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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

自粘式超声波驱动摩擦电纳米发电机用于皮下抗菌和促进伤口愈合（英文）

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science China Materials 2025年第1期 261-269页

作者：吕晓薇郭春梅罗思晗齐丽娜石静怡赵建航陈莹何爱军范曲立 Key Laboratory for Organic Electronics & information Displays and institute of Advanced Materials Nanjing University of Post & Telecommunications school of Electronic science and Engineering Nanjing University

电刺激疗法在伤口愈合和组织再生方面具有巨大潜力.然而,传统方法通常需要外部电源和可植入电极,这可能限制它们的实际应用.在此,我们报道了一种超声介导的自供电伤口愈合装置(LH-TENG)的开发,该装置采用皮肤粘附性AgC@L-g-PAM/HPC水凝...

电刺激疗法在伤口愈合和组织再生方面具有巨大潜力.然而,传统方法通常需要外部电源和可植入电极,这可能限制它们的实际应用.在此,我们报道了一种超声介导的自供电伤口愈合装置(LH-TENG)的开发,该装置采用皮肤粘附性AgC@L-g-PAM/HPC水凝胶作为电极,在超声介导下, LH-TENG能牢固附着在组织表面,并在伤口区域周围产生均匀的电场,促进细胞迁移、增殖并加速愈合.此外,该装置表现出抗菌特性,因此其在治疗感染的慢性伤口方面具有潜力.

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Spatio-temporal patterns and climatic drivers of spring phenology in eight forest communities across the north-south transitional zone of China

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Journal of Geographical sciences 2025年第1期 17-38页

作者： ZHU Wenbin LU Yu institute of Geographic sciences and Natural Resources Research CAS school of Geographical science Nanjing University of Information Science & Technology

The Qinba Mountains are climatically and ecologically recognized as the northsouth transitional zone of *** of its phenology is critical for comprehending the response of vegetation to climatic *** retrieved the start of spring phenology （SOS）of eight forest communities from the MODIS products and adopted it as an indicator for spring *** analysis,partial correlation analysis,and Geo Detector were employed to reveal the spatio-temporal patterns and climatic drivers of *** results indicated that the SOS presented an advance trend from 2001 to 2020,with a mean rate of–0.473 d yr–*** SOS of most forests correlated negatively with air temperature （TEMP） and positively with precipitation （PRE）,suggesting that rising TEMP and increasing PRE in spring would forward and delay SOS,*** dominant factors influencing the sensitivity of SOS to climatic variables were altitude,forest type,and latitude,while the effects of slope and aspect were relatively *** response of SOS to climatic factors varied significantly in space and among forest communities,partly due to the influence of altitude,slope,and aspect.

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Bifunctional bridging capping layer enables 24.5% efficiency of perovskite solar cells with polymer-based hole transport materials

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science China Chemistry 2025年第1期 350-359页

作者： Can Zhu Yiyang Wang Lei Meng Beibei Qiu Jing Li Shucheng Qin Ke Hu Xin Jiang Wenbin Lai Minchao Liu Zhe Liu Chenxing Lu Jinyuan Zhang Yongfang Li Beijing National Laboratory for Molecular sciences CAS Key Laboratory of Organic Solids Institute of Chemistry Chinese Academy of Sciences school of Chemical science University of Chinese Academy of Sciences Key Laboratory of Solid State Optoelectronic Devices of Zhejiang Province College of Physics and Electronic Information Engineering Zhejiang Normal University Key Laboratory of Photochemical Conversion and Optoelectronic Materials Technical Institute of Physics and ChemistryChinese Academy of Sciences Laboratory of Advanced Optoelectronic Materials College of Chemistry Chemical Engineering and Materials ScienceSoochow University

