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Dysregulated RUNX1 Predicts Poor Prognosis by Mediating Epithelialmesenchymal Transition in Cervical Cancer

Current Medical Science 2022年第6期42卷 1285-1296页

作者： Ling-ling ZHENG Lei CAI Xiao-qing ZHANG Zhe LEI Chang-sheng YI xing-dang liu Ji-gang YANG Department of Nuclear Medicine Beijing Friendship HospitalCapital Medical UniversityBeijing100050China Department of Nuclear Medicine Huashan HospitalFudan UniversityShanghai200040China Reproductive Medicine Center Tongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan430030China Department of Thoracic Surgery the Affiliated Cancer Hospital of Zhengzhou UniversityHenan Cancer HospitalZhengzhou450003China

Objective Runt-related transcription factor 1(RUNX1)has been proven to be over-expressed and vital in many ***,its role in cervical cancer is still *** Some online databases(Oncomine,GEPIA,UALCAN,LinkedOmics,and others)were used to explore the expression level,prognostic significance,and gene mutation characteristics of RUNX1 in cervical *** protein levels of RUNX1 in cervical cancer were measured by immunohistochemistry(IHC).The functional changes of cervical cancer cells were measured in vitro after decreasing *** Bioinformatic results revealed that RUNX1 was upregulated in cervical cancer compared to normal ***,over-expression of RUNX1 was significantly correlated with cervical cancer patients’clinical parameters(e.g.,individual cancer stages,patients’age,nodal metastasis status,and others).Meanwhile,functional enrichment analysis of RUNX1-related genes indicated that RUNX1 was mainly involved in the epithelial-mesenchymal transition(EMT)process in cervical ***,RUNX1 may be upregulated by hsamiR-616-5p and hsa-miR-766 identified by miRDB,TargetScan,and ***,RUNX1 was upregulated in cervical cancer compared to normal tissues by IHC in collected cervical cancer *** invasion and migration abilities of cervical cancer cells were significantly reduced by repressing EMT after knocking down RUNX1 in *** RUNX1 was highly expressed in cervical cancer,and upregulated RUNX1 could significantly promote the invasive abilities of cervical cancer cells by inducing ***,RUNX1 may be a potential biomarker for early diagnosis and targeted therapy of cervical cancer.

关键词： runt-related transcription factor 1 cervical cancer epithelial-mesenchymal transition bioinformatics

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Domain generalization with semi-supervised learning for people-centric activity recognition

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Science China(Information Sciences) 2025年第1期68卷 171-188页

作者： Jing liu Wei ZHU Di LI xing HU Liang SONG Academy for Engineering & Technology Fudan University Shanghai East-bund Research Institute on Networking Systems of AI School of Optoelectronic Information and Computer Engineering University of Shanghai for Science & Technology

People-centric activity recognition is one of the most critical technologies in a wide range of real-world applications,including intelligent transportation systems, healthcare services, and brain-computer interfaces. Large-scale data collection and annotation make the application of machine learning algorithms prohibitively expensive when adapting to new tasks. One way of circumventing this limitation is to train the model in a semi-supervised learning manner that utilizes a percentage of unlabeled data to reduce the labeling burden in prediction tasks. Despite their appeal, these models often assume that labeled and unlabeled data come from similar distributions, which leads to the domain shift problem caused by the presence of distribution gaps. To address these limitations, we propose herein a novel method for people-centric activity recognition,called domain generalization with semi-supervised learning(DGSSL), that effectively enhances the representation learning and domain alignment capabilities of a model. We first design a new autoregressive discriminator for adversarial training between unlabeled and labeled source domains, extracting domain-specific features to reduce the distribution gaps. Second, we introduce two reconstruction tasks to capture the task-specific features to avoid losing information related to representation learning while maintaining task-specific consistency. Finally, benefiting from the collaborative optimization of these two tasks, the model can accurately predict both the domain and category labels of the source domains for the classification task. We conduct extensive experiments on three real-world sensing datasets. The experimental results show that DGSSL surpasses the three state-of-the-art methods with better performance and generalization.

