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Mass extinctions, their causes and consequences: an interview with Douglas H.Erwin and Shuzhong Shen

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National Science Review 2024年第1期11卷 66-70页

作者： Shucheng xie State Key Laboratory of Biogeology and Environmental Geology China University of Geosciences at Wuhan

‘Mass extinctions’ have been a hot topic for several decades. What triggers a mass extinction? How does a mass extinction impact the evolution of life? How does our ecosystem recover after a mass extinction? These questions attracted the interest of both scientists and the public alike.NSR spoke to two renowned researchers in the field of mass extinctions: Prof. Douglas H. Erwin from the National Museum of Natural History of the USA, and Prof. Shuzhong Shen from Nanjing University, China.

关键词： Stratigraphy

Deformable Catalytic Material Derived from Mechanical Flexibility for Hydrogen Evolution Reaction

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Nano-Micro Letters 2024年第2期16卷 287-311页

作者： Fengshun Wang Lingbin xie Ning Sun Ting Zhi Mengyang Zhang Yang Liu Zhongzhong Luo Lanhua yi Qiang Zhao Longlu Wang College of Electronic and Optical Engineering&College of Flexible Electronics(Future Technology) Nanjing University of Posts&Telecommunications(NJUPT)9 WenyuanNanjing 210023People’s Republic of China Key Laboratory of Environmentally Friendly Chemistry and Applications of Ministry of Education School of ChemistryXiangtan UniversityXiangtan 411105People’s Republic of China State Key Laboratory of Organic Electronics and Information Displays&Jiangsu Key Laboratory for Biosensors Institute of Advanced Materials(IAM)&Institute of Flexible Electronics(Future Technology)Nanjing University of Posts&Telecommunications9 WenyuanNanjing 210023People’s Republic of China

Deformable catalytic material with excellent flexible structure is a new type of catalyst that has been applied in various chemical reactions,especially electrocatalytic hydrogen evolution reaction(HER).In recent years,deformable catalysts for HER have made great progress and would become a research hotspot.The catalytic activities of deformable catalysts could be adjustable by the strain engineering and surface reconfiguration.The surface curvature of flexible catalytic materials is closely related to the electrocatalytic HER properties.Here,firstly,we systematically summarized self-adaptive catalytic performance of deformable catalysts and various micro–nanostructures evolution in catalytic HER process.Secondly,a series of strategies to design highly active catalysts based on the mechanical flexibility of lowdimensional nanomaterials were summarized.Last but not least,we presented the challenges and prospects of the study of flexible and deformable micro–nanostructures of electrocatalysts,which would further deepen the understanding of catalytic mechanisms of deformable HER catalyst.

关键词： Deformable catalytic material Micro-nanostructures evolution Mechanical flexibility Hydrogen evolution reaction

New insights into the effect of hard carbons microstructure on the diffusion of sodium ions into closed pores

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Chinese Chemical Letters 2024年第6期35卷 155-160页

作者： Mingxin Song Lijing xie Fangyuan Su Zonglin yi Quangui Guo Cheng-Meng Chen CAS Key Laboratory of Carbon Materials Institute of Coal ChemistryChinese Academy of SciencesTaiyuan 030001China University of Chinese Academy of Sciences Beijing 100049China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing 100049China

Closed pores formed in hard carbons play an essential role in sodium storage at plateau region.However,the effect of different structural features on the diffusion of sodium ions into closed pores remains unclear.Herein,a precursor reconstruction strategy is conducted to regulate carbon microstructures including interlayer spacing,defect concentration,and closed pore volume by changing the ratio of aromatic and polysaccharide components.Aromatic structure parts tend to develop disordered carbons with fewer defects,larger interlayer spacing,and smaller closed pore volume,while polysaccharide components prefer to form disordered carbons with more defects,smaller interlayer spacing,and larger closed pore volume.Through the correlation analysis of microstructure features and the sodium storage capacity below 0.1 V.It finds that the intercalation capacity is proportional to the ratio of pseudo-graphitic domains,whereas the pore filling capacity appeared at lower potential gradually decreases with the increasing defect concentration due to homo-ionic repulsion effect,without linear correlation with shortrange microcrystalline and closed pore volume.The optimized sample with suitable interlayer spacing and defect concentration exhibits a high plateau capacity of 241.7 m Ah/g.This work provides insights into the exploitation of closed pore sodium storage performance.

