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Novel lactylation-related signature to predict prognosis for pancreatic adenocarcinoma

World Journal of Gastroenterology 2024年第19期30卷 2575-2602页

作者： Tian Peng fang sun Jia-Chun Yang Mei-Hong Cai Man-Xiu Huai Jia-Xing Pan Fei-Yu Zhang Lei-Ming Xu Department of Gastroenterology Xinhua Hospital Affiliated to Shanghai Jiao Tong UniversityShanghai 200092China

BACKGROUND Lactate,previously considered a metabolic byproduct,is pivotal in cancer progression and maintaining the immunosuppressive tumor microenvironment.Further investigations confirmed that lactate is a primary regulator,introducing recently described post-translational modifications of histone and non-histone proteins,termed lysine lactylation.Pancreatic adenocarcinomas are characterized by increased glycolysis and lactate accumulation.However,our understanding of lactylation-related genes in pancreatic adenocarcinomas remains limited.AIM To construct a novel lactylation-related gene signature to predict the survival of patients with pancreatic cancer.METHODS RNA-seq and clinical data of pancreatic adenocarcinoma(PDAC)were obtained from the GTEx(Genotype-Tissue Expression)and TCGA(The Cancer Genome Atlas)databases via Xena Explorer,and GSE62452 datasets from GEO.Data on lactylation-related genes were obtained from publicly available sources.Differential expressed genes(DEGs)were acquired by using R package“DESeq2”in R.Univariate COX regression analysis,LASSO Cox and multivariate Cox regressions were produced to construct the lactylation-related prognostic model.Further analyses,including functional enrichment,ESTIMATE,and CIBERSORT,were performed to analyze immune status and treatment responses in patients with pancreatic cancer.PDAC and normal human cell lines were subjected to western blot analysis under lactic acid intervention;two PDAC cell lines with the most pronounced lactylation were selected.Subsequently,RT-PCR was employed to assess the expression of LRGs genes;SLC16A1,which showed the highest expression,was selected for further investigation.SLC16A1-mediated lactylation was analyzed by immunofluorescence,lactate production analysis,colony formation,transwell,and wound healing assays to investigate its role in promoting the proliferation and migration of PDAC cells.In vivo validation was performed using an established tumor model.RESULTS In this study,we successfully identified 10 differentially e

关键词： Pancreatic adenocarcinoma Lactylation Prognosis Immunotherapy Tumor microenvironment

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A New Method for Solving Nonlinear Partial Differential Equations Based on Liquid Time-Constant Networks

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Journal of Systems Science & Complexity 2024年第2期37卷 480-493页

作者： sun Jiuyun DONG Huanhe fang Yong College of Mathematics and Systems Science Shandong University of Science and TechnologyQingdao 266590China

In this paper,physics-informed liquid networks(PILNs)are proposed based on liquid time-constant networks(LTC)for solving nonlinear partial differential equations(PDEs).In this approach,the network state is controlled via ordinary differential equations(ODEs).The significant advantage is that neurons controlled by ODEs are more expressive compared to simple activation functions.In addition,the PILNs use difference schemes instead of automatic differentiation to construct the residuals of PDEs,which avoid information loss in the neighborhood of sampling points.As this method draws on both the traveling wave method and physics-informed neural networks(PINNs),it has a better physical interpretation.Finally,the KdV equation and the nonlinear Schr¨odinger equation are solved to test the generalization ability of the PILNs.To the best of the authors’knowledge,this is the first deep learning method that uses ODEs to simulate the numerical solutions of PDEs.

关键词： Nonlinear partial differential equations numerical solutions physics-informed liquid networks physics-informed neural networks

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Physical informed memory networks for solving PDEs:implementation and applications

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Communications in Theoretical Physics 2024年第2期76卷 51-61页

作者： Jiuyun sun Huanhe Dong Yong fang College of Mathematics and Systems Science Shandong University of Science and TechnologyQingdao 266590China

With the advent of physics informed neural networks(PINNs),deep learning has gained interest for solving nonlinear partial differential equations(PDEs)in recent years.In this paper,physics informed memory networks(PIMNs)are proposed as a new approach to solving PDEs by using physical laws and dynamic behavior of PDEs.Unlike the fully connected structure of the PINNs,the PIMNs construct the long-term dependence of the dynamics behavior with the help of the long short-term memory network.Meanwhile,the PDEs residuals are approximated using difference schemes in the form of convolution filter,which avoids information loss at the neighborhood of the sampling points.Finally,the performance of the PIMNs is assessed by solving the Kd V equation and the nonlinear Schr?dinger equation,and the effects of difference schemes,boundary conditions,network structure and mesh size on the solutions are discussed.Experiments show that the PIMNs are insensitive to boundary conditions and have excellent solution accuracy even with only the initial conditions.

