The cerebellum is receiving increasing attention for its cognitive,emotional,and social functions,as well as its unique metabolic profiles.Cerebellar microglia exhibit specialized and highly immunogenic phenotypes und...The cerebellum is receiving increasing attention for its cognitive,emotional,and social functions,as well as its unique metabolic profiles.Cerebellar microglia exhibit specialized and highly immunogenic phenotypes under both physiological and pathological conditions.These immune cells communicate with intrinsic and systemic factors and contribute to the structural and functional compartmentalization of the cerebellum.In this review,we discuss the roles of microglia in the cerebellar microenvironment,neuroinflammation,cerebellar adaptation,and neuronal activity,the associated molecular and cellular mechanisms,and potential therapeutic strategies targeting cerebellar microglia in the context of neuroinflammation.Future directions and unresolved questions in this field are further highlighted,particularly regarding therapeutic interventions targeting cerebellar microglia,functional mechanisms and activities of microglia in the cerebellar circuitry,neuronal connectivity,and neurofunctional outcomes of their activity.Cerebellar morphology and neuronal performance are influenced by both intrinsic and systemic factors that are actively monitored by microglia in both healthy and diseased states.Under pathological conditions,local subsets of microglia exhibit diverse responses to the altered microenvironment that contribute to the structural and functional compartmentalization of the cerebellum.Microglia in the cerebellum undergo early maturation during the embryonic stage and display specialized,highly immunogenic phenotypes.In summary,cerebellar microglia have the capacity to serve as regulatory tools that influence outcomes across a wide range of neurological and systemic conditions,including neurodevelopmental,neurodegenerative,metabolic,and stress-related disorders.展开更多
Nano-zinc oxides(ZnO)demonstrate remarkable antibacterial properties.To further enhance the corrosion resistance and antibacterial efficiency of magnesium alloy micro-arc oxidation(MAO)coatings,this study investigates...Nano-zinc oxides(ZnO)demonstrate remarkable antibacterial properties.To further enhance the corrosion resistance and antibacterial efficiency of magnesium alloy micro-arc oxidation(MAO)coatings,this study investigates the preparation of ZnO-containing micro-arc oxidation coatings with dual functionality by incorporating nano-ZnO into MAO electrolyte.The influence of varying ZnO concentrations on the microstructure,corrosion resistance,and antibacterial properties of the coating was examined through microstructure analysis,immersion tests,electrochemical experiments,and antibacterial assays.The findings revealed that the addition of nano-ZnO significantly enhanced the corrosion resistance of the MAO-coated alloy.Specifically,when the ZnO concentration in the electrolyte was 5 g/L,the corrosion rate was more than ten times lower compared to the MAO coatings without ZnO.Moreover,the antibacterial efficacy of ZnO+MAO coating,prepared with a ZnO concentration of 5 g/L,surpassed 95%after 24 h of co-culturing with Staphylococcus aureus(S.aureus).The nano-ZnO+MAO-coated alloy exhibited exceptional degradation resistance,corrosion resistance,and antibacterial effectiveness.展开更多
信息通信技术(information and communications technology,ICT)等的发展使现代地图面临着机遇和挑战:地图趋向数字虚拟空间方向发展,地图学的研究方法、主题与传统地图学大相径庭,地图虚拟空间的理论还有很大的发展空间,同时互联网技术...信息通信技术(information and communications technology,ICT)等的发展使现代地图面临着机遇和挑战:地图趋向数字虚拟空间方向发展,地图学的研究方法、主题与传统地图学大相径庭,地图虚拟空间的理论还有很大的发展空间,同时互联网技术(internet technology,IT)领域的学科跨界迫使地图逐渐发展成为互联网产品的附属物,内忧外患的双重夹击使得地图学亟待完善和更新理论。地图学发展的难题促使学者向其他领域进行探索。计算机游戏通常具有明显的地理意义,"数字+文化"的发展将游戏推向高新技术的前列,游戏地图则是现代ICT技术和地图的合体。以游戏地图的结构为研究对象,以游戏地图的维度、交互性、叙事探索性和文化传播性来探究虚拟空间的特点、本质及对现实物理世界的启示,发掘其对地图理论的扩展,从而完善ICT时代地图学的知识和理论,促进地图学的发展。展开更多
Dear Editor,It is now well established that optogenetic stimulation can achieve precise intervention and modulate the activity of local neurons or neural circuits in the brain.Although this technique holds promise for...Dear Editor,It is now well established that optogenetic stimulation can achieve precise intervention and modulate the activity of local neurons or neural circuits in the brain.Although this technique holds promise for clinical therapy for neurological and psychiatric disorders,it requires the expression of lightsensitive proteins(such as channel rhodopsin)or photoactivatable chemicals(such as caged neurotransmitters)in the targeted brain regions[1].展开更多