关键词： activity recognition deep learning domain generalization semi-supervised learning adversarial training

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Molecular Structure Tailoring of Organic Spacers for High‑Performance Ruddlesden–Popper Perovskite Solar Cells

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Nano-Micro Letters 2025年第2期17卷 314-357页

作者： Pengyun liu Xuejin Li Tonghui Cai Wei xing Naitao Yang Hamidreza Arandiyan Zongping Shao Shaobin Wang Shaomin liu School of Materials Science and Engineering State Key Laboratory of Heavy Oil ProcessingChina University of Petroleum(East China)Qingdao 266580People’s Republic of China School of Chemistry and Chemical Engineering Shandong University of TechnologyZibo 255049People’s Republic of China Centre for Applied Materials and Industrial Chemistry(CAMIC) School of ScienceRMIT UniversityMelbourneVic 3000Australia WA School of Mines:Minerals Energy and Chemical Engineering(WASM‑MECE)Curtin UniversityPerthWA 6102Australia School of Chemical Engineering The University of AdelaideAdelaideSA 5005Australia School of Engineering Great Bay UniversityDongguan 523000People’s Republic of China

Layer-structured Ruddlesden–Popper(RP)perovskites(RPPs)with decent stability have captured the imagination of the photovoltaic research community and bring hope for boosting the development of perovskite solar cell(PSC)***,two-dimensional(2D)or quasi-2D RP PSCs are encountered with some challenges of the large exciton binding energy,blocked charge transport and poor film quality,which restrict their photovoltaic ***,these issues can be readily resolved by rationally designing spacer cations of *** review mainly focuses on how to design the molecular structures of organic spacers and aims to endow RPPs with outstanding photovoltaic *** firstly elucidated the important roles of organic spacers in impacting crystallization kinetics,charge transporting ability and stability of *** we brought three aspects to attention for designing organic ***,we presented the specific molecular structure design strategies for organic spacers of RPPs aiming to improve photovoltaic performance of RP *** proposed strategies in this review will provide new avenues to develop novel organic spacers for RPPs and advance the development of RPP photovoltaic technology for future applications.

关键词： Ruddlesden-Popper perovskites Low-dimensional perovskite solar cells Organic spacers Molecular structure Design strategies

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Solution‑Processed Thin Film Transparent Photovoltaics:Present Challenges and Future Development

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Nano-Micro Letters 2025年第2期17卷 566-600页

作者： Tianle liu Munerah M.S.Almutairi Jie Ma Aisling Stewart Zhaohui xing Mengxia liu Bo Hou Yuljae Cho UM-SJTU Joint Institute Shanghai Jiao Tong UniversityShanghai 200240People’s Republic of China School of Physics and Astronomy Cardiff UniversityCardiff CF243AAWalesUK Department of Electrical and Computer Engineering Yale UniversityNew HavenCT 06511USA Energy Sciences Institute Yale UniversityWest HavenCT 06516USA Future Photovoltaics Research Center Global Institute of Future TechnologyShanghai Jiao Tong UniversityShanghai 200240People’s Republic of China

Electrical energy is essential for modern society to sustain economic *** soaring demand for the electrical energy,together with an awareness of the environmental impact of fossil fuels,has been driving a shift towards the utilization of solar ***,traditional solar energy solutions often require extensive spaces for a panel installation,limiting their practicality in a dense urban *** overcome the spatial constraint,researchers have developed transparent photovoltaics(TPV),enabling windows and facades in vehicles and buildings to generate electric *** TPV advancements are focused on improving both transparency and power output to rival commercially available silicon solar *** this review,we first briefly introduce wavelength-and non-wavelengthselective strategies to achieve *** of merit and theoretical limits of TPVs are discussed to comprehensively understand the status of current TPV *** we highlight recent progress in different types of TPVs,with a particular focus on solution-processed thin-film photovoltaics(PVs),including colloidal quantum dot PVs,metal halide perovskite PVs and organic *** applications of TPVs are also reviewed,with emphasis on agrivoltaics,smart windows and ***,current challenges and future opportunities in TPV research are pointed out.

