Proppant transport within fractures is one of the most critical tasks in oil,gas and geothermal reservoir stimulation,as it largely determines the ultimate performance of the operating well.Proppant transport in rough...Proppant transport within fractures is one of the most critical tasks in oil,gas and geothermal reservoir stimulation,as it largely determines the ultimate performance of the operating well.Proppant transport in rough fracture networks is still a relatively new area of research and the associated transport mechanisms are still unclear.In this study,representative parameters of rough fracture surfaces formed by supercritical CO_(2) fracturing were used to generate a rough fracture network model based on a spectral synthesis method.Computational fluid dynamics(CFD)coupled with the discrete element method(DEM)was used to study proppant transport in this rough fracture network.To reveal the turning transport mechanism of proppants into branching fractures at the intersections of rough fracture networks,a comparison was made with the behavior within smooth fracture networks,and the effect of key pumping parameters on the proppant placement in a secondary fracture was analyzed.The results show that the transport behavior of proppant in rough fracture networks is very different from that of the one in the smooth fracture networks.The turning transport mechanisms of proppant into secondary fractures in rough fracture networks are gravity-driven sliding,high velocity fluid suspension,and fracture structure induction.Under the same injection conditions,supercritical CO_(2)with high flow Reynolds number still has a weaker ability to transport proppant into secondary fractures than water.Thickening of the supercritical CO_(2)needs to be increased beyond a certain value to have a significant effect on proppant carrying,and under the temperature and pressure conditions of this paper,it needs to be increased more than 20 times(about 0.94 m Pa s).Increasing the injection velocity and decreasing the proppant concentration facilitates the entry of proppant into the branching fractures,which in turn results in a larger stimulated reservoir volume.The results help to understand the proppant transport and placement process in rough fracture networks formed by reservoir stimulation,and provide a theoretical reference for the optimization of proppant pumping parameters in hydraulic fracturing.展开更多
Ever-increasing emissions of anthropogenic carbon dioxide(CO_(2))cause global environmental and climate challenges.Inspired by biological photosynthesis,developing effective strategies NeuNlto up-cycle CO_(2)into high...Ever-increasing emissions of anthropogenic carbon dioxide(CO_(2))cause global environmental and climate challenges.Inspired by biological photosynthesis,developing effective strategies NeuNlto up-cycle CO_(2)into high-value organics is crucial.Electrochemical CO_(2)reduction reaction(CO_(2)RR)is highly promising to convert CO_(2)into economically viable carbon-based chemicals or fuels under mild process conditions.Herein,mesoporous indium supported on multi-walled carbon nanotubes(mp-In@MWCNTs)is synthesized via a facile wet chemical method.The mp-In@MWCNTs electrocatalysts exhibit high CO_(2)RR performance in reducing CO_(2)into formate.An outstanding activity(current density-78.5 mA cm^(-2)),high conversion efficiency(Faradaic efficiency of formate over 90%),and persistent stability(∼30 h)for selective CO_(2)-to-formate conversion are observed.The outstanding CO_(2)RR process performance is attributed to the unique structures with mesoporous surfaces and a conductive network,which promote the adsorption and desorption of reactants and intermediates while improving electron transfer.These findings provide guiding principles for synthesizing conductive metal-based electrocatalysts for high-performance CO_(2)conversion.展开更多