Developing a bridge capping layer between perovskite and hole transport layer materials（HTMs） in the n-i-p perovskite solar cells（pero-SCs） is an effective approach to modify the morphology of HTMs and passivate the perovskite ***, we select the quinoxaline-based bifunctional passivation agent, quinoxalin-6-yl-methylamine hydrochloride（Qx MACl）,as the bridging layer, and a D-A copolymer PBQ12 containing the same quinoxaline unit as an HTM for the n-i-p pero-SCs. Due to the π-π stacking among the common quinoxaline units in the bridge layer and HTM, Qx MACl induces the π-π stacking of the PBQ12 film and improves the film morphology of HTMs with better conductivity. Additionally, Qx MACl can effectively passivate the perovskite surface, and PBQ12 possesses appropriate energy levels and high hole mobility. The pero-SCs based on FAPbI3with PBQ12/Qx MACl treatment showed a higher power conversion efficiency（PCE） of 24.05% and outstanding stability, maintaining 95.4% and 92.1% of its initial PCE after 750 h of storage and after over 800 h of thermal annealing at 85 °C, respectively. To further enhance the PCE of the PBQ12/Qx MACl-based devices, we developed a non-metal ion dopant for the PBQ12 HTM. Through trace doping of PBQ12 HTM by the non-metal ion dopant, the PCE of the PBQ12/Qx MACl-based devices reached 25.24%（the calibrated PCE of 24.55% by the National institute of Metrology, China）.

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A deep learning approach for detecting candidates of supernova remnants

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Research in Astronomy and Astrophysics 2019年第3期19卷 85-96页

作者： Wei Liu Cong Dai Meng Zhu Bing-Yi Wang Kang Wu Xian-Chuan Yu Wen-Wu Tian Meng-Fei Zhang Hong-Feng Wang College of information science and Technology Beijing Normal University National astronomical Observatories Chinese Academy of Sciences school of information management Dezhou University

Detecting supernova remnant(SNR) candidates in the interstellar medium is a challenging task because SNRs have weak radio signals and irregular shapes. The use of a convolutional neural network is a deep learning method that can help us extract various features from images. To extract SNRs from astronomical images and estimate the positions of SNR candidates, we design the SNR-Net model composed of a training component and a detection component. In addition, transfer learning is used to initialize the network parameters, which improves the speed and accuracy of network training. We apply a T-T plot(of the different brightness temperatures of map pixels at two different frequencies) to calculate the spectral index of SNR candidates. To accelerate the scientific computing process, we take advantage of innovative hardware architecture, such as deep learning optimized graphics processing units, which increases the speed of computation by a factor of 5. A case study suggests that SNR-Net may be applicable to detecting extended sources in the images automatically.

关键词： methods data analysis-techniques image processing-stars fundamental parameters

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A Comprehensive Survey on Federated Learning Applications in Computational Mental Healthcare

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Computer Modeling in Engineering & sciences 2025年第1期142卷 49-90页

作者： Vajratiya Vajrobol Geetika Jain Saxena Amit Pundir Sanjeev Singh Akshat Gaurav Savi Bansal Razaz Waheeb Attar Mosiur Rahman Brij B.Gupta institute of Informatics and Communication University of DelhiDelhi110021India Maharaja Agrasen College University of DelhiDelhi110096India Computer Engineering Ronin InstituteMontclairNJ 07043USA Department of Research and Innovation Insights2TechinfoJaipur302001India University Centre for Research and Development(UCRD) Chandigarh UniversityChandigarh140413India management Department College of Business AdministrationPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia CCRI&Department of Computer science and information Engineering Asia UniversityTaichung413Taiwan Symbiosis Centre for information Technology(SCIT) Symbiosis International UniversityPune411057India Center for Interdisciplinary Research University of Petroleum and Energy Studies(UPES)Dehradun248007India

Mental health is a significant issue worldwide,and the utilization of technology to assist mental health has seen a growing *** aims to alleviate the workload on healthcare professionals and aid *** applications have been developed to support the challenges in intelligent healthcare ***,because mental health data is sensitive,privacy concerns have *** learning has gotten some *** research reviews the studies on federated learning and mental health related to solving the issue of intelligent healthcare *** explores various dimensions of federated learning in mental health,such as datasets(their types and sources),applications categorized based on mental health symptoms,federated mental health frameworks,federated machine learning,federated deep learning,and the benefits of federated learning in mental health *** research conducts surveys to evaluate the current state of mental health applications,mainly focusing on the role of Federated Learning(FL)and related privacy and data security *** survey provides valuable insights into how these applications are emerging and evolving,specifically emphasizing FL’s impact.