关键词： Precursor reconstruction Hard carbons Structural features Closed pore filling Sodium-ion batteries

Sulfated Cyclocarya paliurus polysaccharides exert immunomodulatory potential on macrophages via Toll-like receptor 4 mediated MAPK/NF-κB signaling pathways

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Food Science and Human Wellness 2024年第1期13卷 115-123页

作者： Yue Yu Haibin Zhu Mingyue Shen Qiang Yu yi Chen Shiru Mo Jianhua xie State Key Laboratory of Food Science and Technology Nanchang UniversityNanchang 330047China International Institute of Food Innovation Nanchang UniversityNanchang 330200China

The biological activity of plant polysaccharides can be enhanced by sulfated modification.In this study,the immunomodulatory effect of sulfated Cyclocarya paliurus polysaccharides(SCP3)on macrophages RAW264.7 and its potential molecular mechanism were investigated.Results showed that SCP3 at 25-100μg/m L increased viability and improved phagocytosis of RAW264.7 cells.Meanwhile,SCP3 could activate mitogen-activated protein kinase(MAPK)and nuclear factor kappa B(NF-κB)signaling pathways,which increased the phosphorylation of Erk1/2,JNK,p38 and NF-κB p65,promoting secretion of cytokines tumor necrosis factorα(TNF-α),interleukin 6(IL-6)and nitric oxide(NO)as well as the production of reactive oxygen species(ROS).In addition,Toll-like receptor 4(TLR4)receptor inhibitors were able to block the production of NO and TNF-αby SCP3-stimulated macrophages.Based on Western blot analysis and validation using specific inhibitors against MAPK and NF-κB signaling pathways,the results demonstrated that SCP3 induced macrophages activation and enhanced TNF-αand NO production via TLR4-mediated MAPK and NF-κB pathways.In summary,SCP3 has significant immunomodulatory potential.The underlying molecular mechanism was that SCP3 activates macrophages via TLR4 receptors to promote ROS production,which in turn activates the downstream MAPK/NF-κB signaling pathway and then increases the secretion levels of cytokines and NO.

关键词： Cyclocarya paliurus Sulfated polysaccharides Macrophages Immunomodulatory Mechanism

Targeted G-to-T base editing for generation of novel herbicide-resistance gene alleles in rice

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Journal of Integrative Plant Biology 2024年第6期66卷 1048-1051页

作者： yifu Tian Xinbo Li Jiyong xie Zai Zheng Rundong Shen Xuesong Cao Mugui Wang chao Dong Jian-Kang Zhu Ministry of Agriculture and Rural Affairs Key Laboratory of Gene Editing Technologies (Hainan) Institute of Crop Sciences and National Nanfan Research Institute Chinese Academy of Agricultural Sciences Hainan Seed Industry Laboratory Shanghai Center for Plant Stress Biology CAS Center for Excellence in Molecular Plant Sciences The Chinese Academy of Sciences University of Chinese Academy of Sciences Institute of Advanced Biotechnology and School of Medicine Southern University of Science and Technology

Deaminase-based cytosine base editors (CBEs) and adenine base editors (ABEs) induce C-to-T and A-to-G transitions, respectively, enabling single-nucleotide variants(SNVs) in plants for research and crop enhancement (Li et al.,2023a). The C-to-G base editors (CGBEs) and A-to-Y base editors (AYBEs), developed by incorporating glycosylases with CBEs and ABEs, expand the repertoire of base editing products, allowing C-to-T/G and A-to-T/G transversions in plants (Li et al., 2023b, 2023c; Sretenovic et a., 2021;