In this paper,we jointly design the power control and position dispatch for Multi-Unmanned Aerial Vehicle(UAV)-enabled communication in Device-to-Device(D2D)networks.Our objective is to maximize the total transmission...In this paper,we jointly design the power control and position dispatch for Multi-Unmanned Aerial Vehicle(UAV)-enabled communication in Device-to-Device(D2D)networks.Our objective is to maximize the total transmission rate of Downlink Users(DUs).Meanwhile,the Quality of Service(QoS)of all D2D users must be satisfied.We comprehensively considered the interference among D2D communications and downlink transmissions.The original problem is strongly non-convex,which requires high computational complexity for traditional optimization methods.And to make matters worse,the results are not necessarily globally optimal.In this paper,we propose a novel Graph Neural Networks(GNN)based approach that can map the considered system into a specific graph structure and achieve the optimal solution in a low complexity manner.Particularly,we first construct a GNN-based model for the proposed network,in which the transmission links and interference links are formulated as vertexes and edges,respectively.Then,by taking the channel state information and the coordinates of ground users as the inputs,as well as the location of UAVs and the transmission power of all transmitters as outputs,we obtain the mapping from inputs to outputs through training the parameters of GNN.Simulation results verified that the way to maximize the total transmission rate of DUs can be extracted effectively via the training on samples.Moreover,it also shows that the performance of proposed GNN-based method is better than that of traditional means.展开更多
Interference management is one of the most important issues in the device-to-device(D2D)-enabled heterogeneous cellular networks(HetCNets)due to the coexistence of massive cellular and D2D devices in which D2D devices...Interference management is one of the most important issues in the device-to-device(D2D)-enabled heterogeneous cellular networks(HetCNets)due to the coexistence of massive cellular and D2D devices in which D2D devices reuse the cellular spectrum.To alleviate the interference,an efficient interference management way is to set exclusion zones around the cellular receivers.In this paper,we adopt a stochastic geometry approach to analyze the outage probabilities of cellular and D2D users in the D2D-enabled HetCNets.The main difficulties contain three aspects:1)how to model the location randomness of base stations,cellular and D2D users in practical networks;2)how to capture the randomness and interrelation of cellular and D2D transmissions due to the existence of random exclusion zones;3)how to characterize the different types of interference and their impacts on the outage probabilities of cellular and D2D users.We then run extensive Monte-Carlo simulations which manifest that our theoretical model is very accurate.展开更多
SnO_(2) has been extensively investigated as an anode material for sodium-ion batteries(SIBs)and potassium-ion batteries(PIBs)due to its high Na/K storage capacity,high abundance,and low toxicity.However,the sluggish ...SnO_(2) has been extensively investigated as an anode material for sodium-ion batteries(SIBs)and potassium-ion batteries(PIBs)due to its high Na/K storage capacity,high abundance,and low toxicity.However,the sluggish reaction kinetics,low electronic conductivity,and large volume changes during charge and discharge hinder the practical applications of SnO_(2)-based electrodes for SIBs and PIBs.Engineering rational structures with fast charge/ion transfer and robust stability is important to overcoming these challenges.Herein,S-doped SnO_(2)(S-SnO_(2))quantum dots(QDs)(≈3 nm)encapsulated in an N,S codoped carbon fiber networks(S-SnO_(2)-CFN)are rationally fabricated using a sequential freeze-drying,calcination,and S-doping strategy.Experimental analysis and density functional theory calculations reveal that the integration of S-SnO_(2) QDs with N,S codoped carbon fiber network remarkably decreases the adsorption energies of Na/K atoms in the interlayer of SnO_(2)-CFN,and the S doping can increase the conductivity of SnO_(2),thereby enhancing the ion transfer kinetics.The synergistic interaction between S-SnO_(2) QDs and N,S codoped carbon fiber network results in a composite with fast Na+/K+storage and extraordinary long-term cyclability.Specifically,the S-SnO_(2)-CFN delivers high rate capacities of 141.0 mAh g^(−1) at 20 A g^(−1) in SIBs and 102.8 mAh g^(−1) at 10 A g^(−1) in PIBs.Impressively,it delivers ultra-stable sodium storage up to 10,000 cycles at 5 A g^(−1) and potassium storage up to 5000 cycles at 2 A g^(−1).This study provides insights into constructing metal oxide-based carbon fiber network structures for high-performance electrochemical energy storage and conversion devices.展开更多