关键词： nonlinear partial differential equations physics informed memory networks physics informed neural networks numerical solution

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Experimental clearance rate and intraguild predation of jellyfish Cyanea nozakii

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Journal of Oceanology and Limnology 2024年第1期42卷 128-140页

作者： Pengpeng WANG fang ZHANG Song sun Shuguo LÜ CAS Key Laboratory of Marine Ecology and Environmental Sciences Institute of OceanologyChinese Academy of SciencesQingdao 266071China Laboratory for Marine Ecology and Environmental Sciences Pilot National Laboratory for Marine Science and Technology(Qingdao)Qingdao 266237China University of Chinese Academy of Sciences Beijing 100049China Jiaozhou Bay Marine Ecosystem Research Station Chinese Academy of SciencesQingdao 266071China Center for Ocean Mega-Science Chinese Academy of SciencesQingdao 266071China Institute of Marine Ecology and Environment Hainan Academy of Environmental SciencesHaikou 570100China

Cyanea nozakii,a common jellyfish distributed in offshore China,has a complex trophic relationship with other zooplankton groups.However,few studies have reported the predation rates and prey selection patterns of C.nozakii medusae on different prey items.Research is also lacking on the intraguild predation of Aurelia coerulea(another common bloom jellyfish in offshore China)by C.nozakii.To address the knowledge gaps,the clearance rates of C.nozakii for different prey items,including copepods(small1000μm),fish larvae,and gelatinous prey(hydromedusae,A.coerulea ephyrae,and chaetognaths),were measured.The influence of predator size on the clearance rate was also determined.Additionally,we examined the intraguild predation of C.nozakii on A.coerulea medusae.The clearance rates of C.nozakii varied widely with prey organisms,being independent of prey concentrations.Gelatinous organisms,except for chaetognaths,were captured with considerably high efficiency,followed by fish larvae and copepods,indicating the preferential prey selection of gelatinous organisms by C.nozakii.The clearance rate increased linearly with the cross-sectional area of C.nozakii.Body size in medusae may,to some extents,underpin their capacity to capture more prey by increasing the encounter rate and capture success through ontogeny.C.nozakii preyed voraciously on A.coerulea in high feeding efficiency,but the clearance rate decreased with increasing A.coerulea(as prey)size.This phenomenon of intraguild predation suggests a speculative hypothesis of potential population regulation of A.coerulea by C.nozakii.The information regarding the feeding ecology of C.nozakii reported in this study is important for understanding plankton dynamics in marine ecosystems with extensive occurrences of this jellyfish.

关键词： Scyphomedusae predation rate gelatinous organisms prey selection feeding mechanism

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Laser manufacturing of spatial resolution approaching quantum limit

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Light(Science & Applications) 2024年第3期13卷 421-428页

作者： Xiao-Jie Wang Hong-Hua fang Zhen-Ze Li Dan Wang Hong-Bo sun State Key Laboratory of Precision Measurement Technology and Instruments Department of Precision InstrumentTsinghua UniversityBeijing 100084China State Key Laboratory of Integrated Optoelectronics College of Electronic Science and EngineeringJilin University2699 Qianjin StreetChangchun 130012China

Atomic and close-to-atom scale manufacturing is a promising avenue toward single-photon emitters,single-electron transistors,single-atom memory,and quantum-bit devices for future communication,computation,and sensing applications.Laser manufacturing is outstanding to this end for ease of beam manipulation,batch production,and no requirement for photomasks.It is,however,suffering from optical diffraction limits.Herein,we report a spatial resolution improved to the quantum limit by exploiting a threshold tracing and lock-in method,whereby the two-order gap between atomic point defect complexes and optical diffraction limit is surpassed,and a feature size of<5 nm is realized.The underlying physics is that the uncertainty of local atom thermal motion dominates electron excitation,rather than the power density slope of the incident laser.We show that the colour centre yield in hexagonal boron nitride is transformed from stochastic to deterministic,and the emission from individual sites becomes polychromatic to monochromatic.As a result,single colour centres in the regular array are deterministically created with a unity yield and high positional accuracy,serving as a step forward for integrated quantum technological applications.