关键词： Transparent semiconductors Solution-processable transparent solar cell Emerging solar cell materials Buildingintegrated photovoltaics

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Insights into spinal muscular atrophy from molecular biomarkers

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Neural Regeneration Research 2025年第7期20卷 1849-1863页

作者： Xiaodong xing Xinzhu liu Xiandeng Li Mi Li Xian Wu Xiaohui Huang Ajing Xu Yan liu Jian Zhang Department of Clinical Pharmacy Xinhua HospitalShanghai Jiao Tong University School of MedicineShanghaiChina College of Pharmacy Chongqing Medical UniversityChongqingChina

Spinal muscular atrophy is a devastating motor neuron disease characterized by severe cases of fatal muscle *** is one of the most common genetic causes of mortality among infants aged less than 2 *** research is currently receiving more attention,and new candidate biomarkers are constantly being *** review initially discusses the evaluation methods commonly used in clinical practice while briefly outlining their respective pros and *** also describe recent advancements in research and the clinical significance of molecular biomarkers for spinal muscular atrophy,which are classified as either specific or non-specific *** review provides new insights into the pathogenesis of spinal muscular atrophy,the mechanism of biomarkers in response to drug-modified therapies,the selection of biomarker candidates,and would promote the development of future ***,the successful utilization of biomarkers may facilitate the implementation of gene-targeting treatments for patients with spinal muscular atrophy.

关键词： biomarkers disease progression gene-targeting therapy neurofilaments Nusinersen spinal muscular atrophy(SMA) survival motor neuron therapeutic evaluation treatment outcomes

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Effect of pouring time on microstructure and mechanical properties of centrifugal cast Ti-46Al alloy tubes

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China Foundry 2025年

作者： Gang Huang Qian dang Cong-cong Su Jing Zhao Chi Zhang Guo-huai liu Zhao-dong Wang The State Key Laboratory of Rolling and Automation Northeastern University School of Materials Science and Engineering Shenyang University of Technology

The grain size of TiAl alloy castings prepared by traditional casting process is coarse, thus showing poor mechanical properties. In this study, a new type of high performance Ti-46Al alloy tube prepared by vacuum centrifugal casting technology was introduced. This research comprehensively examined the influence of pouring time on the microstructure and mechanical performance of the castings, employing both experimental approaches and ProCast simulation methodologies. The findings indicate that prolonging the pouring time facilitates a microstructural evolution from coarse columnar grains to refined equiaxed grains. Under the condition of pouring temperature of 1,600 °C, rotation speed of 800 r·min-1and pouring time of 6 s, the tensile strength of Ti-46Al alloy at room temperature reaches 650 MPa, and the tensile strength at 800 °C reaches 705 MPa, which is significantly higher than that of traditional as-cast Ti-Al alloy.

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Recent Advances in Fibrous Materials for Hydroelectricity Generation

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Nano-Micro Letters 2025年第2期17卷 109-133页

作者： Can Ge Duo Xu Xiao Feng xing Yang Zheheng Song Yuhang Song Jingyu Chen Yingcun liu Chong Gao Yong Du Zhe Sun Weilin Xu Jian Fang College of Textile and Clothing Engineering Soochow UniversitySuzhou 215123People’s Republic of China National Engineering Laboratory for Modern Silk Soochow UniversitySuzhou 215123People’s Republic of China State Key Laboratory of New Textile Materials and Advanced Processing Technologies Wuhan Textile UniversityWuhan 430200People’s Republic of China Institute of Functional Nano&Soft Materials(FUNSOM) Soochow UniversitySuzhou 215123People’s Republic of China Department of Electrical and Computer Engineering University of MassachusettsAmherstMA 01003USA Department of Materials Imperial College LondonSouth Kensington CampusLondon SW72AZUK College of Textile Science and Engineering Zhejiang Sci-Tech UniversityHangzhou 310018People’s Republic of China School of Materials Science and Engineering Shanghai Institute of Technology100 Haiquan RoadShanghai 201418People’s Republic of China

