemistryHong Kong Baptist UniversityHong Kong 999077China Institute of Environmental Science Shanxi UniversityTaiyuan 030006China

The outbreak of COVID-19 has caused concerns globally.To reduce the rapid transmission of the virus,strict city lockdown measures were conducted in different regions.China is the country that takes the earliest home-based quarantine for people.Although normal industrial and social activities were suspended,the spread of virus was efficiently controlled.Simultaneously,another merit of the city lockdown measure was noticed,which is the improvement of the air quality.Contamination levels of multiple atmospheric pollutants were decreased.However,in this work,24 and 14 air fine particulate matter(PM_(2.5))samples were continuously collected before and during COVID-19 city lockdown in Linfen(a typical heavy industrial city in China),and intriguingly,the unreduced concentration was found for environmentally persistent free radicals(EPFRs)in PM_(2.5)after normal life suspension.The primary non-stopped coal combustion source and secondary Cu-related atmospheric reaction may have impacts on this phenomenon.The cigarette-based assessment model also indicated possible exposure risks of PM_(2.5)-bound EPFRs during lockdown of Linfen.This study revealed not all the contaminants in the atmosphere had an apparent concentration decrease during city lockdown,suggesting the pollutants with complicated sources and formation mechanisms,like EPFRs in PM_(2.5),still should not be ignored.

关键词： PM_(2.5) EPFRs COVID-19 City lockdown Health risks

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A motion characteristics modeled angular position sensor by nonlinear transfer of differential capacitance for miniaturized scanning mirrors

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Microsystems & Nanoengineering 2023年第6期9卷 129-147页

作者： Songtao Liu Gaofei zhang lingyun zhang Junya Wang Minghao Gong Zheng You Department of Precision Instrument Tsinghua UniversityBejing 100084China Key Laboratory of Smart Microsystem(Tsinghua University) Ministry of EducationBeijing 100084China State Key Laboratory of Precision Measurement Technology and Instruments Tsinghua UniversityBeijing 100084China School of Mechanical Science&Engineer Huazhong University of Science and TechnologyWuhan 430074China

In this paper,an angular position sensor(APS)designed for a resonant miniaturized scanning mirror(M-SM)is presented.The APS operates based on the principle of differential variable capacitance,significantly expanding the detectable bandwidth from a few hertz to several kilohertz.By modeling the motion characteristics,the sampling rates of the biaxial scanning angles are 1473.6 times and 539.4 times higher than those of conventional sensors.Initially,the motion characteristics model is presented as a simple harmonic motion,converting sampled capacitance into continuous capacitance.Subsequently,the nonparallel state of the M-SM and sensor is transformed into a parallel state through the space coordinate system transformation.Furthermore,a 2D nonlinear angle transfer function is developed to convert the differential capacitance into an angle,thereby mitigating the nonlinear errors resulting from large angles.Achieving an accuracy better than 0.014°,the measuring range expands from±0.5729°(±10 mrad)to±5.026°(±87 mrad).Additionally,the capturing mode and tracking mode are proposed to monitor real-time angular changes of the M-SM with an accuracy of 0.017°.High-precision APSs have enhanced beam pointing accuracy and resolution and can thereby be used to advance the development of laser components,including light detection and ranging(LiDAR).

关键词： capacitance angular nonlinear

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Recent advances in artificial intelligence generated content

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Frontiers of Information Technology & Electronic Engineering 2024年第1期25卷 1-5页

作者： Junping zhang lingyun SUN Cong JIN Junbin GAO Xiaobing LI Jiebo LUO Zhigeng PAN Ying TANG Jingdong WANG School of Computer Science Fudan UniversityShanghai 200433China International Design Institute Zhejiang UniversityHangzhou 310058China School of Information and Communication Engineering Communication University of ChinaBeijing 100024China The University of Sydney Business School The University of SydneyNSW 2006Australia Department of AI Music and Music Information Technology Central Conservatory of MusicBeijing 100032China Department of Computer Science University of RochesterNY 14627USA School of Artificial Intelligence Nanjing University of Information Science and TechnologyNanjing 210044China Electrical and Computer Engineering Department Rowan UniversityGlassboroNJ 08028USA Baidu Beijing 100085China

Artificial intelligence generated content(AIGC)has been a research hotspot in the field of artificial intelligence in recent years.It is expected to replace humans in performing some of the work of content generation at a low cost and a high volume,such as music,painting,multimodal content generation,news articles,summary reports,stock commentary summaries,and even content and digital people generated in the meta-universe.AIGC provides a new technical path for the development and implementation of AI in the future.