关键词： Depression emotional recognition intelligent healthcare systems mental health federated learning stress detection sleep behaviour

Enhanced Privacy Preserving for Social Networks Relational Data Based on Personalized Differential Privacy

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Chinese Journal of Electronics 2022年第4期31卷 741-751页

作者： KANG Haiyan JI Yuanrui ZHANG Shuxuan school of information management Beijing Information Science and Technology University Computer school Beijing Information Science and Technology University

With the popularization and development of social software, more and more people join the social network, which produces a lot of valuable information, but also contains plenty of sensitive privacy information. To achieve the personalized privacy protection of massive social network relational data, a privacy enhancement method for social networks relational data based on personalized differential privacy is proposed. And a dimensionality reduction segmentation sampling(DRS-S)algorithm is proposed to implement this method. First, in order to solve the problem of inefficiency caused by the excessive amount of data in social networks, dimension reduction and segmentation are carried out to divide the data into groups. According to the privacy protection requirements of different users, we adopt sampling method to protect users with different privacy requirements at different levels, so as to realize personalized different privacy. After that, the noise is added to the protected data to satisfy the privacy budget. Then publish the social network data. Finally, the proposed algorithm is compared with the traditional personalized differential privacy(PDP) algorithm and privacy preserving approach based on clustering and noise(PBCN) in real data set, the experimental results demonstrate that the quality of privacy protection and data availability of DRS-S are better than that of PDP algorithm and PBCN algorithm.

关键词： Social network Privacy preserving Dimensionality reduction segmentation Personalized differential privacy DRS-S algorithm

A Bayesian Recommender Model for User Rating and Review Profiling

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Tsinghua science and Technology 2015年第6期20卷 634-643页

作者： Mingming Jiang Dandan Song Lejian Liao Feida Zhu school of Computer science and Technology Beijing Institute of Technology school of information Systems Singapore Management University

Intuitively, not only do ratings include abundant information for learning user preferences, but also reviews accompanied by ratings. However, most existing recommender systems take rating scores for granted and discard the wealth of information in accompanying reviews. In this paper, in order to exploit user profiles’ information embedded in both ratings and reviews exhaustively, we propose a Bayesian model that links a traditional Collaborative Filtering(CF) technique with a topic model seamlessly. By employing a topic model with the review text and aligning user review topics with 'user attitudes'(i.e., abstract rating patterns) over the same distribution, our method achieves greater accuracy than the traditional approach on the rating prediction task. Moreover, with review text information involved, latent user rating attitudes are interpretable and 'cold-start' problem can be *** property qualifies our method for serving as a 'recommender' task with very sparse datasets. Furthermore,unlike most related works, we treat each review as a document, not all reviews of each user or item together as one document, to fully exploit the reviews’ information. Experimental results on 25 real-world datasets demonstrate the superiority of our model over state-of-the-art methods.

关键词： collaborative filtering topic model recommender sy

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Distributed fiber optic sensing system for vibration monitoring of 3D printed bridges

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Optoelectronics Letters 2025年第1期21卷 28-34页

作者： ZHAO Shuai ZHOU Ran LUO Mingming LIU Jianfei LIU Xiongfei ZHOU Tao school of Electronic information Engineering Hebei University of Technology Tianjin Key Laboratory of Electronic Materials and Devices school of Civil Engineering and Transportation Hebei University of Technology Tianjin Jinhang institute of Technical Physics

The fiber optic sensing technology provides data support in structural health monitoring of the macro facilities, including design, construction, and maintenance of bridges, tunnels, ports and other infrastructures. In this paper, a distributed vibration sensing system is proved to be responsive to a single touch over a 1.8-m-long equivalent fiber segment, covering a vibration frequency from 5 Hz to 25 kHz. The sensing fiber was arranged as an S type layout on the bridge to recognize the standing state, windblown disturbance, and walking vibration. Moreover, the knocking and climbing events are recognized fiber laying spinning lines and hanging on the fences, respectively. The demonstration shows an accurate positioning and sensitive vibration monitoring applied on the automated three-dimensional(3D) printed bridge, which is applicable to all kinds of 3D printed facilities as intelligent sensory neuro-networks.

关键词： Spinning (fibers)