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Accurate simulations of pure-viscoacoustic wave propagation in tilted transversely isotropic media

Petroleum Science 2024年第2期21卷 866-884页

作者： Qiang Mao jian-ping huang Xin-Ru Mu Ji-Dong Yang Yu-jian Zhang Geosciences Department China University of Petroleum(East China)Qingdao266580ShandongChina Pilot National Laboratory for Marine Science and Technology(Qingdao) Qingdao266207ShandongChina

Forward modeling of seismic wave propagation is crucial for the realization of reverse time migration(RTM) and full waveform inversion(FWI) in attenuating transversely isotropic media. To describe the attenuation and anisotropy properties of subsurface media, the pure-viscoacoustic anisotropic wave equations are established for wavefield simulations, because they can provide clear and stable wavefields. However, due to the use of several approximations in deriving the wave equation and the introduction of a fractional Laplacian approximation in solving the derived equation, the wavefields simulated by the previous pure-viscoacoustic tilted transversely isotropic(TTI) wave equations has low accuracy. To accurately simulate wavefields in media with velocity anisotropy and attenuation anisotropy, we first derive a new pure-viscoacoustic TTI wave equation from the exact complex-valued dispersion formula in viscoelastic vertical transversely isotropic(VTI) media. Then, we present the hybrid finite-difference and low-rank decomposition(HFDLRD) method to accurately solve our proposed pure-viscoacoustic TTI wave equation. Theoretical analysis and numerical examples suggest that our pure-viscoacoustic TTI wave equation has higher accuracy than previous pure-viscoacoustic TTI wave equations in describing q P-wave kinematic and attenuation characteristics. Additionally, the numerical experiment in a simple two-layer model shows that the HFDLRD technique outperforms the hybrid finite-difference and pseudo-spectral(HFDPS) method in terms of accuracy of wavefield modeling.

关键词： Pure-viscoacoustic TTI wave equation Attenuation anisotropy Seismic modeling Low-rank decomposition method

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Identification and characterization of camptothecin tailoring enzymes in Nothapodytes tomentosa

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Journal of Integrative Plant Biology 2024年第6期66卷 1158-1169页

作者： Yin Chen jian-ping huang Yong-jiang Wang Meng-Ling Tu Junheng Li Bingyan Xu Guoqing Peng Jing Yang Sheng-Xiong huang State Key Laboratory of Phytochemistry and Plant Resources in West China and Yunnan Key Laboratory of Natural Medicinal Chemistry Kunming Institute of Botany Chinese Academy of Sciences University of Chinese Academy of Sciences Key Laboratory for Economic Plants and Biotechnology Kunming Institute of Botany Chinese Academy of Sciences

Camptothecin is a complex monoterpenoid indole alkaloid with remarkable antitumor activity. Given that two C-10 modified camptothecin derivatives,topotecan and irinotecan, have been approved as potent anticancer agents, there is a critical need for methods to access other aromatic ringfunctionalized congeners(e.g., C-9, C-10, etc.).However, contemporary methods for chemical oxidation are generally harsh and low-yielding when applied to the camptothecin scaffold, thereby limiting the development of modified derivatives. Reported herein, we have identified four tailoring enzymes responsible for C-9 modifications of camptothecin from Nothapodytes tomentosa, via metabolomic and transcriptomic analysis. These consist of a cytochrome P450(Nt CPT9H) which catalyzes the regioselective oxidation of camptothecin to 9-hydroxycamptothecin, as well as two methyltransferases(Nt OMT1/2, converting 9-hydroxycamptothecin to 9-methoxycamptothecin),and a uridine diphosphate-glycosyltransferase(Nt UGT5, decorating 9-hydroxycamptothecin to9-β-D-glucosyloxycamptothecin). Importantly, the critical residues that contribute to the specific catalytic activity of Nt CPT9H have been elucidated through molecular docking and mutagenesis experiments. This work provides a genetic basis for producing camptothecin derivatives through metabolic engineering. This will hasten the discovery of novel C-9 modified camptothecin derivatives,with profound implications for pharmaceutical manufacture.

