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Neurocircuit regeneration by extracellular matrix reprogramming

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Neural Regeneration research 2025年第8期20卷 2300-2301页

作者： Shengzhang Su Ian N.Levasseur Kimberly M.Alonge Department of medicinal chemistry University of WashingtonSeattleWAUSA Department of chemistry University of WashingtonSeattleWAUSA Department of Medicine University of Washington Medicine Diabetes InstituteSeattleWAUSA

The brain's extracellular matrix(ECM),which is comprised of protein and glycosaminoglycan(GAG)scaffolds,constitutes 20%-40% of the human brain and is considered one of the largest influencers on brain cell functioning(Soles et al.,2023).Synthesized by neural and glial cells,the brain's ECM regulates a myriad of homeostatic cellular processes,including neuronal plasticity and firing(Miyata et al.,2012),cation buffering(Moraws ki et al.,2015),and glia-neuron interactions(Anderson et al.,2016).Considering the diversity of functions,dynamic remodeling of the brain's ECM indicates that this understudied medium is an active participant in both normal physiology and neurological diseases.

关键词： matrix programming

Emerging structures and dynamic mechanisms ofγ-secretase for Alzheimer’s disease

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Neural Regeneration research 2025年第1期20卷 174-180页

作者： Yinglong Miao Michael S.Wolfe Computational Medicine Program and Department of Pharmacology University of North Carolina–Chapel HillChapel HillNCUSA Department of medicinal chemistry University of KansasLawrenceKSUSA

γ-Secretase,called“the proteasome of the membrane,”is a membrane-embedded protease complex that cleaves 150+peptide substrates with central roles in biology and medicine,including amyloid precursor protein and the Notch family of cell-surface *** inγ-secretase and amyloid precursor protein lead to early-onset familial Alzheimer’s disease.γ-Secretase has thus served as a critical drug target for treating familial Alzheimer’s disease and the more common late-onset Alzheimer’s disease as ***,critical gaps remain in understanding the mechanisms of processive proteolysis of substrates,the effects of familial Alzheimer’s disease mutations,and allosteric modulation of substrate cleavage byγ-*** this review,we focus on recent studies of structural dynamic mechanisms ofγ-*** mechanisms,including the“Fit-Stay-Trim,”“Sliding-Unwinding,”and“Tilting-Unwinding,”have been proposed for substrate proteolysis of amyloid precursor protein byγ-secretase based on all-atom molecular dynamics *** an incorrect registry of the Notch1 substrate was identified in the cryo-electron microscopy structure of Notch1-boundγ-secretase,molecular dynamics simulations on a resolved model of Notch1-boundγ-secretase that was reconstructed using the amyloid precursor protein-boundγ-secretase as a template successfully capturedγ-secretase activation for proper cleavages of both wildtype and mutant Notch,being consistent with biochemical experimental *** approach could be potentially applied to decipher the processing mechanisms of various substrates byγ-*** addition,controversy over the effects of familial Alzheimer’s disease mutations,particularly the issue of whether they stabilize or destabilizeγ-secretase-substrate complexes,is ***,an outlook is provided for future studies ofγ-secretase,including pathways of substrate binding and product release,effects of modulators on familial Alzheimer’s disease mutations

关键词： Alzheimer’s disease amyloid precursor protein cryo-EM structures drug design intramembrane proteolysis molecular dynamics Notch

Emerging trends in the selective production of value-added aromatics

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Science China chemistry 2025年第1期68卷 15-20页

作者： Yuchao Wu Houliang Dai Weisheng Yang Yaxing Li Lichen Liu Petrochemical research Institute Company Limited China National Petroleum Corporation Engineering research Center of Advanced Rare Earth Materials Department of Chemistry Tsinghua University

1 Introduction Aromatics (mainly benzene, toluene, and xylenes, BTX) are essential intermediates in the chemical industry. They are employed in the synthesis of a broad spectrum of chemicals and materials, e.g., various polymers, plastics, resins, solvents, dyes, pharmaceuticals [1]. The manufacturing pathway of BTX mainly includes petroleum reforming of naphtha, coal-to-aromatics, methanol-to-aromatics [2].