关键词： quantum limit resolution

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Implication of community-level ecophysiological parameterization to modelling ecosystem productivity:a case study across nine contrasting forest sites in eastern China

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Journal of Forestry Research 2024年第1期35卷 1-11页

作者： Minzhe fang Changjin Cheng Nianpeng He Guoxin Si Osbert Jianxin sun School of Ecology and Nature Conservation Beijing Forestry UniversityBeijing 100083China Research Institute of Energy Saving Environmental ProtectionOccupational Safety and HealthChina Academy of Railway Sciences Corporation LimitedBeijing 100081China Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China College of Resources and Environment University of Chinese Academy of SciencesBeijing 100049China

Parameterization is a critical step in modelling ecosystem dynamics.However,assigning parameter values can be a technical challenge for structurally complex natural plant communities;uncertainties in model simulations often arise from inappropriate model parameterization.Here we compared five methods for defining community-level specific leaf area(SLA)and leaf C:N across nine contrasting forest sites along the North-South Transect of Eastern China,including biomass-weighted average for the entire plant community(AP_BW)and four simplified selective sampling(biomass-weighted average over five dominant tree species[5DT_BW],basal area weighted average over five dominant tree species[5DT_AW],biomass-weighted average over all tree species[AT_BW]and basal area weighted average over all tree species[AT_AW]).We found that the default values for SLA and leaf C:N embedded in the Biome-BGC v4.2 were higher than the five computational methods produced across the nine sites,with deviations ranging from 28.0 to 73.3%.In addition,there were only slight deviations(<10%)between the whole plant community sampling(AP_BW)predicted NPP and the four simplified selective sampling methods,and no significant difference between the predictions of AT_BW and AP_BW except the Shennongjia site.The findings in this study highlights the critical importance of computational strategies for community-level parameterization in ecosystem process modelling,and will support the choice of parameterization methods.

关键词： Biome-BGC Community traits Forest Ecosystems Model parameterization

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A Methodology for Assessing Axial Compressor Stability with Inlet Temperature Ramp Distortion

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Journal of Thermal Science 2024年第3期33卷 856-871页

作者： sun Dakun GU Benhao NING fangfei fang Yibo DONG Xu XU Dengke sun Xiaofeng School of Energy and Power Engineering Beihang UniversityBeijing102206China Research Institute of Aero-engine Beihang UniversityBeijing102206China

Based on a small perturbation stability model for periodic flow,the effects of inlet total temperature ramp distortion on the axial compressor are investigated and the compressor stability is quantitatively evaluated.In the beginning,a small perturbation stability model for the periodic flow in compressors is proposed,referring to the governing equations of the Harmonic Balance Method.This stability model is validated on a single-stage low-speed compressor TA36 with uniform inlet flow.Then,the unsteady flow of TA36 with different inlet total temperature ramps and constant back pressure is simulated based on the Harmonic Balance Method.Based on these simulations,the compressor stability is analyzed using the proposed small perturbation model.Further,the Dynamic Mode Decomposition method is employed to accurately extract pressure oscillations.The two parameters of the temperature ramp,ramp rate and Strouhal number,are discussed in this paper.The results indicate the occurrence and extension of hysteresis loops in the rows,and a decrease in compressor stability with increasing ramp rate.Compressor performance is divided into two phases,stable and limit,based on the ramp rate.Furthermore,the model predictions suggest that a decrease in period length and an increase in Strouhal number lead to improved compressor stability.The DMD results imply that for compressors with inlet temperature ramp distortion,the increase of high-order modes and oscillations at the rotor tip is always the signal of decreasing stability.