关键词： camptothecin biosynthesis enzymatic assay Nothapodytes tomentosa tailoring enzyme transcriptomic analysis

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Identification of differentially expressed mRNAs as novel predictive biomarkers for gastric cancer diagnosis and prognosis

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World Journal of Gastrointestinal Oncology 2024年第5期16卷 1947-1964页

作者： jian-Wei Zhou Yi-Bing Zhang Zhi-Yang huang Yu-ping Yuan Jie Jin Department of Gastroenterology Wenzhou Central HospitalDingli Clinical College of Wenzhou Medical UniversityThe Second Affiliated Hospital of Shanghai UniversityWenzhou 325000Zhejiang ProvinceChina

BACKGROUND Gastric cancer(GC)has a high mortality rate worldwide.Despite significant progress in GC diagnosis and treatment,the prognosis for affected patients still remains unfavorable.AIM To identify important candidate genes related to the development of GC and iden-tify potential pathogenic mechanisms through comprehensive bioinformatics analysis.METHODS The Gene Expression Omnibus database was used to obtain the GSE183136 dataset,which includes a total of 135 GC samples.The limma package in R software was employed to identify differentially expressed genes(DEGs).Thereafter,enrichment analyses of Gene Ontology(GO)terms and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathways were performed for the gene modules using the clusterProfile package in R software.The protein-protein interaction(PPI)networks of target genes were constructed using STRING and visualized by Cytoscape software.The common hub genes that emerged in the cohort of DEGs that was retrieved from the GEPIA database were then screened using a Venn Diagram.The expression levels of these overlapping genes in stomach adenocarcinoma samples and non-tumor samples and their association with prognosis in GC patients were also obtained from the GEPIA database and Kaplan-Meier curves.Moreover,real-time quantitative polymerase chain reaction(RT-qPCR)and western blotting were performed to determine the mRNA and protein levels of glutamic-pyruvic transaminase(GPT)in GC and normal immortalized cell lines.In addition,cell viability,cell cycle distribution,migration and invasion were evaluated by cell counting kit-8,flow cytometry and transwell assays.Furthermore,we also conducted a retrospective analysis on 70 GC patients diagnosed and surgically treated in Wenzhou Central Hospital,Dingli Clinical College of Wenzhou Medical University,The Second Affiliated Hospital of Shanghai University between January 2017 to December 2020.The tumor and adjacent normal samples were collected from the patients to determine the potential association between the expression lev

关键词： Gastric cancer Differentially expressed genes Bioinformatics Hub genes Prognosis

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Superiority of a Convolutional Neural Network Model over Dynamical Models in Predicting Central Pacific ENSO

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Advances in Atmospheric Sciences 2024年第1期41卷 141-154页

作者： Tingyu WANG ping huang Center for Monsoon System Research Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD) Nanjing University of Information Science&TechnologyNanjing 210044China State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China University of Chinese Academy of Sciences Beijing 100049China

The application of deep learning is fast developing in climate prediction,in which El Ni?o–Southern Oscillation(ENSO),as the most dominant disaster-causing climate event,is a key target.Previous studies have shown that deep learning methods possess a certain level of superiority in predicting ENSO indices.The present study develops a deep learning model for predicting the spatial pattern of sea surface temperature anomalies(SSTAs)in the equatorial Pacific by training a convolutional neural network(CNN)model with historical simulations from CMIP6 models.Compared with dynamical models,the CNN model has higher skill in predicting the SSTAs in the equatorial western-central Pacific,but not in the eastern Pacific.The CNN model can successfully capture the small-scale precursors in the initial SSTAs for the development of central Pacific ENSO to distinguish the spatial mode up to a lead time of seven months.A fusion model combining the predictions of the CNN model and the dynamical models achieves higher skill than each of them for both central and eastern Pacific ENSO.

关键词： ENSO diversity deep learning ENSO prediction dynamical forecast system

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An overview for monitoring and prediction of pathogenic microorganisms in the atmosphere

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Fundamental Research 2024年第3期4卷 430-441页