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Stiffness-tunable biomaterials provide a good extracellular matrix environment for axon growth and regeneration

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Neural Regeneration research 2025年第5期20卷 1364-1376页

作者： Ronglin Han Lanxin Luo Caiyan Wei Yaru Qiao Jiming Xie Xianchao Pan Juan Xing Department of Pathophysiology School of Basic Medical SciencesSouthwest Medical UniversityLuzhouSichuan ProvinceChina Department of medicinal chemistry School of PharmacySouthwest Medical UniversityLuzhouSichuan ProvinceChina

Neuronal growth, extension, branching, and formation of neural networks are markedly influenced by the extracellular matrix—a complex network composed of proteins and carbohydrates secreted by cells. In addition to providing physical support for cells, the extracellular matrix also conveys critical mechanical stiffness cues. During the development of the nervous system, extracellular matrix stiffness plays a central role in guiding neuronal growth, particularly in the context of axonal extension, which is crucial for the formation of neural networks. In neural tissue engineering, manipulation of biomaterial stiffness is a promising strategy to provide a permissive environment for the repair and regeneration of injured nervous tissue. Recent research has fine-tuned synthetic biomaterials to fabricate scaffolds that closely replicate the stiffness profiles observed in the nervous system. In this review, we highlight the molecular mechanisms by which extracellular matrix stiffness regulates axonal growth and regeneration. We highlight the progress made in the development of stiffness-tunable biomaterials to emulate in vivo extracellular matrix environments, with an emphasis on their application in neural repair and regeneration, along with a discussion of the current limitations and future prospects. The exploration and optimization of the stiffness-tunable biomaterials has the potential to markedly advance the development of neural tissue engineering.

关键词： alginate axon growth biomaterials extracellular matrix neural repair neurons neuroregeneration polyacrylamide polydimethylsiloxane stiffness

Sequence-activated chemiluminescence probes: programmable illumination for high-contrast in vivo sensing and imaging

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Science China chemistry 2025年第1期68卷 26-34页

作者： Yutao Zhang Juan Li Wei-Hong Zhu Zhiqian Guo Shanghai Key Laboratory of Functional Materials chemistry Joint International Research Laboratory of Precision Chemistry and Molecular Engineering Institute of Fine Chemicals School of Chemistry and Molecular Engineering East China University of Science and Technology State Key Laboratory of Bioreactor Engineering Shanghai Frontier Science Research Base of Optogenetic Techniques for Cell MetabolismEast China University of Science & Technology

Sequence-activated chemiluminescence(CL) technique offers a unique approach to detecting specific biomolecules or cellular events with high sensitivity and spatial resolution. The fundamental principle behind sequence-activated CL probes involves tailoring highly-controllable CL signals in response to specific sequences or events of interest, thus enabling high-contrast signals under complex physiological conditions. This sequential activation could be triggered by enzymes, reactive oxygen species(ROS), biothiols or changes in the microenvironment. These unique sequence-activated CL probes bestow several advantages, including minimal background, deep-tissue penetration, and the ability of non-invasive or minimally invasive detection. The sequence-activated CL techniques represent a significant advancement in molecular imaging and diagnostics. In this mini-review, we focus on the latest developments in sequential CL probes, addressing the technical challenges and discussing the future trajectory by harnessing CL signaling and molecular recognition.

关键词： chemiluminescnece sequence-activation in-vivo bioimaging cyclic peroxide

Boosting hydrocarbon conversion via Cu-doping induced oxygen vacancies on CeO2 in CO2 electroreduction

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Journal of Energy chemistry 2025年第1期100卷 66-76页

作者： Lei Xue Tong Shi Chenhui Han Heng Zhang Fenrong Liu Haorun Li Yan Wang Xiaojun Gu Shanghong Zeng Inner Mongolia Key Laboratory of chemistry and Physics of Rare Earth Materials School of Chemistry and Chemical Engineering Inner Mongolia University State Key Laboratory of Coal Conversion Institute of Coal Chemistry Chinese Academy of Sciences Institute of Catalysis Department of Chemistry Zhejiang University National Key Laboratory of Baiyunobo Rare Earth Resource research and Comprehensive Utilization Baotou Research Institute of Rare Earths

Conversion of CO2back to hydrocarbons is the most direct way of closing the“carbon cycle”,and its significance is further enlarged if this process is driven by renewable energies such as ***,precisely controlling the product selectivity towards hydrocarbons against the competitive hydrogen evolution remains challenging,especially for Cu-based ***,we report a novel defect engineering strategy,by which Cu-doping-induced oxygen vacancies on CeO2nanorods were effectively created,with adjustable vacancy/Cu *** resulting optimum catalyst shows up to 79% catalytic current density to hydrocarbons （excluding CO）,with 49% faradaic efficiency to *** and density functional theory unveil that the ratio between oxygen vacancy and Cu affects significantly the formation of*CHO and activation of H2O,which leads to the following deep hydrogenation to *** findings may spur new insights for designing and developing more controllable chemical process relevant to CO2utilization.