Depleting fossil energy sources and conventional polluting power generation pose a threat to sustainable *** generation from ubiquitous and spontaneous phase transitions between liquid and gaseous water has been considered a promising strategy for mitigating the energy *** materials with unique flexibility,processability,multifunctionality,and practicability have been widely applied for fibrous materials-based hydroelectricity generation(FHG).In this review,the power generation mechanisms,design principles,and electricity enhancement factors of FHG are first ***,the fabrication strategies and characteristics of varied constructions including 1D fiber,1D yarn,2D fabric,2D membrane,3D fibrous framework,and 3D fibrous gel are ***,the advanced functions of FHG during water harvesting,proton dissociation,ion separation,and charge accumulation processes are analyzed in ***,the potential applications including power supply,energy storage,electrical sensor,and information expression are also ***,some existing challenges are considered and prospects for future development are sincerely proposed.

关键词： Hydroelectricity Fibrous material Streaming potential Ion diffusion

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Single-cell omics: experimental workflow, data analyses and applications

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Science China Life Sciences 2025年第1期68卷 5-102页

作者： Fengying Sun Haoyan Li Dongqing Sun Shaliu Fu Lei Gu Xin Shao Qinqin Wang Xin Dong Bin Duan Feiyang xing Jun Wu Minmin Xiao Fangqing Zhao Jing-Dong J.Han Qi liu Xiaohui Fan Chen Li Chenfei Wang Tieliu Shi Department of Clinical Laboratory the Affiliated Wuhu Hospital of East China Normal University (The Second People's Hospital of Wuhu City) Pharmaceutical Informatics Institute College of Pharmaceutical SciencesZhejiang University Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University) Ministry of EducationOrthopaedic DepartmentTongji HospitalBioinformatics DepartmentSchool of Life Sciences and TechnologyTongji University Frontier Science Center for Stem Cells School of Life Sciences and TechnologyTongji University Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine Shanghai East HospitalBioinformatics DepartmentSchool of Life Sciences and TechnologyTongji University Research Institute of Intelligent Computing Zhejiang Lab Shanghai Research Institute for Intelligent Autonomous Systems Center for Single-cell Omics School of Public HealthShanghai Jiao Tong University School of Medicine National Key Laboratory of Chinese Medicine Modernization Innovation Center of Yangtze River DeltaZhejiang University Center for Bioinformatics and Computational Biology Shanghai Key Laboratory of Regulatory Biologythe Institute of Biomedical Sciences and School of Life SciencesEast China Normal University Beijing Institutes of Life Science Chinese Academy of Sciences Peking-Tsinghua Center for Life Sciences Academy for Advanced Interdisciplinary StudiesCenter for Quantitative Biology (CQB)Peking University Zhejiang Key Laboratory of Precision Diagnosis and Therapy for Major Gynecological Diseases Women's HospitalZhejiang University School of Medicine Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE School of StatisticsEast China Normal University

Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular features. Our exploration of how the genomes orchestrate the formation and maintenance of each cell, and control the cellular phenotypes of various organismsis, is both captivating and intricate. Since the inception of the first single-cell RNA technology, technologies related to single-cell sequencing have experienced rapid advancements in recent years. These technologies have expanded horizontally to include single-cell genome, epigenome,proteome, and metabolome, while vertically, they have progressed to integrate multiple omics data and incorporate additional information such as spatial sc RNA-seq and CRISPR screening. Single-cell omics represent a groundbreaking advancement in the biomedical field,offering profound insights into the understanding of complex diseases, including cancers. Here, we comprehensively summarize recent advances in single-cell omics technologies, with a specific focus on the methodology section. This overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.