To reduce CO_(2) emissions in response to global climate change,shale reservoirs could be ideal candidates for long-term carbon geo-sequestration involving multi-scale transport processes.However,most current CO_(2) s...To reduce CO_(2) emissions in response to global climate change,shale reservoirs could be ideal candidates for long-term carbon geo-sequestration involving multi-scale transport processes.However,most current CO_(2) sequestration models do not adequately consider multiple transport mechanisms.Moreover,the evaluation of CO_(2) storage processes usually involves laborious and time-consuming numerical simulations unsuitable for practical prediction and decision-making.In this paper,an integrated model involving gas diffusion,adsorption,dissolution,slip flow,and Darcy flow is proposed to accurately characterize CO_(2) storage in depleted shale reservoirs,supporting the establishment of a training database.On this basis,a hybrid physics-informed data-driven neural network(HPDNN)is developed as a deep learning surrogate for prediction and inversion.By incorporating multiple sources of scientific knowledge,the HPDNN can be configured with limited simulation resources,significantly accelerating the forward and inversion processes.Furthermore,the HPDNN can more intelligently predict injection performance,precisely perform reservoir parameter inversion,and reasonably evaluate the CO_(2) storage capacity under complicated scenarios.The validation and test results demonstrate that the HPDNN can ensure high accuracy and strong robustness across an extensive applicability range when dealing with field data with multiple noise sources.This study has tremendous potential to replace traditional modeling tools for predicting and making decisions about CO_(2) storage projects in depleted shale reservoirs.展开更多
BACKGROUND Glucagon-like peptide-1 receptor agonists(GLP-1RA)and sodium-glucose co-transporter-2 inhibitors(SGLT-2I)are associated with significant cardiovascular benefit in type 2 diabetes(T2D).However,GLP-1RA or SGL...BACKGROUND Glucagon-like peptide-1 receptor agonists(GLP-1RA)and sodium-glucose co-transporter-2 inhibitors(SGLT-2I)are associated with significant cardiovascular benefit in type 2 diabetes(T2D).However,GLP-1RA or SGLT-2I alone may not improve some cardiovascular outcomes in patients with prior cardiovascular co-morbidities.AIM To explore whether combining GLP-1RA and SGLT-2I can achieve additional benefit in preventing cardiovascular diseases in T2D.METHODS The systematic review was conducted according to PRISMA recommendations.The protocol was registered on PROSPERO(ID:42022385007).A total of 107049 participants from eligible cardiovascular outcomes trials of GLP-1RA and SGLT-2I were included in network meta-regressions to estimate cardiovascular benefit of the combination treatment.Effect modification of prior myocardial infarction(MI)and heart failure(HF)was also explored to provide clinical insight as to when the INTRODUCTION The macro-and micro-vascular benefits of glucagon-like peptide-1 receptor agonists(GLP-1RA)and sodium-glucose co-transporter-2 inhibitors(SGLT-2I)are independent of their glucose-lowering effects[1].In patients with type 2 diabetes(T2D),the major cardiovascular outcome trials(CVOT)showed that dipeptidyl peptidase-4 inhibitors(DPP-4I)did not improve cardiovascular outcomes[2],whereas cardiovascular benefit of GLP-1RA or SGLT-2I was significant[3,4].Further subgroup analyses indicated that the background cardiovascular risk should be considered when examining the cardiovascular outcomes of these newer glucose-lowering medications.For instance,prevention of major adverse cardiovascular events(MACE)was only seen in those patients with baseline atherosclerotic cardiovascular disease[3,4].Moreover,a series of CVOT conducted in patients with heart failure(HF)have demonstrated that(compared with placebo)SGLT-2I significantly