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Neuroscience Bulletin 2023年第11期39卷 1623-1637页

作者： Xueshan Cao Xiaoxiao Tang Chengyun Feng Jing Lin Huajie Zhang Qiong Liu Qihong Zheng Hongbin Zhuang Xukun Liu Haiying Li Naseer Ullah Khan Liming She College of Life Science and Oceanography Shenzhen UniversityShenzhen518060China College of Physics and Optoelectronics engineering Shenzhen UniversityShenzhen518060China Maternal and Child Health Hospital of Baoan Shenzhen518100China Department of Endocrinology Guiyang First People’s HospitalGuiyang550002China shenzhen-Hong Kong Institute of Brain Science-shenzhen Fundamental Research Institutions Shenzhen518055China shenzhen key laboratory of marine Biotechnology and Ecology Shenzhen518060China

Autism spectrum disorder(ASD)is one of the common neurodevelopmental disorders in children.Its etiology and pathogenesis are poorly understood.Previous studies have suggested potential changes in the complement and coagulation pathways in individuals with ASD.In this study,using multiple reactions monitoring proteomic technology,16 of the 33 proteins involved in this pathway were identified as differentially-expressed proteins in plasma between children with ASD and controls.Among them,CFHR3,C4BPB,C4BPA,CFH,C9,SERPIND1,C8A,F9,and F11 were found to be altered in the plasma of children with ASD for the first time.SERPIND1 expression was positively correlated with the CARS score.Using the machine learning method,we obtained a panel composed of 12 differentially-expressed proteins with diagnostic potential for ASD.We also reviewed the proteins changed in this pathway in the brain and blood of patients with ASD.The complement and coagulation pathways may be activated in the peripheral blood of children with ASD and play a key role in the pathogenesis of ASD.

关键词： pathogenesis children complement

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中国碳收支:1980～2021年（英文）

Science Bulletin 2024年第1期 114-124页

作者：夏晓圣任培阳王旭辉刘丹陈修治丹利何斌何洪林居为民梁敏琪陆星劼彭静覃章才夏江周郑博魏静乐旭于贵瑞朴世龙袁文平 Jiangsu key laboratory of Atmospheric Environment Monitoring and Pollution Control Collaborative Innovation Center of Atmospheric Environment and Equipment Technology School of Environmental Science and Engineering Nanjing University of Information Science & Technology School of Atmospheric Sciences Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle Sun Yat-sen University Sino-French Institute for Earth System Science College of Urban and Environmental Sciences Peking University State key laboratory of Tibetan Plateau Earth System Resources and Environment Institute of Tibetan Plateau Research Chinese Academy of Sciences key laboratory of Regional Climate-Environment for Temperate East Asia Institute of Atmospheric Physics Chinese Academy of Sciences State key laboratory of Earth Surface Processes and Resource Ecology College of Global Change and Earth System Science Beijing Normal University Synthesis Research Center of China's Ecosystem Research Network Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences International Institute for Earth System Science Nanjing University Tianjin key laboratory of Water Resources and Environment Tianjin Normal University Institute of Environment and Ecology Tsinghua Shenzhen International Graduate School Tsinghua University

As one of the world’s largest emitters of greenhouse gases,China has set itself the ambitious goal of achieving carbon peaking and carbon neutrality.Therefore,it is crucial to quantify the magnitude and trend of sources and sinks of atmospheric carbon dioxide(CO2),and to monitor China’s progress toward these goals.Using state-of-the-art datasets and models,this study comprehensively estimated the anthropogenic CO2emissions from energy,industrial processes and product use,and waste along with natural sources and sinks of CO2for all of China during 1980-2021.To recognize the differences among various methods of estimating greenhouse emissions,the estimates are compared with China’s National Greenhouse Gas Inventories(NGHGIs) for 1994,2005,2010,2012,and 2014.Anthropogenic CO2emissions in China have increased by 7.39 times from 1980 to 12.77 Gt CO2a-1in 2021.While benefiting from ecological projects(e.g., Three Norths Shelter Forest System Project),the land carbon sink in China has reached 1.65 Gt CO2a-1averaged through 2010-2021,which is almost 15.81 times that of the carbon sink in the 1980s.On average,China’s terrestrial ecosystems offset 14.69%±2.49% of anthropogenic CO2emissions through 2010-2021.Two provincial-level administrative regions of China,Xizang and Qinghai,have achieved carbon neutrality according to our estimates,but nearly half of the administrative regions of China have terrestrial carbon sink offsets of less than 10% of anthropogenic CO2emissions.This study indicated a high level of consistency between NGHGIs and various datasets used for estimating fossil CO2emissions,but found notable differences for land carbon sinks.Future estimates of the terrestrial carbon sinks of NGHGIs urgently need to be verified with process-based models which integrate the comprehensive carbon cycle processes.