作者： jianping huang Danfeng Wang Yongguan Zhu Zifeng Yang Maosheng Yao Xiaoming Shi Taicheng An Qiang Zhang Cunrui huang Xinhui Bi jiang Li Zifa Wang Yongqin Liu Guibing Zhu Siyu Chen jian Hang Xinghua Qiu Weiwei Deng Huaiyu Tian Tengfei Zhang Tianmu Chen Sijin Liu Xinbo Lian Bin Chen Beidou Zhang Yingjie Zhao Rui Wang Han Li Collaborative Innovation Center for Western Ecological Safety College of Atmospheric SciencesLanzhou UniversityLanzhou 730000China Research Center for Eco-Environmental Sciences Chinese Academy of SciencesBeijing 100085China National Clinical Research Center for Respiratory Disease Guangzhou Institute of Respiratory HealthFirst Affiliated Hospital of Guangzhou Medical UniversityState Key Laboratory of Respiratory Disease(Guangzhou Medical University)Guangzhou 510230China College of Environmental Sciences and Engineering Peking UniversityBeijing 100871China China CDC Key Laboratory of Environment and Population Health National Institute of Environmental HealthChinese Center for Disease Control and PreventionBeijing 100021China Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health School of Environmental Science and EngineeringInstitute of Environmental Health and Pollution ControlGuangdong University of TechnologyGuangzhou 510006China Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System ScienceTsinghua UniversityBeijing 100084China Vanke School of Public Health Tsinghua UniversityBeijing 100084China State Key Laboratory of Organic Geochemistry and Guangdong Key Laboratory of Environmental Protection and Resources Utilization Guangzhou Institute of GeochemistryChinese Academy of SciencesGuangzhou 510640China National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijing 100021China State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Center for Pan-third Pole Environment Lanzhou UniversityLanzhou 730000China College of Atmospheric Sciences Lanzhou UniversityLanzhou 730000China School of Atmospheric Sciences Sun Yat-sen Universityand Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)Zhuhai 510640

Corona virus disease 2019(COVID-19)has exerted a profound adverse impact on human health.Studies have demonstrated that aerosol transmission is one of the major transmission routes of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2).Pathogenic microorganisms such as SARS-CoV-2 can survive in the air and cause widespread infection among people.Early monitoring of pathogenic microorganism transmission in the atmosphere and accurate epidemic prediction are the frontier guarantee for preventing large-scale epidemic outbreaks.Monitoring of pathogenic microorganisms in the air,especially in densely populated areas,may raise the possibility to detect viruses before people are widely infected and contain the epidemic at an earlier stage.The multi-scale coupled accurate epidemic prediction system can provide support for governments to analyze the epidemic situation,allocate health resources,and formulate epidemic response policies.This review first elaborates on the effects of the atmospheric environment on pathogenic microorganism transmission,which lays a theoretical foundation for the monitoring and prediction of epidemic development.Secondly,the monitoring technique development and the necessity of monitoring pathogenic microorganisms in the atmosphere are summarized and emphasized.Subsequently,this review introduces the major epidemic prediction methods and highlights the significance to realize a multi-scale coupled epidemic prediction system by strengthening the multidisciplinary cooperation of epidemiology,atmospheric sciences,environmental sciences,sociology,demography,etc.By summarizing the achievements and challenges in monitoring and prediction of pathogenic microorganism transmission in the atmosphere,this review proposes suggestions for epidemic response,namely,the establishment of an integrated monitoring and prediction platform for pathogenic microorganism transmission in the atmosphere.

关键词： Aerosol transmission Epidemic monitoring methods Epidemic prediction modelsEpidemic response Multidisciplinary cooperation

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Danhongqing formula alleviates cholestatic liver fibrosis by downregulating long non-coding RNA H19 derived from cholangiocytes and inhibiting hepatic stellate cell activation

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Journal of Integrative Medicine 2024年第2期22卷 188-198页

作者： Meng Li Yang Zhou Hui Zhu Lie-ming Xu jian ping Institute of Liver Diseases Shuguang HospitalShanghai University of Traditional Chinese MedicineShanghai 201203China Preventive Treatment Center Yueyang Hospital of Integrated Traditional Chinese and Western MedicineShanghai University of Traditional Chinese MedicineShanghai 200437 China Department of Gastroenterology Suzhou Traditional Chinese Medicine HospitalSuzhou 215000Jiangsu ProvinceChina Shanghai Key Laboratory of Traditional Chinese Medicine Shanghai 201203China Key Laboratory of Liver and Kidney Diseases(Ministry of Education) Shanghai 201203China