关键词： artificial replace content

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Green intelligent fertilizers——A novel approach for aligning sustainable agriculture with green development

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Frontiers of Agricultural Science and Engineering 2024年第1期11卷 186-196页

作者： Maoying WANG lingyun CHENG Chengdong HUANG Yang LYU Lin zhang Zhenya LU Changzhou WEI Wenqi MA Zed RENGEL Jianbo SHEN Fusuo zhang State Key Laboratory of Nutrient Use and Management College of Resources and Environmental SciencesNational Academy of Agriculture Green DevelopmentKey Laboratory of Plant–Soil Interactions(Ministry of Education)China Agricultural UniversityBeijing 100193China College of Agronomy Shihezi UniversityShihezi 832000China College of Resources and Environmental Science Hebei Agricultural UniversityBaoding 071000China Soil Science and Plant Nutrition UWA School of Agriculture and EnvironmentThe University of Western AustraliaPerthWA 6009Australia Institute for Adriatic Crops and Karst Reclamation Split 21000Croatia

This review addresses the growing disparity between the current state of fertilizer production in China and the evolving demands of green agriculture in the 21st century. It explores major advances in fertilizers, proposes the concept of green intelligent fertilizers and develops new strategies aligned with the principles of green development in fertilizer industry and agriculture.Green intelligent fertilizers may be designed to maximize the synergistic effects among plants, soils, microorganisms, nutrient sources and the environment. This concept emphasizes the integration of industry and agriculture toward green development for entire industry chain, using an interdisciplinary approach to drive the green transformation of fertilizer industry, and promote green and sustainable development of agriculture. By bridging the gap between the current state of fertilizer industry and a growing need for environmentally responsible agricultural practices, this review highlights a path toward harmonizing fertilizer production with the imperatives of green agriculture.

关键词： Root-nutrient feedback green development intelligent fertilizers new fertilizer plant-soil-fertilizer interaction rhizosphere engineering

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Construction and Application of a Regional Kilometer-Scale Carbon Source and Sink Assimilation Inversion System(CCMVS-R)

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Engineering 2024年第2期33卷 263-275页

作者： Lifeng Guo Xiaoye zhang Junting Zhong Deying Wang Changhong Miao Licheng Zhao Zijiang Zhou Jie Liao Bo Hu lingyun Zhu Yan Chen Monitoring and Assessment Center for GHGs and Carbon Neutrality&Key Laboratory of Atmospheric Chemistry of CMA Chinese Academy of Meteorological SciencesBeijing 100081China Laboratory of Climate Change Mitigation and Carbon Neutrality Henan UniversityZhengzhou 450001China National Meteorological Information Center Beijing 100081China Shanxi Meteorological Administration Taiyuan 030002China Shanxi Provincial Institute of Meteorological Sciences Taiyuan 030002China Jiangsu Provincial Climate Center Nanjing 210000China

CO_(2)is one of the most important greenhouse gases(GHGs)in the earth’s atmosphere.Since the industrial era,anthropogenic activities have emitted excessive quantities of GHGs into the atmosphere,resulting in climate warming since the 1950s and leading to an increased frequency of extreme weather and climate events.In 2020,China committed to striving for carbon neutrality by 2060.This commitment and China’s consequent actions will result in significant changes in global and regional anthropogenic carbon emissions and therefore require timely,comprehensive,and objective monitoring and verification support(MVS)systems.The MVS approach relies on the top-down assimilation and inversion of atmospheric CO_(2)concentrations,as recommended by the Intergovernmental Panel on Climate Change(IPCC)Inventory Guidelines in 2019.However,the regional high-resolution assimilation and inversion method is still in its initial stage of development.Here,we have constructed an inverse system for carbon sources and sinks at the kilometer level by coupling proper orthogonal decomposition(POD)with four-dimensional variational(4DVar)data assimilation based on the weather research and forecasting-greenhouse gas(WRF-GHG)model.Our China Carbon Monito ring and Verification Support at the Regional level(CCMVS-R)system can continuously assimilate information on atmospheric CO_(2)and other related information and realize the inversion of regional and local anthropogenic carbon emissions and natural terrestrial ecosystem carbon exchange.Atmospheric CO_(2)data were collected from six ground-based monito ring sites in Shanxi Province,China to verify the inversion effect of regio nal anthropogenic carbon emissions by setting ideal and real experiments using a two-layer nesting method(at 27 and 9 km).The uncertainty of the simulated atmospheric CO_(2)decreased significantly,with a root-mean-square error of CO_(2)concentration values between the ideal value and the simulated after assimilation was close to 0.The total anthropogenic carbon emissions in S

关键词： CCMVS-R Regional carbon assimilation system Anthropogenic carbon emissions CO_(2) POD 4DVar

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Engineered Fabrication of Enamel-Mimetic Materials

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Engineering 2022年第7期8卷 113-123页

作者： lingyun zhang Yunfan zhang Tingting Yu Liying Peng Qiannan Sun Bing Han Department of Orthodontics Peking University School and Hospital of Stomatology&National Engineering Laboratory for Digital and Material Technology of Stomatology&Beijing Key Laboratory of Digital StomatologyBeijing 100081China

Tooth enamel,which is a biological tissue mainly composed of well-aligned hydroxyapatite nanocrystals and an interlaced protein matrix,has remarkable mechanical and aesthetic behaviors.Nevertheless,it is challenging to regenerate enamel naturally,and potential pulp involvement and tooth loss may occur.As the hardest biogenic composite material,enamel has long been regarded as a promising load-bearing material.Thus,understanding the enamel formation process and enamel structural motif mechanisms is important for the design and engineering of high-performance biomimetic composites with high strength and physical resilience.Extensive studies have been conducted on mimicking the microstructure and mechanical properties of tooth enamel,and various enamel-like material synthesis protocols have been developed.In light of the engineering fabrication of enamel-like materials,this review focuses on recent progress in synthetic strategies for enamel-mimetic materials and provides a discussion of the potential applications of these materials.