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Advances in machine learning-and artificial intelligence-assisted material design of steels

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International Journal of Minerals,Metallurgy and Materials 2023年第6期30卷 1003-1024页

作者： Guangfei Pan Feiyang Wang Chunlei Shang Honghui Wu Guilin Wu Junheng Gao Shuize Wang Zhijun Gao Xiaoye Zhou Xinping Mao Beijing Advanced Innovation Center for Materials Genome engineering University of Science and Technology BeijingBeijing 100083China Yangjiang Branch Guangdong Laboratory for Materials Science and Technology(Yangjiang Advanced Alloys Laboratory)Yangjiang 529500China Guangdong Province key laboratory of Durability for marine Civil engineering School of Civil EngineeringShenzhen UniversityShenzhen 518060China

With the rapid development of artificial intelligence technology and increasing material data,machine learning-and artificial intelligence-assisted design of high-performance steel materials is becoming a mainstream paradigm in materials science.Machine learning methods,based on an interdisciplinary discipline between computer science,statistics and material science,are good at discovering correlations between numerous data points.Compared with the traditional physical modeling method in material science,the main advantage of machine learning is that it overcomes the complex physical mechanisms of the material itself and provides a new perspective for the research and development of novel materials.This review starts with data preprocessing and the introduction of different machine learning models,including algorithm selection and model evaluation.Then,some successful cases of applying machine learning methods in the field of steel research are reviewed based on the main theme of optimizing composition,structure,processing,and performance.The application of machine learning methods to the performance-oriented inverse design of material composition and detection of steel defects is also reviewed.Finally,the applicability and limitations of machine learning in the material field are summarized,and future directions and prospects are discussed.

关键词： machine learning data-driven design new research paradigm high-performance steel

Electroreduction of Carbon Dioxide by Heterogenized Cofacial Porphyrins

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Transactions of Tianjin University 2022年第1期28卷 73-79页

作者： Pengfei Tian Jianjun Su Yun Song Ruquan Ye Minghui Zhu State key laboratory of Chemical engineering School of Chemical EngineeringEast China University of Science and TechnologyShanghai 200237China State key laboratory of marine Pollution Department of ChemistryCity University of Hong KongHong Kong 999077China City University of Hong Kong shenzhen Research Institute Shenzhen 518057China

Great attention has been paid to cofacial porphyrins due to their many unique advantages over their monomeric analogs.However,their synthesis is usually complicated.In this work,a facile impregnation method for preparing heterogenized,cofacially stacked porphyrins is proposed.An anionic porphyrin is introduced as an underlayer for immobilization of cationic cobalt porphyrin via electrostatic force.The metal center of the underlying molecule contributes to the electronic structure of the upper cationic cobalt porphyrin.Screening reveals the anionic iron porphyrin to be the most efficient underlayer molecule,lowering the activation energy barrier of CO_(2) electroreduction,with an improved turnover frequency by 74%to8.0 s~(-1)at-0.6 V versus RHE.

关键词： CO_(2)RR Porphyrin Cofacial Heterogenization

Innovations and challenges of polyphenol-based smart drug delivery systems

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Nano Research 2022年第9期15卷 8156-8184页

作者： Yanan Wang Jingwen Zhang Yi Zhao Minju Pu Xinyu Song Liangmin Yu Xuefeng Yan Jun Wu Zhiyu He key laboratory of marine Chemistry Theory and Technology Ministry of Education College of Chemistry and Chemical EngineeringOcean University of ChinaQingdao 266100China School of Biomedical engineering Sun Yat-sen UniversityShenzhen 518107China

