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Establishment of human cerebral organoid systems to model early neural development and assess the central neurotoxicity of environmental toxins

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Neural Regeneration Research 2025年第1期20卷 242-252页

作者： Daiyu Hu Yuanqing Cao Chenglin cai Guangming Wang Min Zhou Luying Peng Yantao Fan Qiong Lai Zhengliang Gao Fundamental Research Center Shanghai Yangzhi Rehabilitation Hospital(Shanghai Sunshine Rehabilitation Center)School of MedicineTongji UniversityShanghaiChina Institute of Geriatrics(Shanghai University) Affiliated Nantong Hospital of Shanghai University(The Sixth People’s Hospital of Nantong)Shanghai University School of MedicineNantongJiangsu ProvinceChina Shanghai Engineering Research Center of Organ Repair Shanghai University School of MedicineShanghaiChina Key Laboratory of Arrhythmias Ministry of EducationShanghai East HospitalSchool of MedicineTongji UniversityShanghaiChina

Human brain development is a complex process,and animal models often have significant *** address this,researchers have developed pluripotent stem cell-derived three-dimensional structures,known as brain-like organoids,to more accurately model early human brain development and *** enable more consistent and intuitive reproduction of early brain development,in this study,we incorporated forebrain organoid culture technology into the traditional unguided method of brain organoid *** involved embedding organoids in matrigel for only 7 days during the rapid expansion phase of the neural epithelium and then removing them from the matrigel for further cultivation,resulting in a new type of human brain organoid *** cerebral organoid system replicated the temporospatial characteristics of early human brain development,including neuroepithelium derivation,neural progenitor cell production and maintenance,neuron differentiation and migration,and cortical layer patterning and formation,providing more consistent and reproducible organoids for developmental modeling and toxicology *** a proof of concept,we applied the heavy metal cadmium to this newly improved organoid system to test whether it could be used to evaluate the neurotoxicity of environmental *** organoids exposed to cadmium for 7 or 14 days manifested severe damage and abnormalities in their neurodevelopmental patterns,including bursts of cortical cell death and premature *** exposure caused progressive depletion of neural progenitor cells and loss of organoid integrity,accompanied by compensatory cell proliferation at ectopic *** convenience,flexibility,and controllability of this newly developed organoid platform make it a powerful and affordable alternative to animal models for use in neurodevelopmental,neurological,and neurotoxicological studies.

关键词： cadmium cell death cell proliferation cortical development environmental toxins neural progenitor cells neurogenesis neurotoxicology organoids stem cells

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Application of the improved dung beetle optimizer,muti-head attention and hybrid deep learning algorithms to groundwater depth prediction in the Ningxia area,China

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Atmospheric and Oceanic Science Letters 2025年第1期18卷 18-23页

作者： Jiarui cai Bo Sun Huijun Wang Yi Zheng Siyu Zhou Huixin Li Yanyan Huang Peishu Zong Collaborative Innovation Center on forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster Ministry of Education/Joint International Research Laboratory of Climate and Environment ChangeNanjing University of Information Science and TechnologyNanjingChina Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) ZhuhaiChina China Meteorological Administration Key Laboratory of Transportation MeteorologyNanjingChina Jiangsu Meteorological Observatory NanjingChina

Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical *** learning can effectively solve this issue and has been proven useful in the prediction of groundwater depth in many *** this study,two new models are applied to the prediction of groundwater depth in the Ningxia area,*** two models combine the improved dung beetle optimizer(DBO)algorithm with two deep learning models:The Multi-head Attention-Convolution Neural Network-Long Short Term Memory networks(MH-CNN-LSTM)and the Multi-head Attention-Convolution Neural Network-Gated Recurrent Unit(MH-CNN-GRU).The models with DBO show better prediction performance,with larger R(correlation coefficient),RPD(residual prediction deviation),and lower RMSE(root-mean-square error).Com-pared with the models with the original DBO,the R and RPD of models with the improved DBO increase by over 1.5%,and the RMSE decreases by over 1.8%,indicating better prediction *** addition,compared with the multiple linear regression model,a traditional statistical model,deep learning models have better prediction performance.