关键词： Regeneration Remineralization Abiotic enamel Biomimetic

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Automatic detection of breast lesions in automated 3D breast ultrasound with cross-organ transfer learning

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虚拟现实与智能硬件（中英文） 2024年第3期6卷 239-251页

作者： lingyun BAO Zhengrui HUANG Zehui LIN Yue SUN Hui CHEN You LI zhang LI Xiaochen YUAN Lin XU Tao TAN Affiliated Hangzhou First People's Hospital School of MedicineWestlake UniversityHangzhou 330100China Faculty of Applied Sciences Macao Polytechnic UniversityMacao 999078China Pathology Department Changsha First HospitalChangsha 410073China Radiology Department Changsha First HospitalChangsha 410073China College of Aerospace Science and Engineering National University of Defense TechnologyChangsha 410073China Hunan Provincial Key Laboratory of Image Measurement and Vision Navigation Changsha 410073China School of Information Science and Technology Shanghaitech UniversityShanghai 201210China

Background Deep convolutional neural networks have garnered considerable attention in numerous machine learning applications,particularly in visual recognition tasks such as image and video analyses.There is a growing interest in applying this technology to diverse applications in medical image analysis.Automated three dimensional Breast Ultrasound is a vital tool for detecting breast cancer,and computer-assisted diagnosis software,developed based on deep learning,can effectively assist radiologists in diagnosis.However,the network model is prone to overfitting during training,owing to challenges such as insufficient training data.This study attempts to solve the problem caused by small datasets and improve model detection performance.Methods We propose a breast cancer detection framework based on deep learning(a transfer learning method based on cross-organ cancer detection)and a contrastive learning method based on breast imaging reporting and data systems(BI-RADS).Results When using cross organ transfer learning and BIRADS based contrastive learning,the average sensitivity of the model increased by a maximum of 16.05%.Conclusion Our experiments have demonstrated that the parameters and experiences of cross-organ cancer detection can be mutually referenced,and contrastive learning method based on BI-RADS can improve the detection performance of the model.

关键词： Breast ultrasound Automated 3D breast ultrasound Breast cancers Deep learning Transfer learning Convolutional neural networks Computer-aided diagnosis Cross organ learning

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The interaction between KIF21A and KANK1 regulates dendritic morphology and synapse plasticity in neurons

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Neural Regeneration Research 2025年第1期20卷 209-223页

作者： Shi-Yan Sun lingyun Nie Jing zhang Xue Fang Hongmei Luo Chuanhai Fu Zhiyi Wei Ai-Hui Tang Hefei National Research Center for Physical Sciences at the Microscale CAS Key Laboratory of Brain Function and DiseaseMinistry of Education Key Laboratory for Membrane-less Organelles and Cellular DynamicsDivision of Life Sciences and MedicineUniversity of Science and Technology of ChinaHefeiAnhui ProvinceChina Institute of Artificial Intelligence Hefei Comprehensive National Science CenterHefeiAnhui ProvinceChina CAS Center for Excellence in Molecular Cell Sciences Division of Life Sciences and MedicineUniversity of Science and Technology of ChinaHefeiAnhui ProvinceChina Department of Neurobiology School of Life SciencesSouthern University of Science and TechnologyShenzhenGuangdong ProvinceChina Brain Research Center Southern University of Science and TechnologyShenzhenGuangdong ProvinceChina

Morphological alterations in dendritic spines have been linked to changes in functional communication between neurons that affect learning and memory.Kinesin-4 KIF21A helps organize the microtubule-actin network at the cell cortex by interacting with KANK1;however,whether KIF21A modulates dendritic structure and function in neurons remains unknown.In this study,we found that KIF21A was distributed in a subset of dendritic spines,and that these KIF21A-positive spines were larger and more structurally plastic than KIF21A-negative spines.Furthermore,the interaction between KIF21A and KANK1 was found to be critical for dendritic spine morphogenesis and synaptic plasticity.Knockdown of either KIF21A or KANK1 inhibited dendritic spine morphogenesis and dendritic branching,and these deficits were fully rescued by coexpressing full-length KIF21A or KANK1,but not by proteins with mutations disrupting direct binding between KIF21A and KANK1 or binding between KANK1 and talin1.Knocking down KIF21A in the hippocampus of rats inhibited the amplitudes of long-term potentiation induced by high-frequency stimulation and negatively impacted the animals’cognitive abilities.Taken together,our findings demonstrate the function of KIF21A in modulating spine morphology and provide insight into its role in synaptic function.

关键词： actin cytoskeleton dendrite KANK1 KIF21A microtubule spine morphology spine synaptic plasticity talin1

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