This review presents a comprehensive and forward-looking analysis of how Large Language Models(LLMs)are transforming knowledge discovery in the rational design of advancedmicro/nano electrocatalyst materials.Electroca...This review presents a comprehensive and forward-looking analysis of how Large Language Models(LLMs)are transforming knowledge discovery in the rational design of advancedmicro/nano electrocatalyst materials.Electrocatalysis is central to sustainable energy and environmental technologies,but traditional catalyst discovery is often hindered by high complexity,fragmented knowledge,and inefficiencies.LLMs,particularly those based on Transformer architectures,offer unprecedented capabilities in extracting,synthesizing,and generating scientific knowledge from vast unstructured textual corpora.This work provides the first structured synthesis of how LLMs have been leveraged across various electrocatalysis tasks,including automated information extraction from literature,text-based property prediction,hypothesis generation,synthesis planning,and knowledge graph construction.We comparatively analyze leading LLMs and domain-specific frameworks(e.g.,CatBERTa,CataLM,CatGPT)in terms of methodology,application scope,performance metrics,and limitations.Through curated case studies across key electrocatalytic reactions—HER,OER,ORR,and CO_(2)RR—we highlight emerging trends such as the growing use of embedding-based prediction,retrieval-augmented generation,and fine-tuned scientific LLMs.The review also identifies persistent challenges,including data heterogeneity,hallucination risks,lack of standard benchmarks,and limited multimodal integration.Importantly,we articulate future research directions,such as the development of multimodal and physics-informedMatSci-LLMs,enhanced interpretability tools,and the integration of LLMswith selfdriving laboratories for autonomous discovery.By consolidating fragmented advances and outlining a unified research roadmap,this review provides valuable guidance for both materials scientists and AI practitioners seeking to accelerate catalyst innovation through large language model technologies.展开更多
基金supported by grants from STI2030-Major Projects,No.2021ZD0204000(to YS)Key Strategic Science and Technology Cooperation Project of the Ministry of Science and Technology of China,No.SQ2023YFE0201430(to YS)+1 种基金the National Natural Science Foundation of China,Nos.31820103005(to YS),32200620(to LW)the Natural Science Foundation of Zhejiang Province of China,No.LZ24C090003(to YS)。
文摘The cerebellum is receiving increasing attention for its cognitive,emotional,and social functions,as well as its unique metabolic profiles.Cerebellar microglia exhibit specialized and highly immunogenic phenotypes under both physiological and pathological conditions.These immune cells communicate with intrinsic and systemic factors and contribute to the structural and functional compartmentalization of the cerebellum.In this review,we discuss the roles of microglia in the cerebellar microenvironment,neuroinflammation,cerebellar adaptation,and neuronal activity,the associated molecular and cellular mechanisms,and potential therapeutic strategies targeting cerebellar microglia in the context of neuroinflammation.Future directions and unresolved questions in this field are further highlighted,particularly regarding therapeutic interventions targeting cerebellar microglia,functional mechanisms and activities of microglia in the cerebellar circuitry,neuronal connectivity,and neurofunctional outcomes of their activity.Cerebellar morphology and neuronal performance are influenced by both intrinsic and systemic factors that are actively monitored by microglia in both healthy and diseased states.Under pathological conditions,local subsets of microglia exhibit diverse responses to the altered microenvironment that contribute to the structural and functional compartmentalization of the cerebellum.Microglia in the cerebellum undergo early maturation during the embryonic stage and display specialized,highly immunogenic phenotypes.In summary,cerebellar microglia have the capacity to serve as regulatory tools that influence outcomes across a wide range of neurological and systemic conditions,including neurodevelopmental,neurodegenerative,metabolic,and stress-related disorders.
基金supported by the National Natural Science Foundation of China(No.52001034)the China Postdoctoral Science Foundation(No.2023M731677)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.KYCX23_3032).