关键词： Groundwater depth Multi-head attention Improved dung beetle optimizer CNN-LSTM CNN-GRU Ningxia

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A novel complex network-based deep learning method for characterizing gas-liquid two-phase flow

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Petroleum Science 2021年第1期18卷 259-268页

作者： Zhong-Ke Gao Ming-Xu Liu Wei-dong Dang qing cai School of Electrical and Information Engineering Tianjin UniversityTianjin 300072TianjinChina

Gas-liquid two-phase flow widely exits in production and transportation of petroleum *** gas-liquid flow and measuring flow parameters represent challenges of great importance,which contribute to the recognition of flow regime and the optimal design of industrial *** this paper,we propose a novel complex network-based deep learning method for characterizing gas-liquid ***,we map the multichannel measurements to multiple limited penetrable visibility graphs(LPVGs)and obtain their degree sequences as the graph *** on the degree distribution,we analyze the complicated flow behavior under different flow ***,we design a dual-input convolutional neural network to fuse the raw signals and the graph representation of LPVGs for the classification of flow structures and measurement of gas void *** implement the model with two parallel branches with the same structure,each corresponding to one *** branch consists of a channel-projection convolutional part,a spatial-temporal convolutional part,a dense block and an attention *** outputs of the two branches are concatenated and fed into several full connected layers for the classification and *** last,our method achieves an accuracy of 95.3%for the classification of flow structures,and a mean squared error of 0.0038 and a mean absolute percent error of 6.3%for the measurement of gas void *** method provides a promising solution for characterizing gas-liquid flow and measuring flow parameters.

关键词： Gas-liquid flow Gas void fraction Flow structure Limited penetrable visibility graph Deep learning

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Insight into the promotional mechanism of Cu modification towards wide-temperature NH3-SCR performance of NbCe catalyst

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Chinese Journal of Chemical Engineering 2022年第10期50卷 301-309页

作者： dongqi An Yuyao Yang Weixin Zou Yandi cai qing Tong Jingfang Sun Lin dong Key Laboratory of Mesoscopic Chemistry of MOE School of Chemistry and Chemical Engineering and Jiangsu Key Laboratory of Vehicle Emissions ControlNanjing UniversityNanjing 210093China Center for Nanochemistry College of Chemistry and Molecular EngineeringPeking UniversityBeijing 100871China Jiangsu Key Laboratory of Vehicle Emissions Control School of EnvironmentNanjing UniversityNanjing 210093China Jiangsu Key Laboratory of Vehicle Emissions Control Center of Modern AnalysisNanjing UniversityNanjing 210093China Key Laboratory of Mesoscopic Chemistry of MOE School of Chemistry and Chemical Engineering and Jiangsu Key Laboratory of Vehicle Emissions ControlSchool of EnvironmentCenter of Modern AnalysisNanjing UniversityNanjing 210093China

A simple strategy of Cu modification was proposed to broaden the operation temperature window for NbCe *** best catalyst Cu0.010/Nb1Ce3 presented over 90%NO conversion in a wide temperature range of 200-400℃and exhibited an excellent H_(2)O or/and SO_(2) resistance at 275℃.To understand the promotional mechanism of Cu modification,the correlation among the"activity-structure-property"were tried to establish *** species highly dispersed on NbCe catalyst to serve as the active *** strong interaction among Cu,Nb and Ce promoted the emergence of NbO4 and induced more Bronsted acid *** Cu modification obviously enhanced the redox behavior of the NbCe ***,EPR probed the Cu species exited in the form of monomeric and dimeric Cu^(2+),the isolated Cu^(2+)acted as catalytic active sites to promote the reaction:Cu^(2+)-NO_(3)^(-)+NO(g)→Cu^(2+)-NO_(2)^(-)+NO_(2)(g).Then the generated NO_(2) would accelerate the fast-SCR reaction process and thus facilitated the lowtemperature deNO_(x) ***,surface nitrates became unstable and easy to decompose after Cu modification,thus providing additional adsorption and activation sites for NH3,and ensuring the improvement of catalytic activity at high *** the NH3-SCR reaction followed by E-R reaction pathway efficaciously over Cu_(0.010)/Nb_(1)Ce_(3) catalyst,the excellent H_(2)O and SO_(2) resistance was as expected.

关键词： NH_(3)-SCR NbCe catalyst Cu modification NO_(2)promoting effect Fast-SCR Flue gas

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RE-SEGNN:recurrent semantic evidence-aware graph neural network for temporal knowledge graph forecasting

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Science China(Information Sciences) 2025年

作者： Wenyu cai Mengfan LI Xuanhua SHI Yuanxin FAN Quntao ZHU Hai JIN National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and TechnologyHuazhong University of Science and Technology

Temporal knowledge graph(TKG) reasoning, has seen widespread use for modeling real-world events, particularly in extrapolation settings. Nevertheless, most previous studies are embedded models, which require both entity and relation embedding to make predictions, ignoring the semantic correlations among different entities and relations within the same timestamp. This can lead to random and nonsensical predictions when unseen entities or relations occur. Furthermore, many existing models exhibit limitations in handling highly correlated historical facts with extensive temporal depth. They often either overlook such facts or overly accentuate the relationships between recurring past occurrences and their current counterparts. Due to the dynamic nature of TKG, effectively capturing the evolving semantics between different timestamps can be *** address these shortcomings, we propose the recurrent semantic evidenceaware graph neural network(RE-SEGNN), a novel graph neural network that can learn the semantics of entities and relations simultaneously. For the former challenge, our model can predict a possible answer to missing quadruples based on semantics when facing unseen entities or relations. For the latter problem, based on an obvious established force, both the recency and frequency of semantic history tend to confer a higher reference value for the current. We use the Hawkes process to compute the semantic trend, which allows the semantics of recent facts to gain more attention than those of distant facts. Experimental results show that RE-SEGNN outperforms all SOTA models in entity prediction on 6 widely used datasets, and 5 datasets in relation prediction. Furthermore, the case study shows how our model can deal with unseen entities and relations.