关键词： Nanorods

Exploring the novel role of oligodendrocyte precursor cells in phagocytosis:beyond myelinogenesis

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Neural Regeneration research 2025年第2期20卷 473-474页

作者： Gen Hamanaka Ken Arai Neuroprotection research laboratories Departments of Radiology and NeurologyMassachusetts General Hospital and Harvard Medical SchoolCharlestownMAUSA

Roles of oligodendrocyte precursor cells in the central nervous system:Oligodendrocyte precursor cells(OPCs)have long been recognized for their critical role as precursors to oligodendrocytes,the primary myelin-producing *** precursors,OPCs mature and differentiate into oligodendrocytes,which contribute significantly to the formation of myelin sheaths around *** myelination,which is critical for the conduction of salutatory nerve impulses in the cerebral white matter,underscores the classical role of oligodendrocytes in central nervous system(CNS)***,because oligodendrocytes are differentiated cells that cannot proliferate.

关键词： critical system conduction

When AI meets sustainable 6G

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Science China(Information Sciences) 2025年第1期68卷 4-22页

作者： Xiaohu YOU Yongming HUANG Cheng ZHANG Jiaheng WANG Hao YIN Hequan WU National Mobile Communications research Laboratory Southeast University Purple Mountain laboratories Chinese Academy of Military Science China Information Communication Technologies Group

Sixth-generation(6G) networks are anticipated to achieve transformative advancements, characterized by extreme connectivity, deep integration with artificial intelligence(AI) and sensing, and airground integration. The evolution of 6G exhibits two major trends: ubiquitous intelligence and sustainability. The former aims to embed state-of-the-art AI technology into the 6G network, from the physical layers to applications, while the latter emphasizes reducing energy consumption while enhancing network performance to address environmental concerns. Despite the amazing progress in recent years, AI advancements come with substantial increases in data and computational overhead, posing critical challenges for integrating AI into sustainable 6G networks. First, high energy consumption from large datasets and heavyweight AI models contradicts6G's green goals. Second, the precise collection of large datasets, message delivery latency, and inference delays in AI models pose challenges for real-time tasks in 6G. Third, the uninterpretability and unpredictability of AI models complicate meeting the stringent requirements for controllable transmission in dynamic wireless environments. Addressing these challenges and achieving sustainable 6G with ubiquitous intelligence calls for a revolutionary design of 6G architecture and AI frameworks. To this end, this paper introduces a novel and practical methodology for green, real-time, and controllable 6G native intelligence,starting with knowledge graph(KG) analysis to extract small but critical datasets, followed by the development of distributed lightweight AI models, and the use of digital twins(DTs) to create precise replicas of physical 6G networks. This leads to a pervasive multi-level(PML)-AI framework supported by a task-centric, three-layer 6G architecture. The AI framework operates through non-real-time and real-time cycles, leveraging three key technologies: wireless data KGs for efficient data management,lightweight AI mode

关键词： artificial intelligence sustainable 6G green real-time controllable

Identification of a dual functional betulinic acid analog for the treatment of osteoarthritis by phenotypic screening

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Science China Life Sciences 2025年第1期68卷 300-302页

作者： Ze-Min Lin Mai Xiang Wen-Hui Wei Shu-Hui Fan Li Chen Jie Wang Xiao-Qian Yang Chun-Hao Yang Shi-Jun He Jian-Ping Zuo Laboratory of Immunopharmacology State Key Laboratory of Drug ResearchShanghai Institute of Materia MedicaChinese Academy of Sciences School of Pharmacy University of Chinese Academy of Sciences School of Pharmacy Nanjing University of Chinese Medicine State Key Laboratory of Drug research Department of Medicinal ChemistryShanghai Institute of Materia MedicaChinese Academy of Sciences Innovation research Institute of Traditional Chinese Medicine Shanghai University of Traditional Chinese Medicine Experiment Center for Science and Technology Shanghai University of Traditional Chinese Medicine

Dear Editor, Phenotypic drug discovery, which observes compound effects on physiology,has given way to targeting specific molecules, but has revived by using modern methods to find drugs based on therapeutic outcomes in disease models(Vincent et al., 2022). Osteoarthritis(OA) is a prevalent chronic joint disorder, primarily affecting knee joints, with osteoclast activation due to low-grade inflammation resulting in increased bone resorption and structural changes in the joint(Katz et al.,2021).

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