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Towards a blood ecosystem approach to dissect systemic diseases

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Science China(Life Sciences) 2024年第7期67卷 1528-1531页

作者： Hong Wang Tao Cheng state key laboratory of experimental hematology Haihe Laboratory of Cell EcosystemNational Clinical Research Center for Blood DiseasesInstitute of Hematology&Blood Diseases HospitalChinese Academy of Medical Sciences&Peking Union Medical CollegeTianjin 300020China Tianjin Institutes of Health Science Tianjin 301600China

Systemic diseases,in contrast to localized ailments,exert widespread effects and can impact the entire *** of systemic diseases encompass autoimmune disorders,infectious diseases,metabolic disorders,and chronic conditions like *** diseases often entail intricate interactions among diverse organs,tissues,and physiological systems,influenced by a myriad of factors.

关键词： diseases organs autoimmune

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Conversion of a single-layer ANN to photonic SNN for pattern recognition

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Science China(Information Sciences) 2024年第1期67卷 261-270页

作者： Yanan HAN Shuiying XIANG Tianrui ZHANG Yahui ZHANG Xingxing GUO Yuechun SHI state key laboratory of Integrated Service Networks State Key Discipline Laboratory of Wide Bandgap Semiconductor TechnologyXidian University Yongjiang laboratory

This work presents a complete conversion scheme for photonic spiking neural networks(SNNs).We verified that the output of an artificial neural network(ANN) trained with the simulated optical activation function can be directly converted into the spike rate of a photonic spiking neuron *** reveal the feasibility of hardware implementation,we considered the effects of different bit precisions of data and weight,noise level,and bias current mismatch on the converted *** proposed scheme was evaluated using the Deterding vowel,IRIS,TIDIGITS,and MNIST datasets for pattern recognition,and achieved mean accuracies of 95.80%,98.67%,96.19%,and 92.33%,*** proposed scheme can convert an ANN into a photonic SNN with almost no precision loss,and the performance was comparable to that of an ANN trained with the rectified linear unit *** proposed scheme can enable the high-performance implementation of photonic SNNs.

关键词： photonic SNN conversion optical computing pattern recognition artificial neural network

PRC2 primes bivalent genes for transcription induction independent of histone methyltransferase activity

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Science China Life Sciences 2024年第9期67卷 2033-2035页

作者： Meihan Gong Ye Yuan Zhongye Dai Xuejiao Lv Jiacheng Su Dawei Huo Lin Niu Xu Chen Xudong Wu state key laboratory of experimental hematology The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics Key Laboratory of Immune Microenvironment and Disease (Ministry of Education) Department of Cell Biology School of Basic Medical Sciences Tianjin Medical University Bone Marrow Transplantation Center the First Affiliated Hospital Zhejiang University School of Medicine Liangzhu Laboratory Institute of Hematology Zhejiang University

Dear Editor,Polycomb group proteins, conserved epigenetic transcriptional repressors, are crucial for orchestrating diverse developmental gene expression programs(Schuettengruber et al., 2017). The polycomb repressive complex 2(PRC2) catalyzes H3 lysine-27 trimethylation(H3K27me3) to establish a delicate balance with H3K4me3, forming a bivalent chromatin state at target gene promoters and thereby poising them for subsequent transcription activation(Bernstein et al.,2006).

关键词： REPRESSIVE COMPLEX 2 POLYCOMB PROMOTERS

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Favorable outcomes of front-line risk-adapted therapy in young patients with diffuse large B-cell lymphoma with clinically or biologically high-risk features

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Chinese Medical Journal 2024年第13期137卷 1620-1622页

作者： Hesong Zou Wei Liu Yi Wang Dandan Shan Ting Xie Ru Li Huimin Liu Wenyang Huang Mingwei Fu Tingyu Wang Rui Lyu Shuhui Deng Weiwei Sui Yan Xu Shuhua Yi Gang An Lugui Qiu Dehui Zou state key laboratory of experimental hematology National Clinical Research Center for Blood DiseasesHaihe Laboratory of Cell EcosystemInstitute of Hematology&Blood Diseases HospitalChinese Academy of Medical Science&Peking Union Medical CollegeTianjin 300020China Tianjin Institutes of Health Science Tianjin 301600China