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Cyclical Deformations of Quadrangles in S^(2)_(κ)and Defining Properties of Alexandrov Spaces

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Acta Mathematica Sinica,English Series 2021年第4期37卷 597-640页

作者： qing Song cai Colledge of Science Tianjin University of TechnologyTianjin 300384P.R.China

This paper is mainly devoted to proving the four equivalent defining properties of a CBA(κ)*** proof is based on an interesting tool we established which describes the cyclical five-step deformation procedure for quadrangles in the model 2-plane S^(2)_(κ),including the limit shape of each *** a byproduct we give a complete list of cyclical deformation procedures for all kinds of quadrangles on *** last we make a contrast of geometric properties of CBA with CBB spaces,including a comparison between their defining properties and a discussion about Alexandrov’s Lemma.

关键词： Spherical quadrangle Alexandrov spaces CBA spaces CBB spaces

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Simulation of Water-Resistance of a Clay Layer During Mining:Analysis of a Safe Water Head

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Journal of China University of Mining and Technology 2007年第3期17卷 345-348页

作者： dong qing-hong cai Rong YANG Wei-feng School of Resources and Earth Science China University of Mining ＆ Technology Xuzhou Jiangsu 221008 China Suzhou Track Transportation Co Ltd Suzhou Jiangsu 215004 China

Given previous research and prototypical geological conditions of a mining workface,we simulated fis-sure development in clay layers at the bottom of Quaternary strata and above bedrock,sand and water inrush during mining by model experiments. The results show that V-shaped fissures usually occur in the bottom clay layer at the front top of the active face and that the position of these fissures changes periodically with ground pressure intervals. These fissures occur exactly in the area where the horizontal strain is concentrated. The results also demonstrate that the permeability coefficient of the cracked clay decreases while fissures tend to close. The permeability of the cracked bottom clay layer increases rapidly after a turning point in the permeability coefficient-water head curve (K-H curve) under a certain vertical load. Under static water pressure,the permeability coefficient of cracked clay decreases when load increases. A turning point in the K-H curve showed up and can be seen as a cutoff point to de-cide water inrush under a certain load level. Under an instantaneous water head,the greatest ability of the cracked clay to avoid drastic water inflow is a little higher than that under static conditions.

关键词： model testing water-resistance of the clay layer safety water head water and sand inrush

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Porous Organic Cage‑Based Quasi‑Solid‑State Electrolyte with Cavity‑Induced Anion‑Trapping Effect for Long‑Life Lithium Metal Batteries

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Nano-Micro Letters 2025年第2期17卷 376-386页

作者： Wei-Min Qin Zhongliang Li Wen‑Xia Su Jia‑Min Hu Hanqin Zou Zhixuan Wu Zhiqin Ruan Yue‑Peng cai Kang Li Qifeng Zheng School of Chemistry South China Normal UniversityGuangzhou 510006People’s Republic of China Key Laboratory of Functional Metal‑Organic Compounds of Hunan Province College of Chemistry and Material ScienceHengyang Normal UniversityHengyang 421008People’s Republic of China Guangzhou Key Laboratory of Energy Conversion and Energy Storage Materials Guangzhou 510006People’s Republic of China

Porous organic cages(POCs)with permanent porosity and excellent host–guest property hold great potentials in regulating ion transport behavior,yet their feasibility as solid-state electrolytes has never been testified in a practical ***,we design and fabricate a quasi-solid-state electrolyte(QSSE)based on a POC to enable the stable operation of Li-metal batteries(LMBs).Benefiting from the ordered channels and cavity-induced anion-trapping effect of POC,the resulting POC-based QSSE exhibits a high Li+transference number of 0.67 and a high ionic conductivity of 1.25×10^(−4) S cm^(−1) with a low activation energy of 0.17 *** allow for homogeneous Li deposition and highly reversible Li plating/stripping for over 2000 *** a proof of concept,the LMB assembled with POC-based QSSE demonstrates extremely stable cycling performance with 85%capacity retention after 1000 ***,our work demonstrates the practical applicability of POC as SSEs for LMBs and could be extended to other energy-storage systems,such as Na and K batteries.