reduced risk of hospitalization for HF or cardiovascular death,irrespective of their history of T2D[5-8].However,similar cardiovascular benefits were not observed in those with myocardial infarction(MI)[9,10].Cardiovascular co-morbidities are not only approximately twice as common but are also associated with dispropor-tionately worse cardiovascular outcomes in patients with T2D,compared to the general population[11].Therefore,it is of clinical importance to investigate whether the combination treatment of GLP-1RA and SGLT-2I could achieve greater cardiovascular benefit,particularly when considering patients with cardiovascular co-morbidities who may not gain sufficient cardiovascular protection from the monotherapies.This systematic review with multiple network meta-regressions was mainly aimed to explore whether combining GLP-1RA and SGLT-2I can provide additional cardiovascular benefit in T2D.Cardiovascular outcomes of these newer antidiabetic medications were also estimated under effect modification of prior cardiovascular diseases.This was to provide clinical insight as to when the combination treatment might be prioritized.展开更多
[Objectives]To explore the mechanism of Gegen Qinlian Decoction in treating type 2 diabetes mellitus(T2DM)complicated with non-alcoholic fatty liver disease(NAFLD)by analyzing the effective components of Gegen Qinlian...[Objectives]To explore the mechanism of Gegen Qinlian Decoction in treating type 2 diabetes mellitus(T2DM)complicated with non-alcoholic fatty liver disease(NAFLD)by analyzing the effective components of Gegen Qinlian Decoction.[Methods]TCMSP database was used to analyze the active components of Gegen Qinlian Decoction,and pubchem and Swiss ADME databases were also used to predict drug targets,extract T2DM complicated with NAFLD targets from OMIM and Genecards databases.Venny plot was drawn to obtain intersection targets,and finally Cytoscape was used to make core target maps and drug-target-disease network maps.Using DAVID and Metascape database to analyze the intersection targets,the gene ontology information of Go and KEGG was obtained.Microbial informatics technology was used to visualize GO,and Cytoscape was used to make drug-target-disease network map-enrichment pathway map.[Results]The network pharmacological analysis showed that Gegen Qinlian Decoction acted on the key targets of type 2 diabetes mellitus complicated with non-alcoholic fatty liver disease,such as ALB and ALT1,through many components,and achieved the purpose of treating this disease.The chemical constituents of the drug include formononetin,5-hydroxyisomucronulatol-2,5-2-O-glucoside,cholesteryl laurate,isoliquiritigenin,etc.[Conclusions]This study provides a new idea and theoretical support for future drug research and clinical practice.展开更多
Background:Radix Aconiti Lateralis Preparata(Fu-zi)is a traditional Chinese medicinal herb,which has been widely used in the clinic and has potent anti-inflammatory activities.we aimed to explore the mechanisms of ext...Background:Radix Aconiti Lateralis Preparata(Fu-zi)is a traditional Chinese medicinal herb,which has been widely used in the clinic and has potent anti-inflammatory activities.we aimed to explore the mechanisms of extract containing alkaloids from different Fu-zi Processed Products(FPP)in treating inflammation,especially rheumatoid arthritis(RA).Methods:Firstly,using network pharmacology technology,the ingredients,and targets of Fu-zi were obtained by searching and screening,the targets involving RA were acquired,the intersection targets were constructed a"component-target-pathway"network.A comprehensive investigation was conducted on the anti-rheumatoid arthritis mechanisms of 5 FPPs in lipopolysaccharide(LPS)induced RAW264.7 cells,which serve as a model for RA.The production of NO and inflammatory cytokines were measured by ELISA kit.Quantitative Real-time PCR(qRT-PCR)was utilized to measure the mRNA levels.COX-2/PGE2 signaling pathway-associated proteins were determined by western blot.Results:According to a network pharmacological study,16 chemical components and 43 common targets were found in Fu-zi and 6 key targets including PTGS2 were closely related to the mechanism of Fu-zi in treating RA.The in vitro study revealed that the levels of NO,TNF-α,and IL-1βwere substantially decreased by the 5 FPPs.The 5 FPPs significantly suppressed the expression of proteins COX-2,iNOS,and NF-κB,with particularly notable effects observed for PFZ and XFZ.Conclusion:Altogether,these results demonstrated that the 5 PPS containing alkaloids have a good anti-RA-related inflammatory effect,and the mechanism may be related to COX-2/PGE2 signaling pathway,particularly,Fu-zi prepared utilizing a traditional Chinese technique.展开更多