Polyphenols,as widely existing natural bioactive products,provide a vast array of advanced biomedical applications attributing to their potential health benefits that linked to antioxidant,anti-inflammatory,immunoregulatory,neuroprotective,cardioprotective function,etc.The polyphenol compounds could dynamically interact and bind with diverse species(such as polymers,metal ions,biomacromolecules,etc.)via multiple interactions,including hydrogen bond,hydrophobic,π–π,and cation–πinteractions due to their unique chemical polyphenolic structures,providing far-ranging strategies for designing of polyphenol-based vehicles.Natural polyphenols emerged as multifaceted players,acting either as inherent therapeutics delivered to combat diverse diseases or as pivotal assemblies of drug delivery vehicles.In this review,we focused on the rational design and application of metal-phenolic network(MPN)based delivery systems,polyphenol-based coating films,polyphenol hollow capsules,polyphenolincorporated hydrogels,and polymer-polyphenol-based nanoparticles(NPs)in various diseases therapeutic,including cancer,infection,cardiovascular disease,neurodegenerative disease,etc.Additionally.the versatility and mechanisms of polyphenols in the field of biomacromolecules(e.g.,protein,peptide,nucleic acid,etc.)delivery and cell therapy have been comprehensively summarized.Going through the literature review,the remaining challenges of polyphenol-containing nanosystems need to be addressed are involved,including long-term stability,biosafety in vivo,feasibility of scale-up,etc.,which may enlighten the further developments of this field.This review provides perspectives in utilizing natural polyphenol-based biomaterials to rationally design next generation versatile drug delivery system in the field of biomedicine,which eventually benefits public health.

关键词： polymer-phenolic nanoparticles metal-phenolic network metal-phenolic coatings metal-phenolic hollow capsules polyphenol-protein interactions

Metabolic tuning of a stable microbial community in the surface oligotrophic Indian Ocean revealed by integrated meta-omics

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marine Life Science & Technology 2022年第2期4卷 277-290页

作者： Zhang-Xian Xie Ke-Qiang Yan Ling-Fen Kong Ying-Bao Gai Tao Jin Yan-Bin He Ya-Yu Wang Feng Chen Lin Lin Zhi-Long Lin Hong-Kai Xu Zong-Ze Shao Si-Qi Liu Da-Zhi Wang State key laboratory of marine Environmental Science/College of the Environment and Ecology Xiamen UniversityXiamen361005China College of Ocean and Earth Sciences Xiamen UniversityXiamen361005China Southern marine Science and engineering Guangdong laboratory(Zhuhai) Sun Yat-Sen UniversityZhuhai519082China BGI-shenzhen Beishan Industrial Zone 11th BuildingShenzhen518083China BGI Education Center University of Chinese Academy of SciencesShenzhen518083China key laboratory of marine Genetic Resources Third Institute of OceanographyMinistry of Natural Resources of ChinaXiamen361005China State key laboratory Breeding Base of marine Genetic Resources/Fujian key laboratory of marine Genetic Resources Xiamen361005China Institute of marine and Environmental Technology University of Maryland Center for Environmental ScienceBaltimoreMD21202USA

Understanding the mechanisms,structuring microbial communities in oligotrophic ocean surface waters remains a major ecological endeavor.Functional redundancy and metabolic tuning are two mechanisms that have been proposed to shape microbial response to environmental forcing.However,little is known about their roles in the oligotrophic surface ocean due to less integrative characterization of community taxonomy and function.Here,we applied an integrated meta-omics-based approach,from genes to proteins,to investigate the microbial community of the oligotrophic northern Indian Ocean.Insignificant spatial variabilities of both genomic and proteomic compositions indicated a stable microbial community that was dominated by Prochlorococcus,Synechococcus,and SAR11.However,fine tuning of some metabolic functions that are mainly driven by salinity and temperature was observed.Intriguingly,a tuning divergence occurred between metabolic potential and activity in response to different environmental perturbations.Our results indicate that metabolic tuning is an important mechanism for sustaining the stability of microbial communities in oligotrophic oceans.In addition,integrated meta-omics provides a powerful tool to comprehensively understand microbial behavior and function in the ocean.