Objective:This study explores the mechanism of action of Danhongqing formula(DHQ),a compoundbased Chinese medicine formula,in the treatment of cholestatic liver fibrosis.Methods:In vivo experiments were conducted using 8-week-old multidrug resistance protein 2 knockout(Mdr2-/-)mice as an animal model of cholestatic liver fibrosis.DHQ was administered orally for 8 weeks,and its impact on cholestatic liver fibrosis was evaluated by assessing liver function,liver histopathology,and the expression of liver fibrosis-related proteins.Real-time polymerase chain reaction,Western blot,immunohistochemistry and other methods were used to observe the effects of DHQ on long non-coding RNA H19(H19)and signal transducer and activator of transcription 3(STAT3)phosphorylation in the liver tissue of Mdr2-/-mice.In addition,cholangiocytes and hepatic stellate cells(HSCs)were cultured in vitro to measure the effects of bile acids on cholangiocyte injury and H19 expression.Cholangiocytes overexpressing H19 were constructed,and a conditioned medium containing H19 was collected to measure its effects on STAT3 protein expression and cell activation.The intervention effect of DHQ on these processes was also investigated.HSCs overexpressing H19 were constructed to measure the impact of H19 on cell activation and assess the intervention effect of DHQ.Results:DHQ alleviated liver injury,ductular reaction,and fibrosis in Mdr2-/-mice,and inhibited H19expression,STAT3 expression and STAT3 phosphorylation.This formula also reduced hydrophobic bile acid-induced cholangiocyte injury and the upregulation of H19,inhibited the activation of HSCs induced by cholangiocyte-derived conditioned medium,and decreased the expression of activation markers in HSCs.The overexpression of H19 in a human HSC line confirmed that H19 promoted STAT3 phosphorylation and HSC activation,and DHQ was able to successfully inhibit these effects.Conclusion:DHQ effectively alleviated spontaneous cholestatic liver fibrosis in Mdr2-/-mice by inhibiting H19 upregulation in chol

关键词： Liver cirrhosis biliary Long non-coding RNA H19 Danhongqing formula Cholangiocyte Hepatic stellate cells STAT3 transcription factor

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Stable attenuation-compensated reverse time migration and its application to land seismic data

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Petroleum Science 2023年第5期20卷 2784-2795页

作者： Xin-Ru Mu Qiang Mao jian-ping huang Geosciences Department China University of Petroleum(East China)QingdaoShandong266580China Pilot National Laboratory for Marine Science and Technology(Qingdao) QingdaoShandong266000China

Intrinsic attenuation of the earth causes energy loss and phase distortion in seismic wave propagation.To obtain high-resolution imaging results,these negative effects must be considered during reverse time migration(RTM).We can easily implement attenuation-compensated RTM using the constant Q viscoacoustic wave equation with decoupled amplitude attenuation and phase dispersion terms.However,the nonphysical amplitude-compensation process will inevitably amplify the high-frequency noise in the wavefield in an exponential form,causing the numerical simulation to become unstable.This is due to the fact that the amplitude of the compensation grows exponentially with frequency.In order to achieve stable attenuation-compensated RTM,we modify the analytic expression of the attenuation compensation extrapolation operator and make it only compensate for amplitude loss within the effective frequency band.Based on this modified analytic formula,we then derive an explicit time-space domain attenuation compensation extrapolation operator.Finally,the implementation procedure of stable attenuation-compensated RTM is presented.In addition to being simple to implement,the newly proposed attenuation-compensated extrapolation operator is superior to the conventional low-pass filter in suppressing random noise,which will further improve the imaging resolution.We use two synthetic and one land seismic datasets to verify the stability and effectiveness of the proposed attenuationcompensated RTM in improving imaging resolution in viscous media.