In highly dynamic and heterogeneous vehicular communication networks,it is challenging to efficiently utilize network resources and ensure demanding performance requirements of safetyrelated applications.This paper in...In highly dynamic and heterogeneous vehicular communication networks,it is challenging to efficiently utilize network resources and ensure demanding performance requirements of safetyrelated applications.This paper investigates machinelearning-assisted transmission design in a typical multi-user vehicle-to-vehicle(V2V)communication scenario.The transmission process proceeds sequentially along the discrete time steps,where several source nodes intend to deliver multiple different types of messages to their respective destinations within the same spectrum.Due to rapid movement of vehicles,real-time acquirement of channel knowledge and central coordination of all transmission actions are in general hard to realize.We consider applying multi-agent deep reinforcement learning(MADRL)to handle this issue.By transforming the transmission design problem into a stochastic game,a multi-agent proximal policy optimization(MAPPO)algorithm under a centralized training and decentralized execution framework is proposed such that each source decides its own transmission message type,power level,and data rate,based on local observations of the environment and feedback,to maximize its energy efficiency.Via simulations we show that our method achieves better performance over conventional methods.展开更多
The coronavirus disease 2019(COVID-19)pandemic has greatly damaged human society,but the origins and early transmission patterns of the severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)pathogen remain unclea...The coronavirus disease 2019(COVID-19)pandemic has greatly damaged human society,but the origins and early transmission patterns of the severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)pathogen remain unclear.Here,we reconstructed the transmission networks of SARS-CoV-2 during the first three and six months since its first report based on ancestor-offspring relationships using BANAL-52-referenced mutations.We explored the position(i.e.,root,middle,or tip)of early detected samples in the evolutionary tree of SARS-CoV-2.In total,6799 transmission chains and 1766 transmission networks were reconstructed,with chain lengths ranging from 1-9 nodes.The root node samples of the 1766 transmission networks were from 58 countries or regions and showed no common ancestor,indicating the occurrence of many independent or parallel transmissions of SARS-CoV-2 when first detected(i.e.,all samples were located at the tip position of the evolutionary tree).No root node sample was found in any sample(n=31,all from the Chinese mainland)collected in the first 15 days from 24 December 2019.Results using six-month data or RaTG13-referenced mutation data were similar.The reconstruction method was verified using a simulation approach.Our results suggest that SARS-CoV-2 may have already been spreading independently worldwide before the outbreak of COVID-19 in Wuhan,China.Thus,a comprehensive global survey of human and animal samples is essential to explore the origins of SARS-CoV-2 and its natural reservoirs and hosts.展开更多