关键词： Microbial community Metabolic tuning Metaproteomics Metagenomics Oligotrophic ocean

Transgenerational bone toxicity in F3 medaka (Oryzias latipes) induced by ancestral benzo[a]pyrene exposure: Cellular and transcriptomic insights

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Journal of Environmental Sciences 2023年第5期127卷 336-348页

作者： Jiezhang Mo Miles Teng Wan DorisWai-Ting Au Jingchun Shi Nathan Tam Xian Qin Napo K.M.Cheung Keng Po Lai Christoph Winkler Richard Yuen-Chong Kong Frauke Seemann Southern marine Science and engineering Guangdong laboratory(Guangzhou) Guangzhou 510000China shenzhen key laboratory for the Sustainable Use of marine Biodiversity Research Centre for the Oceans and Human HealthShenzhen Research InstituteCity University of Hong KongShenzhen 518057China State key laboratory of marine Pollution and Department of Chemistry City University of Hong KongHong Kong SARChina laboratory of Environmental Pollution and Integrative Omics Guilin Medical UniversityHuan Cheng North 2nd Road 109Guilin 541004China Department of Biological Sciences National University of Singapore119077Singapore Center for Coastal Studies and Department of Life Sciences Texas A&M University-Corpus ChristiCorpus ChristiTexas 78412USA

Benzo[a]pyrene(BaP),a ubiquitous pollutant,raises environmental health concerns due to induction of bone toxicity in the unexposed offspring.Exposure of F0 ancestor medaka(Oryzias latipes)to 1μg/L BaP for 21 days causes reduced vertebral bone thickness in the unexposed F3 male offspring.To reveal the inherited modifications,osteoblast(OB)abundance and molecular signaling pathways of transgenerational BaP-induced bone thinning were assessed.Histomorphometric analysis showed a reduction in OB abundance.Analyses of the miRNA and mRNA transcriptomes revealed the dysregulation of Wnt signaling(frzb/ola-miR-1–3p,sfrp5/ola-miR-96–5p/miR-455–5p)and bone morphogenetic protein(Bmp)signaling(bmp3/ola-miR-96–5p/miR-181b-5p/miR-199a-5p/miR-205–5p/miR-455–5p).Both pathways are major indicators of impaired bone formation,while the altered Rank signaling in osteoclasts(c-fos/miR-205–5p)suggests a potentially augmented bone resorption.Interestingly,a typical BaP-responsive pathway,the Nrf2-mediated oxidative stress response(gst/ola-miR-181b-5p/miR-199a-5p/miR-205),was also affected.Moreover,mRNA levels of epigenetic modification enzymes(e.g.,hdac6,hdac7,kdm5b)were found dysregulated.The findings indicated that epigenetic factors(e.g.,miRNAs,histone modifications)may directly regulate the expression of genes associated with transgenerational BaP bone toxicity and warrants further studies.The identified candidate genes and miRNAs may serve as potential biomarkers for BaP-induced bone disease and as indicators of historic exposures in wild fish for conservation purposes.

关键词： Polycyclic aromatic hydrocarbons (PAHs) Transcriptome Impaired bone formation Molecular pathways MicroRNAs Medaka(Oryzias latipes)

Improved material descriptors for bulk modulus in intermetallic compounds via machine learning

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Rare Metals 2023年第7期42卷 2396-2405页

作者： De-Xin Zhu Kun-Ming Pan Yuan Wu Xiao-Ye Zhou Xiang-Yue Li Yong-Peng Ren Sai-Ru Shi Hua Yu Shi-Zhong Wei Hong-Hui Wu Xu-Sheng Yang National Joint engineering Research Center for Abrasion Control and Molding of Metal Materials Henan Key Laboratory of High-Temperature Structural and Functional MaterialsHenan University of Science and TechnologyLuoyang471003China Longmen laboratory Luoyang471003China State key laboratory for Advanced Metals and Materials University of Science and Technology BeijingBeijing100083China Guangdong Province key laboratory of Durability for marine Civil engineering School of Civil EngineeringShenzhen UniversityShenzhen518060China Department of Industrial and Systems engineering The Hong Kong Polytechnic UniversityHong Kong999077China

Bulk modulus is an important mechanical property in the optimal design and selection of intermetallic compounds.In this study,bulk modulus datasets of intermetallic compounds were collected,and the features affecting the bulk modulus of intermetallics were screened via feature engineering.Three features B_(cal),dB_(avg),and TIE(corresponding to calculated bulk modulus,mean bulk modulus,and third ionization energy,respectively)were found to be the dominant factors influencing bulk modulus and can be extended to other multi-component alloys.Particularly,we predicted the bulk modulus with an accuracy of 95%using surrogate machine learning models with the selected features,and these features were also demonstrated to be effective for high-entropy alloys.Moreover,symbolic regression provided an expression for the relationship between bulk modulus and the screened features.The machine learning models provide a new approach for optimizing and predicting the bulk moduli of intermetallic compounds.