关键词： axial compressor stability small perturbation model inlet temperature ramp distortion harmonic balance method dynamic mode decomposition method

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Research on the identification of the production origin of Angelica dahurica using LIBS technology combined with machine learning algorithms

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Optoelectronics Letters 2024年第3期20卷 171-176页

作者： sun Jiaxing LI Honglian YAO Yuhang YAN Qiongyan DONG fang College of Quality and Technology Supervising Hebei UniversityBaoding 071000China National and Local Joint Engineering Center of Measuring Instruments and Metrology Systems Baoding 071000China Key Laboratory of Energy Measurement and Safety Detection Technology in Hebei Province Baoding 071000China

The origin of Angelica dahurica medicinal herbs varies, and their pharmacological effects also differ. In order to achieve rapid and accurate identification of the origin of Angelica dahurica medicinal herbs, this study utilizes laser induced breakdown spectroscopy(LIBS) technology combined with machine learning algorithms to identify the original source of Angelica dahurica. Sliced samples of Angelica dahurica were taken from four regions: Hebei, Henan, Zhejiang, and Sichuan. The spectral data from the sliced samples were used as features, and different algorithms including support vector machine(SVM), back propagation(BP) neural network, genetic algorithm-back propagation(GA-BP) neural network, particle swarm optimization-back propagation(PSO-BP) neural network, convolutional neural network(CNN), and CNN-SVM were employed to classify the origin of Angelica dahurica samples.

关键词： neural origin network

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OFDMA-Based Unsourced Random Access in LEO Satellite Internet of Things

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China Communications 2024年第1期21卷 13-23页

作者： Jiaqi fang Gangle sun Wenjin Wang Li You Rui Ding National Mobile Communications Research Laboratory Southeast UniversityNanjing 210096China Purple Mountain Laboratories Nanjing 211100China Institute of Telecommunication Satellite CASTBeijing 100094China

This paper investigates the low earth orbit(LEO)satellite-enabled coded compressed sensing(CCS)unsourced random access(URA)in orthogonal frequency division multiple access(OFDMA)framework,where a massive uniform planar array(UPA)is equipped on the satellite.In LEO satellite communications,unavoidable timing and frequency offsets cause phase shifts in the transmitted signals,substantially diminishing the decoding performance of current terrestrial CCS URA receiver.To cope with this issue,we expand the inner codebook with predefined timing and frequency offsets and formulate the inner decoding as a tractable compressed sensing(CS)problem.Additionally,we leverage the inherent sparsity of the UPA-equipped LEO satellite angular domain channels,thereby enabling the outer decoder to support more active devices.Furthermore,the outputs of the outer decoder are used to reduce the search space of the inner decoder,which cuts down the computational complexity and accelerates the convergence of the inner decoding.Simulation results verify the effectiveness of the proposed scheme.

关键词： LEO OFDMA satellite unsourced random access UPA

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Characteristics and triggering mechanisms of early negative Indian Ocean Dipole

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Acta Oceanologica Sinica 2024年第3期43卷 59-65页

作者： Yue fang Shuangwen sun Yongcan Zu Jianhu Wang Lin Feng First Institute of Oceanography and Key Laboratory of Marine Science and Numerical ModelingMinistry of Natural ResourcesQingdao 266061China Laboratory for Regional Oceanography and Numerical Modeling Qingdao Marine Science and Technology CenterQingdao 266237China Shandong Key Laboratory of Marine Science and Numerical Modeling Qingdao 266061China

Negative Indian Ocean Dipole(nIOD)can exert great impacts on global climate and can also strongly influence the climate in China.Early nIOD is a major type of nIOD,which can induce more pronounced climate anomalies in summer than La Niña-related nIOD.However,the characteristics and triggering mechanisms of early nIOD are unclear.Our results based on reanalysis datasets indicate that the early nIOD and La Niña-related nIOD are the two major types of nIOD,and the former accounts for over one third of all the nIOD events in the past six decades.These two types of nIODs are similar in their intensities,but are different in their spatial patterns and seasonal cycles.The early nIOD,which develops in spring and peaks in summer,is one season earlier than the La Niña-related nIOD.The spatial pattern of the wind anomaly associated with early nIOD exhibits a winter monsoon-like pattern,with strong westerly anomalies in the equatorial Indian Ocean and eastly anomalies in the northern Indian Ocean.Opposite to the triggering mechanism of early positve IOD,the early nIOD is induced by delayed Indian summer monsoon onset.The results of this study are helpful for improving the prediction skill of IOD and its climate impacts.

关键词： Indian Ocean Dipole(IOD) triggering mechanism Indian summer monsoon seasonal cycle negative IOD

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