文摘Nano-zinc oxides(ZnO)demonstrate remarkable antibacterial properties.To further enhance the corrosion resistance and antibacterial efficiency of magnesium alloy micro-arc oxidation(MAO)coatings,this study investigates the preparation of ZnO-containing micro-arc oxidation coatings with dual functionality by incorporating nano-ZnO into MAO electrolyte.The influence of varying ZnO concentrations on the microstructure,corrosion resistance,and antibacterial properties of the coating was examined through microstructure analysis,immersion tests,electrochemical experiments,and antibacterial assays.The findings revealed that the addition of nano-ZnO significantly enhanced the corrosion resistance of the MAO-coated alloy.Specifically,when the ZnO concentration in the electrolyte was 5 g/L,the corrosion rate was more than ten times lower compared to the MAO coatings without ZnO.Moreover,the antibacterial efficacy of ZnO+MAO coating,prepared with a ZnO concentration of 5 g/L,surpassed 95%after 24 h of co-culturing with Staphylococcus aureus(S.aureus).The nano-ZnO+MAO-coated alloy exhibited exceptional degradation resistance,corrosion resistance,and antibacterial effectiveness.
文摘信息通信技术(information and communications technology,ICT)等的发展使现代地图面临着机遇和挑战:地图趋向数字虚拟空间方向发展,地图学的研究方法、主题与传统地图学大相径庭,地图虚拟空间的理论还有很大的发展空间,同时互联网技术(internet technology,IT)领域的学科跨界迫使地图逐渐发展成为互联网产品的附属物,内忧外患的双重夹击使得地图学亟待完善和更新理论。地图学发展的难题促使学者向其他领域进行探索。计算机游戏通常具有明显的地理意义,"数字+文化"的发展将游戏推向高新技术的前列,游戏地图则是现代ICT技术和地图的合体。以游戏地图的结构为研究对象,以游戏地图的维度、交互性、叙事探索性和文化传播性来探究虚拟空间的特点、本质及对现实物理世界的启示,发掘其对地图理论的扩展,从而完善ICT时代地图学的知识和理论,促进地图学的发展。
基金supported by grants from the Key Strategic Science and Technology Cooperation Project of the Ministry of Science and Technology of China(2023YFE0206800)the National Natural Science Foundation of China(81625006,31820103005,32200620,32170976,81971874)+1 种基金Zhejiang Province Natural Science Foundation of China(LZ24C090003 and LY21C090003)the Peak Discipline Cultivation Program of Zhejiang University School of Basic Medicine.
文摘Dear Editor,It is now well established that optogenetic stimulation can achieve precise intervention and modulate the activity of local neurons or neural circuits in the brain.Although this technique holds promise for clinical therapy for neurological and psychiatric disorders,it requires the expression of lightsensitive proteins(such as channel rhodopsin)or photoactivatable chemicals(such as caged neurotransmitters)in the targeted brain regions[1].
文摘This review presents a comprehensive and forward-looking analysis of how Large Language Models(LLMs)are transforming knowledge discovery in the rational design of advancedmicro/nano electrocatalyst materials.Electrocatalysis is central to sustainable energy and environmental technologies,but traditional catalyst discovery is often hindered by high complexity,fragmented knowledge,and inefficiencies.LLMs,particularly those based on Transformer architectures,offer unprecedented capabilities in extracting,synthesizing,and generating scientific knowledge from vast unstructured textual corpora.This work provides the first structured synthesis of how LLMs have been leveraged across various electrocatalysis tasks,including automated information extraction from literature,text-based property prediction,hypothesis generation,synthesis planning,and knowledge graph construction.We comparatively analyze leading LLMs and domain-specific frameworks(e.g.,CatBERTa,CataLM,CatGPT)in terms of methodology,application scope,performance metrics,and limitations.Through curated case studies across key electrocatalytic reactions—HER,OER,ORR,and CO_(2)RR—we highlight emerging trends such as the growing use of embedding-based prediction,retrieval-augmented generation,and fine-tuned scientific LLMs.The review also identifies persistent challenges,including data heterogeneity,hallucination risks,lack of standard benchmarks,and limited multimodal integration.Importantly,we articulate future research directions,such as the development of multimodal and physics-informedMatSci-LLMs,enhanced interpretability tools,and the integration of LLMswith selfdriving laboratories for autonomous discovery.By consolidating fragmented advances and outlining a unified research roadmap,this review provides valuable guidance for both materials scientists and AI practitioners seeking to accelerate catalyst innovation through large language model technologies.