关键词： Porous organic cage Cavity-induced anion-trapping Quasi-solid-state electrolyte Homogeneous Li+flux Lithium metal battery

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Light-responsive organic artificial enzymes:Material designs and bio-applications

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Nano Research 2023年第1期16卷 117-126页

作者： Weili Wang qing Shen Hao cai Leichen Wang Jinjun Shao Wenjun Wang Xiaochen dong Key Laboratory of Flexible Electronics(KLOFE)and Institute of Advanced Materials(IAM) Nanjing Tech University(NanjingTech)Nanjing 211816China School of Physical Science and Information Technology Liaocheng UniversityLiaocheng 252059China

As significant biocatalysts,natural enzymes have exhibited a vast range of applications in biocatalytic ***,the“always-on”natural enzyme activity is not beneficial for the regulation of catalytic processes,which limits their ***,it has been extensively reported that various organic artificial enzymes exhibit prominent absorption and controlled activity under illumination,which not only creates a series of light-responsive catalytic platforms but also plays a key role in biosensing and biomedical *** provide novel ideas for the design of artificial enzymes,we conduct this review to highlight the recent progress of light-responsive organic artificial enzymes(LOA-Enz).The specific photoresponse mechanism and various bio-applications of LOA-Enz are also presented in ***,the remaining challenges and future perspectives in this field are discussed.

关键词： light-response organic artificial enzymes catalytic activity bio-applications

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Antithetical impacts of deleterious LRP1B mutations in non-squamous and squamous NSCLCs on predicting benefits from immune checkpoint inhibitor alone or with chemotherapy over chemotherapy alone: retrospective analyses of the POPLAR/OAK and CHOICE-01 trial

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Science China Life Sciences 2025年第1期68卷 249-262页

作者： Jinliang Wang Wenyong Zhou Yu Xu Jianchun Duan Qiaoxia Zhou Guoqiang Wang Leo Li Chunwei Xu Wenxian Wang Shangli cai Zhijie Wang Jie Wang Department of Oncology The Fifth Medical Center of Chinese PLA General Hospital Department of Thoracic Surgery Shanghai Chest HospitalSchool of MedicineShanghai Jiao Tong University Burning Rock Biotech CAMS Key Laboratory of Translational Research on Lung Cancer State Key Laboratory of Molecular OncologyDepartment of Medical OncologyNational Cancer Center/National Clinical Research Center for ancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical College Institute of Basic Medicine and Cancer (IBMC) Chinese Academy of Sciences Department of Clinical Trial The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital)

In non-small cell lung cancers,the non-squamous and squamous subtypes（nsqNSCLC and sqNSCLC） exhibit disparities in pathophysiology,tumor immunology,and potential genomic correlates affecting responses to immune checkpoint inhibitor（ICI）-based *** our inhouse training cohort（n=85）,the presence of the LRP1B deleterious mutation（LRP1B-del） was associated with longer and shorter progression-free survival（PFS） on ICIs alone in nsqNSCLCs and sqNSCLCs,respectively(Pinteraction=0.008).These results were validated using a larger public ICI cohort(n=208,Pinteraction<0.001).Multiplex immunofluorescence staining revealed an association between LRP1B-del and increased and decreased numbers of tumor-infiltrating CD8+T cells in nsqNSCLCs（P=0.040） and sqNSCLCs（P=0.014）,*** the POPLAR/OAK cohort,nsqNSCLCs with LRP1B-del demonstrated improved PFS benefits from atezolizumab over docetaxel(hazard ratio（HR）=0.70,P=0.046),whereas this benefit was negligible in those without LRP1B-del（HR=1.05,P=0.64）.Conversely,sqNSCLCs without LRP1B-del benefited more from atezolizumab（HR=0.60,P=0.002） than those with LRP1B-del（HR=1.30,P=0.31）.Consistent results were observed in the in-house CHOICE-01 cohort,in which nsqNSCLCs with LRP1B-del and sqNSCLCs without LRP1B-del benefited more from toripalimab plus chemotherapy than from chemotherapy alone(Pinteraction=0.008).This multi-cohort study delineates the antithetical impacts of LRP1B-del in nsqNSCLCs and sqNSCLCs on predicting the benefits from ICI alone or with chemotherapy over chemotherapy *** findings highlight the distinct clinical utility of LRP1B-del in guiding treatment choices for nsqNSCLCs and sqNSCLCs,emphasizing the necessity for a detailed analysis based on pathological subtypes when investigating biomarkers for cancer therapeutics.

关键词： non-squamous NSCLC squamous NSCLC LRP1B deleterious mutations predictive biomarker immune checkpoint inhibitor

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