关键词： Bulk modulus Intermetallic compounds Machine learning Symbolic regression

High sensitivity ratiometric fluorescence temperature sensing using the microencapsulation of CsPbBr3 and K2SiF6:Mn4+phosphor

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Chinese Chemical Letters 2022年第11期33卷 4798-4802页

作者： Jingwen Jin Jie Lin Yipeng Huang Linchun Zhang Yaqi Jiang Dongjie Tian Fangyuan Lin Yiru Wang Xi Chen Department of Chemistry and the MOE key laboratory of Spectrochemical Analysis&Instrumentation College of Chemistry and Chemical EngineeringXiamen UniversityXiamen 361005China State key laboratory of marine Environmental Science Xiamen UniversityXiamen 361005China shenzhen Research Institute of Xiamen University Shenzhen 518000China

A dual emission sensing film has been prepared for colorimetric temperature sensing using CsPbBr_(3)perovskite nanocrystals(CsPbBr_(3)NCs)and manganese doped potassium fluorosilicate(K_(2)SiF_(6):Mn^(4+),KSF)encapsulated in polystyrene by a microencapsulation strategy.The CsPbBr_(3)-KSF-PS film shows good temperature sensing response from 30℃to 70℃,with a relative temperature sensitivity(Sr)up to 10.31%℃^(−1) at 45℃.Meanwhile,the film maintains more than 95%intensity after 6 heating-cooling cycles and keeps its fluorescence characteristics after 3 months.The film can be used to monitor temperature change by naked eye under a UV lamp.In particular,the temperature discoloration point of the sensing film can be controlled by the ratio change of CsPbBr_(3):KSF to expand its applications.The study of the CsPbBr_(3)-KSF-PS sensing mechanism in this work is helpful to provide effective strategies for the design of reliable,high sensitivity and stable temperature sensing system using CsPbBr_(3)NCs.

关键词： Ratiometric fluorescence sensing High sensitivity Perovskite nanocrystals Temperature Microencapsulation

Genomic selection of orange-spotted grouper(Epinephelus coioides)based on multiplex PCR enrichment capture sequencing

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Aquaculture and Fisheries 2023年第6期8卷 681-688页

作者： Xinxin Shan Xinhui Zhang Zhiqiang Ruan Jieming Chen Qiong Shi Junmin Xu Xinxin You shenzhen key Lab of marine Genomics Guangdong Provincial Key Lab of Molecular Breeding in Marine Economic AnimalsBGI Academy of Marine SciencesBGI MarineBGIShenzhen518083China Southern marine Science and engineering Guangdong laboratory(Zhuhai) State Key Laboratory of BiocontrolSchool of Marine SciencesSun Yat-Sen UniversityGuangzhou510275China College of Life Sciences University of Chinese Academy of SciencesBeijing100049China

Orange spotted grouper(Epinephelus coioides)is an important mariculture fish,and genomic breeding of this grouper species has been hindered due to lack of efficient genotyping tools.Here,we developed a single nucleotide polymorphism(SNP)genotyping technology based on multiplex PCR enrichment capture sequencing,which mainly aims at target area for high-throughput sequencing,and 741 SNPs were designed for genomic selection(GS)of growth and ammonia tolerance traits at the same time.The multiplex PCR enrichment capture sequencing assay showed that the genotyping efficiency was more than 99%in the orange-spotted grouper and the predictive accuracy of body weight and ammonia tolerance traits was 82%and 96%,respectively.More importantly,the average identity of the sequences with these SNPs aligned to the genomes of giant grouper(E.lanceolatus)and brown-marbled grouper(E.fuscoguttatus)were both over 96%.Test data showed that the SNP genotyping efficiency was more than 94%in both giant grouper and brown-marbled grouper.In summary,these results indicated that the development of SNP loci and genotyping approach based on the multiple PCR enrichment capture sequencing are suitable for GS of growth and ammonia tolerance traits in various grouper species,and it would provide technical support for practical grouper breeding.

关键词： Grouper SNP genotyping Approach Multiple PCR enrichment Capture sequencing Genomic selection