关键词： Seismic attenuation Reverse time migration Stability strategy Pseudospectral method

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Spherical Confinement Generates Entropic Force to Accelerate Polymer Chain Detachment

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Chinese Journal of Polymer Science 2024年第3期42卷 407-416,I0010页

作者： Yu-Shan Zheng jian-ping Zhou Yan Xu Kai Li Mechanical Engineering Xinjiang UniversityUrumqi 830002China

To understand the dynamic process of polymer detachment, it is necessary to determine the mean detachment time of a single breakable link, which is modeled as a spring. Normally, this time can be viewed as the escape of a Brownian particle from the potential well of the spring. However, as the free dangling length of the polymer chain increases, the conformational entropy of the chain is affected by geometric confinement. It means that the wall exerts a repulsive force on the chain, resulting in accelerated link detachment from a macroscopic perspective. In this work, we investigate the effect of entropy on the detachment rate in the case where the substrate is spherical. We demonstrate that spherical confinement accelerates chain detachment both inside and outside the sphere. An analytical expression for the mean detachment time of breakable links is given, which includes an additional pre-factor that is related to the partition function. Additionally, we analyze the expressions for entropic forces inside the sphere, outside the sphere, and on a flat wall, comparing their magnitudes to explain the difference in mean detachment time.

关键词： Polymer detachment Breakable link Entropic force Mean first passage time

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Understanding the Low Predictability of the 2015/16 El Niño Event Based on a Deep Learning Model

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Advances in Atmospheric Sciences 2024年第7期41卷 1313-1325页

作者： Tingyu WANG ping huang Xianke YANG Center for Monsoon System Research Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China National Space Science Center Chinese Academy of SciencesBeijing 100190China State Key Laboratory of Space Weather National Space Science CenterChinese Academy of SciencesBeijing 100190China College of Plant Science and Technology Huazhong Agricultural UniversityWuhan 430070China

The 2015/16 El Niño event ranks among the top three of the last 100 years in terms of intensity,but most dynamical models had a relatively low prediction skill for this event before the summer months.Therefore,the attribution of this particular event can help us to understand the cause of super El Niño–Southern Oscillation events and how to forecast them skillfully.The present study applies attribute methods based on a deep learning model to study the key factors related to the formation of this event.A deep learning model is trained using historical simulations from 21 CMIP6 models to predict the Niño-3.4 index.The integrated gradient method is then used to identify the key signals in the North Pacific that determine the evolution of the Niño-3.4 index.These crucial signals are then masked in the initial conditions to verify their roles in the prediction.In addition to confirming the key signals inducing the super El Niño event revealed in previous attribution studies,we identify the combined contribution of the tropical North Atlantic and the South Pacific oceans to the evolution and intensity of this event,emphasizing the crucial role of the interactions among them and the North Pacific.This approach is also applied to other El Niño events,revealing several new precursor signals.This study suggests that the deep learning method is useful in attributing the key factors inducing extreme tropical climate events.

关键词： ENSO attribution deep learning ENSO prediction extreme El Niño

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Enhanced and asymmetric signatures of hybridization at climatic margins: Evidence from closely related dioecious fig species

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Plant Diversity 2024年第2期46卷 181-193页

作者： jian-Feng huang Clive T.Darwell Yan-Qiong Peng CAS Key Laboratory of Tropical Forest Ecology Xishuangbanna Tropical Botanical GardenChinese Academy of SciencesMengla 666303China National Center for Genetic Engineering and Biotechnology(BIOTEC) 113 Thailand Science ParkPhahonyothin RoadKhlong NuengKhlong LuangPathum Thani 12120Thailand

Hybridization plays a significant role in biological evolution. However, it is not clear whether ecological contingency differentially influences likelihood of hybridization, particularly at ecological margins where parental species may exhibit reduced fitnesses. Moreover, it is unknown whether future ecosystem change will increase the prevalence of hybridization. Ficus heterostyla and F. squamosa are closely related species co-distributed from southern Thailand to southwest China where hybridization, yielding viable seeds, has been documented. As a robust test of ecological factors driving hybridization, we investigated spatial hybridization signatures based on nuclear microsatellites from extensive population sampling across a widespread contact range. Both species showed high population differentiation and strong patterns of isolation by distance. Admixture estimates exposed asymmetric interspecific gene flow.Signatures of hybridization increase significantly towards higher latitude zones, peaking at the northern climatic margins. Geographic variation in reproductive phenology combined with ecologically challenging marginal habitats may promote this phenomenon. Our work is a first systematic evaluation of such patterns in a comprehensive, latitudinally-based clinal context, and indicates that tendency to hybridize appears strongly influenced by environmental conditions. Moreover, that future climate change scenarios will likely alter and possibly augment cases of hybridization at ecosystem scales.

关键词： Hybridization Heterospecific visitation Fig Pollinator wasp Asymmetric gene flow

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