关键词： single-cell sequencing genome epigenome proteomics metabolomics multimodal spatial transcriptomics CRISPR screening

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Facile synthesis of the dodecahydridododecaborate (B12H122-) from borane Lewis base adducts

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Science China Chemistry 2025年

作者： Yi Jing Xin-Ran liu xing-Hua Wang Hui Han Sha-Sha Liang Xi-Meng Chen Dong-Hui Wei Lai-Sheng Wang Xue-Nian Chen College of Chemistry Zhengzhou University School of Chemistry and Chemical Engineering Henan Key Laboratory of Boron Chemistry and Advanced MaterialsHenan Normal University Department of Chemistry Brown University

Polyhedral boranes are a class of well-known boron molecular clusters widely used in energy,chemistry,medicine,and materials science because of their unique physical and chemical *** efforts have been made in the past decades to find more effective synthetic methods for this important class of boron ***,existing synthetic methods suffer from low efficiency and low ***,we report a facile one-pot synthesis of[（CH3）3S]2B12H12with moderate yields at mild *** mechanisms for the multi-step chemoselective synthesis of B12H122-without other by-products are elucidated based on theoretical results and our previous *** Lewis base used in B–H bond condensation reaction,which acts as a hydrogen or to balance the newly generated polyhedral borane charges,is proposed and studied in *** current study has led to a more effective and selective synthetic method for B12H122-and has also implicated the syntheses of other new polyhedral boranes.

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Deep learning-based software engineering: progress,challenges, and opportunities

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Science China(Information Sciences) 2025年第1期68卷 57-144页

作者： Xiangping CHEN xing HU Yuan HUANG He JIANG Weixing JI Yanjie JIANG Yanyan JIANG Bo liu Hui liu Xiaochen LI Xiaoli LIAN Guozhu MENG Xin PENG Hailong SUN Lin SHI Bo WANG Chong WANG Jiayi WANG Tiantian WANG Jifeng XUAN Xin XIA Yibiao YANG Yixin YANG Li ZHANG Yuming ZHOU Lu ZHANG School of Journalism and Communication Sun Yat-sen University School of Software Technology Zhejiang University School of Software Engineering Sun Yat-sen University School of Software Dalian University of Technology School of Computer Science and Technology Beijing Institute of Technology Key Laboratory of High Confidence Software Technologies (Peking University) Ministry of EducationSchool of Computer Science Peking University State Key Laboratory for Novel Software Technology Nanjing University School of Computer Science and Engineering Beihang University Institute of Information Engineering Chinese Academy of Sciences School of Computer Science Fudan University State Key Laboratory of Complex & Critical Software Environment (CCSE) School of Software Beihang University School of Computer and Information Technology Beijing Jiaotong University School of Computer Science and Technology Harbin Institute of Technology School of Computer Science Wuhan University Huawei Technologies

Researchers have recently achieved significant advances in deep learning techniques, which in turn has substantially advanced other research disciplines, such as natural language processing, image processing, speech recognition, and software engineering. Various deep learning techniques have been successfully employed to facilitate software engineering tasks, including code generation, software refactoring, and fault localization. Many studies have also been presented in top conferences and journals, demonstrating the applications of deep learning techniques in resolving various software engineering tasks. However,although several surveys have provided overall pictures of the application of deep learning techniques in software engineering,they focus more on learning techniques, that is, what kind of deep learning techniques are employed and how deep models are trained or fine-tuned for software engineering tasks. We still lack surveys explaining the advances of subareas in software engineering driven by deep learning techniques, as well as challenges and opportunities in each subarea. To this end, in this study, we present the first task-oriented survey on deep learning-based software engineering. It covers twelve major software engineering subareas significantly impacted by deep learning techniques. Such subareas spread out through the whole lifecycle of software development and maintenance, including requirements engineering, software development, testing, maintenance, and developer collaboration. As we believe that deep learning may provide an opportunity to revolutionize the whole discipline of software engineering, providing one survey covering as many subareas as possible in software engineering can help future research push forward the frontier of deep learning-based software engineering more systematically. For each of the selected subareas,we highlight the major advances achieved by applying deep learning techniques with pointers to the available datasets i

关键词： deep learning software engineering software benchmark software artifact representation survey

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