To the Editor:Diffuse large B-cell lymphoma(DLBCL)exhibits clinical significance and biological *** the last two decades,rituximab with cyclophosphamide,doxorubicin,vincristine,and prednisone(R-CHOP)has substantially improved outcomes for DLBCL ***,approximately one-third of DLBCL cases continue to experience disease progression,resulting in long-term survival ranging from 50%to 60%.[1]Efforts to improve DLBCL patient outcomes by modifying R-CHOP dosing schedules have yielded limited success,and the addition of new drugs has benefited only specific patient ***,intensive immunochemotherapy(IIC)has demonstrated promise and cost-effectiveness in recent *** regimen of dose-adjusted etoposide.

关键词： CHOP drugs chemotherapy

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Skull and vertebral bone marrow in central nervous system inflammation

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Fundamental Research 2024年第2期4卷 246-250页

作者： Honglei Ren Qiang Liu Department of Neurology Tianjin Neurological InstituteTianjin Institute of ImmunologyState Key Laboratory of Experimental HematologyInternational Joint Laboratory of Ocular DiseasesMinistry of EducationHaihe Laboratory of Cell EcosystemTianjin Medical University General HospitalTianjin 300052China

Emerging evidence has highlighted the capacity of hematogenous cells in skull and vertebral bone marrow to enter the meningeal borders via ossified vascular channels and maintain immune homeostasis in the central nervous system(CNS).CNS-adjacent skull and vertebral bone marrow comprises hematopoietic niches that can sense CNS injury and supply specialized immune cells to fine-tune inflammatory ***,we review recent advances in our understanding of skull and vertebral bone marrow-derived immune cells in homeostasis and inflammatory CNS ***,we discuss the implications for future development of therapies to mitigate CNS inflammation and its detrimental sequelae in neurological disorders.

关键词： Central nervous system Bone marrow Hematopoiesis Immune cells Neuroinflammation Stroke Multiple sclerosis

experimental and numerical demonstration of hierarchical time-delay reservoir computing based on cascaded VCSELs with feedback and multiple injections

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Science China(Information Sciences) 2024年第2期67卷 279-290页

作者： Xingxing GUO Shuiying XIANG Xingyu CAO Biling GU state key laboratory of Integrated Service Networks Xidian University state key Discipline laboratory of Wide Bandgap Semiconductor Technology School of MicroelectronicsXidian University

In this paper, we propose and demonstrate experimentally and numerically a hierarchical timedelay optical reservoir computing(RC) system based on cascaded vertical-cavity surface-emitting lasers(VCSELs) with feedback and multiple injections. The prediction performance characteristics of the hierarchical time-delay RC system based on cascaded VCSELs under different reservoir layers are ***, the prediction performance of the hierarchical time-delay RC system is first improved and saturates as the number of reservoir layers increases. Besides, the impacts of key factors on predicting the hierarchical time-delay RC system are also analyzed in detail experimentally and numerically. This proposed hierarchical time-delay RC system based on VCSELs is useful for the further development of RC systems and may be beneficial to improve the ability of RC systems to solve more complex problems.

关键词： vertical-cavity surface-emitting laser reservoir computing neuromorphic photonics time-delay system information processing

A credible traffic prediction method based on self-supervised causal discovery

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Science China(Information Sciences) 2024年第5期67卷 244-258页

作者： Dan WANG Yingjie LIU Bin SONG state key laboratory of Integrated Services Networks Xidian University