关键词： TOLERANCE

Tumor microenvironment of cancer stem cells:Perspectives on cancer stem cell targeting

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Genes & Diseases 2024年第3期11卷 275-302页

作者： Qianqian Guo yi Zhou Tianyuan xie yin Yuan Huilong Li Wanjin Shi Lufeng Zheng Xiaoman Li Wenzhou Zhang Department of Pharmacy The Affiliated Cancer Hospital of Zhengzhou University&Henan Cancer HospitalZhengzhouHenan 450003China Jiangsu Key Laboratory for Pharmacology and Safety Evaluation of Chinese Materia Medica School of PharmacyNanjing University of Chinese MedicineNanjingJiangsu 210023China School of Life Science and Technology Jiangsu Key Laboratory of Carcinogenesis and InterventionChina Pharmaceutical UniversityNanjingJiangsu 211198China

There are few tumor cell subpopulations with stem cell characteristics in tumor tis-sue,defined as cancer stem cells(CSCs)or cancer stem-like cells(CSLCs),which can recon-struct neoplasms with malignant biological behaviors such as invasiveness via self-renewal and unlimited generation.The microenvironment that CsCs depend on consists of various cellular components and corresponding medium components.Among these factors existing at a variety of levels and forms,cytokine networks and numerous signal pathways play an important role in signaling transduction.These factors promote or maintain cancer cell stem-ness,and participate in cancer recurrence,metastasis,and resistance.This review aims to summarize the recent molecular data concerning the multilayered relationship between CsCs and CsC-favorable microenvironments.We also discuss the therapeutic implications of target-ing this synergistic interplay,hoping to give an insight into targeting cancer cell stemness for tumortherapyandprognosis.

关键词： Cancer stem cells Cancerstem-like cells Cellular factors Non-cellularfactors Tumor microenvironment

Principal Model Analysis Based on Bagging PLS and PCA and Its Application in Financial Statement Fraud

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Journal of Systems Science and Information 2024年第2期12卷 212-228页

作者： Xiao LIANG Qiwei xie Chunyan LUO Liang TANG yi SUN School of Economics and Management Beijing University of TechnologyBeijing 100124China Shanghai Tongtu Semiconductor Technology Co. LtdShanghai 210203China School of Finance Anhui University of Finance&EconomicsBengbu 233000China

Motivated by the Bagging Partial Least Squares(Bagging PLS)and Principal Component Analysis(PCA)algorithms,a novel approach known as Principal Model Analysis(PMA)method is introduced in this paper.In the proposed PMA algorithm,the PCA and the Bagging PLS are combined.In this method,multiple PLS models are trained on sub-training sets,derived from the training set using the random sampling with replacement approach.The regression coefficients of all the sub-PLS models are fused in a joint regression coefficient matrix.The final projection direction is then estimated by performing the PCA on the joint regression coefficient matrix.Subsequently,the proposed PMA method is compared with other traditional dimension reduction methods,such as PLS,Bagging PLS,Linear discriminant analysis(LDA)and PLS-LDA.Experimental results on six public datasets demonstrate that our proposed method consistently outperforms other approaches in terms of classification performance and exhibits greater stability.Additionally,it is employed in the application of financial statement fraud identification.PMA and other five algorithms are utilized to financial statement fraud which concerned by the academic community,and the results indicate that the classification of PMA surpassed that of the other methods.

关键词： principal model analysis partial least squares principal component analysis dimension reduction ensemble learning financial statement fraud detection

Geochemistry and origins of hydrogen-containing natural gases in deep Songliao Basin,China:Insights from continental scientific drilling

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Petroleum Science 2024年第2期21卷 741-751页

作者： Shuang-Biao Han chao-Han Xiang Xin Du Lin-Feng xie Jie Huang Cheng-Shan Wang College of Geoscience and Surveying Engineering China University of Mining and TechnologyBeijing100083China State Key Laboratory of Biogeology and Environmental Geology China University of GeosciencesBeijing100083China