Next-generation wireless network aims to support low-latency, high-speed data transmission services by incorporating artificial intelligence(AI) technologies. To fulfill this promise, AI-based network traffic prediction is essential for pre-allocating resources, such as bandwidth and computing power. This can help reduce network congestion and improve the quality of service(QoS) for users. Most studies achieve future traffic prediction by exploiting deep learning and reinforcement learning, to mine spatio-temporal correlated variables. Nevertheless, the prediction results obtained only by the spatio-temporal correlated variables cannot reflect real traffic changes. This phenomenon prevents the true prediction variables from being inferred, making the prediction algorithm perform poorly. Inspired by causal science, we propose a novel network traffic prediction method based on self-supervised spatio-temporal causal discovery(SSTCD). We first introduce the Granger causal discovery algorithm to build a causal graph among prediction variables and obtain spatio-temporal causality in the observed data, which reflects the real reasons affecting traffic ***, a graph neural network(GNN) is adopted to incorporate causality for traffic prediction. Furthermore,we propose a self-supervised method to implement causal discovery to to address the challenge of lacking ground-truth causal graphs in the observed data. experimental results demonstrate the effectiveness of the SSTCD method.

关键词： wireless network traffic prediction causal discovery self-supervised

Micelle-directed self-assembly of single-crystal-like mesoporous stoichiometric oxides for high-performance lithium storage

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National Science Review 2024年第4期11卷 195-205页

作者： Yanhua Wan Changyao Wang Xingmiao Zhang Yang Yin Mengmeng Liu Bing Ma Linlin Duan Yuzhu Ma Wei Zhang Changlin Zheng Dongliang Chao Fei Wang Yongyao Xia Wei Li Department of Chemistry Laboratory of Advanced Materials Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials State Key Laboratory of Molecular Engineering of Polymers College of Chemistry and Materials ScienceFudan University state key laboratory of Surface Physics and Department of Physics Fudan University

Due to their uncontrollable assembly and crystallization process,the synthesis of mesoporous metal oxide single crystals remains a formidable ***,we report the synthesis of single-crystal-like mesoporous Li2TiSiO5by using soft micelles as *** key lies in the atomic-scale self-assembly and step-crystallization processes,which ensure the formation of single-crystal-like mesoporous Li2TiSiO5microparticles via an oriented attachment growth mechanism under the confinement of an in-situ formed carbon *** mesoporous Li2TiSiO5anode achieves a superior rate capability(148 mAh g-1at5.0 A g-1) and outstanding long-term cycling stability(138 mAh g-1after 3000 cycles at 2.0 A g-1) for lithium storage as a result of the ultrafast Li+diffusion caused by penetrating mesochannels and nanosized crystal frameworks（5-10 nm）.In comparison,bulk Li2TiSiO5exhibits poor rate capability and cycle performance due to micron-scale diffusion *** method is very simple and reproducible,heralding a new way of designing and synthesizing mesoporous single crystals with controllable frameworks and chemical functionalities.

关键词： mesoporous materials micelles single-crystal-like Li2TiSiO5 lithium-ion batteries

Recent advances in protein conformation sampling by combining machine learning with molecular simulation

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Chinese Physics B 2024年第3期33卷 80-87页

作者：唐一鸣杨中元姚逸飞周运谈圆王子超潘瞳熊瑞孙俊力韦广红 Department of Physics State Key Laboratory of Surface Physicsand Key Laboratory for Computational Physical Sciences (Ministry of Education)Shanghai 200438China

The rapid advancement and broad application of machine learning(ML)have driven a groundbreaking revolution in computational *** of the most cutting-edge and important applications of ML is its integration with molecular simulations to improve the sampling efficiency of the vast conformational space of large *** review focuses on recent studies that utilize ML-based techniques in the exploration of protein conformational *** first highlight the recent development of ML-aided enhanced sampling methods,including heuristic algorithms and neural networks that are designed to refine the selection of reaction coordinates for the construction of bias potential,or facilitate the exploration of the unsampled region of the energy ***,we review the development of autoencoder based methods that combine molecular simulations and deep learning to expand the search for protein ***,we discuss the cutting-edge methodologies for the one-shot generation of protein conformations with precise Boltzmann ***,this review demonstrates the promising potential of machine learning in revolutionizing our insight into the complex conformational ensembles of proteins.

关键词： machine learning molecular simulation protein conformational space enhanced sampling

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