The different reservoirs in deep Songliao Basin have non-homogeneous lithologies and include multiple layers with a high content of hydrogen gas.The gas composition and stable isotope characteristics vary significantly,but the origin analysis of different gas types has previously been weak.Based on the geochemical parameters of gas samples from different depths and the analysis of geological settings,this research covers the diverse origins of natural gas in different strata.The gas components are mainly methane with a small amount of C_(2+),and non-hydrocarbon gases,including nitrogen(N_(2)),hydrogen(H_(2)),carbon dioxide(CO_(2)),and helium(He).At greater depth,the carbon isotope of methane becomes heavier,and the hydrogen isotope points to a lacustrine sedimentary environment.With increasing depth,the origins of N_(2)and CO_(2)change gradually from a mixture of organic and inorganic to inorganic.The origins of hydrogen gas are complex and include organic sources,water radiolysis,water-rock(Fe^(2+)-containing minerals)reactions,and mantle-derived.The shales of Denglouku and Shahezi Formations,as source rocks,provide the premise for generation and occurrence of organic gas.Furthermore,the deep faults and fluid activities in Basement Formation control the generation and migration of mantle-derived gas.The discovery of a high content of H_(2)in study area not only reveals the organic and inorganic association of natural-gas generation,but also provides a scientific basis for the exploration of deep hydrogen-rich gas.

关键词： Gas compositions Stable isotopes Gas origins Hydrogen gas Songliao Basin

TSC prediction and dynamic control of BOF steelmaking with state-of-the-art machine learning and deep learning methods

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Journal of Iron and Steel Research(International) 2024年第1期31卷 174-194页

作者： Tian-yi xie Cai-dong Zhang Quan-lin Zhou Zhi-qiang Tian Shuai Liu Han-jie Guo Material Technology Research Institute Hesteel GroupShijiazhuang050023HebeiChina Tangsteel Company Hesteel GroupTangshan063611HebeiChina School of Artificial Intelligence Beijing Technology and Business UniversityBeijing100048China School of Metallurgical and Ecological Engineering University of Science and Technology BeijingBeijing100083China

Mathematical(data-driven)models based on state-of-the-art(SOTA)machine learning and deep learning models and data collected from 12,786 heats were established to predict the values of temperature,sample,and carbon(TSC)test,including temperature of molten steel(TSC-Temp),carbon content(TSC-C)and phosphorus content(TSC-P),which made prepa-ration for eliminating the TSC test.To maximize the prediction accuracy of the proposed approach,various models with different inputs were implemented and compared,and the best models were applied to the production process of a Hesteel Group steelmaking plant in China in the field.The number of tabular features(hot metal information,scrap,additives,blowing practices,and preset values)was expanded,and time series(off-gas profiles and blowing practice curves)that could reflect the entire steelmaking process were introduced as inputs.First,the latest machine learning models(LightGBM,CatBoost,TabNet,and NODE)were used to make predictions with tabular features,and the best coefficient of determination R^(2)values obtained for TSC-P,TSC-C and TSC-Temp predictions were 0.435(LightGBM),0.857(Cat-Boost)and 0.678(LightGBM),respectively,which were higher than those of classic models(backpropagation and support vector machine).Then,making predictions was performed by using SOTA time series regression models(SCINet,DLinear,Informer,and MLSTM-FCN)with original time series,SOTA image regression models(NesT,CaiT,ResNeXt,and GoogLeNet)with resized time series,and the proposed Concatenate-Model and Parallel-Model with both tabular features and time series.Through optimization and comparisons,it was finally determined that the Concatenate-Model with MLSTM-FCN,SCINet and Informer as feature extractors performed the best,and its R^(2)values for predicting TSC-P,TSC-C and TSC-Temp reached 0.470,0.858 and 0.710,respectively.Its field test accuracies for TSC-P,TSC-C and TSC-Temp were 0.459,0.850 and 0.685,respectively.A related importance analysis was carried out,and dynamic control methods based on pred

关键词： BOF steelmaking In-blow prediction TSC test Machine learning Deep learning Field application