In this work,we consider the performance analysis of state dependent priority traffic and scheduling in device to device(D2D)heterogeneous networks.There are two priority transmission types of data in wireless communi...In this work,we consider the performance analysis of state dependent priority traffic and scheduling in device to device(D2D)heterogeneous networks.There are two priority transmission types of data in wireless communication,such as video or telephone,which always meet the requirements of high priority(HP)data transmission first.If there is a large amount of low priority(LP)data,there will be a large amount of LP data that cannot be sent.This situation will cause excessive delay of LP data and packet dropping probability.In order to solve this problem,the data transmission process of high priority queue and low priority queue is studied.Considering the priority jump strategy to the priority queuing model,the queuing process with two priority data is modeled as a two-dimensionalMarkov chain.A state dependent priority jump queuing strategy is proposed,which can improve the discarding performance of low priority data.The quasi birth and death process method(QBD)and fixed point iterationmethod are used to solve the causality,and the steady-state probability distribution is further obtained.Then,performance parameters such as average queue length,average throughput,average delay and packet dropping probability for both high and low priority data can be expressed.The simulation results verify the correctness of the theoretical derivation.Meanwhile,the proposed priority jump queuing strategy can significantly improve the drop performance of low-priority data.展开更多
针对火电机组SO_(2)排放质量浓度的影响因素众多,难以准确预测的问题,提出一种改进向量加权平均(weighted mean of vectors,INFO)算法与双向长短期记忆(bi-directional long short term memory,Bi-LSTM)神经网络相结合的预测模型(改进IN...针对火电机组SO_(2)排放质量浓度的影响因素众多,难以准确预测的问题,提出一种改进向量加权平均(weighted mean of vectors,INFO)算法与双向长短期记忆(bi-directional long short term memory,Bi-LSTM)神经网络相结合的预测模型(改进INFO-Bi-LSTM模型)。采用Circle混沌映射和反向学习产生高质量初始化种群,引入自适应t分布提升INFO算法跳出局部最优解和全局搜索的能力。选取改进INFO-Bi-LSTM模型和多种预测模型对炉内外联合脱硫过程中4种典型工况下的SO_(2)排放质量浓度进行预测,将预测结果进行验证对比。结果表明:改进INFO算法的寻优能力得到提升,并且改进INFO-Bi-LSTM模型精度更高,更加适用于SO_(2)排放质量浓度的预测,可为变工况下的脱硫控制提供控制理论支撑。展开更多
Realizing a lithium sulfide(Li_(2)S)cathode with both high energy density and a long lifespan requires an innovative cathode design that maximizes electrochemical performance and resists electrode deterioration.Herein...Realizing a lithium sulfide(Li_(2)S)cathode with both high energy density and a long lifespan requires an innovative cathode design that maximizes electrochemical performance and resists electrode deterioration.Herein,a high-loading Li_(2)S-based cathode with micrometric Li_(2)S particles composed of two-dimensional graphene(Gr)and one-dimensional carbon nanotubes(CNTs)in a compact geometry is developed,and the role of CNTs in stable cycling of high-capacity Li–S batteries is emphasized.In a dimensionally combined carbon matrix,CNTs embedded within the Gr sheets create robust and sustainable electron diffusion pathways while suppressing the passivation of the active carbon surface.As a unique point,during the first charging process,the proposed cathode is fully activated through the direct conversion of Li_(2)S into S_(8) without inducing lithium polysulfide formation.The direct conversion of Li_(2)S into S_(8) in the composite cathode is ubiquitously investigated using the combined study of in situ Raman spectroscopy,in situ optical microscopy,and cryogenic transmission electron microscopy.The composite cathode demonstrates unprecedented electrochemical properties even with a high Li_(2)S loading of 10 mg cm^(–2);in particular,the practical and safe Li–S full cell coupled with a graphite anode shows ultra-long-term cycling stability over 800 cycles.展开更多
目的比较非奈利酮与钠-葡萄糖共转运蛋白-2(sodium-glucose cotransporter-2,SGLT2)抑制剂对2型糖尿病和/或慢性肾脏病患者心血管事件的影响。方法检索PubMed、Cochrane Library、Web of Science和Embase数据库关于2型糖尿病和/或慢性...目的比较非奈利酮与钠-葡萄糖共转运蛋白-2(sodium-glucose cotransporter-2,SGLT2)抑制剂对2型糖尿病和/或慢性肾脏病患者心血管事件的影响。方法检索PubMed、Cochrane Library、Web of Science和Embase数据库关于2型糖尿病和/或慢性肾脏病患者的随机对照试验,时间为建库至2023年7月3日。基于频率模型,使用STATA 17.0软件进行网状荟萃分析(network meta-analysis,NMA)。结果共纳入7项随机对照试验,包括33206例患者。涉及的治疗方式包括非奈利酮和SGLT2抑制剂,其中SGLT2抑制剂包含恩格列净、卡格列净、达格列净和索格列净(双重SGLT抑制剂)。在心血管复合事件方面,根据累计曲线下的概率面积(surface under the cumulative ranking area,SUCRA)排序,索格列净最有效。在心血管死亡方面,根据SUCRA排序,恩格列净最有效。在心力衰竭住院方面,根据SUCRA排序,卡格列净最有效。在全因死亡方面,根据SUCRA排序,达格列净最有效。非奈利酮和SGLT2抑制剂在不良事件、严重不良事件和急性肾损害的安全性方面比较,差异均无统计学意义(均P>0.05)。与采用非奈利酮治疗的患者相比,采用SGLT2抑制剂治疗的患者高钾血症发生率更低(RR=0.41,95%CI 0.32~0.52)。结论与非奈利酮相比,SGLT2抑制剂能更好地降低心血管事件的发生率,可作为2型糖尿病和/或慢性肾脏病患者的基础治疗,帮助预防或减少心血管事件。展开更多
Background:The development and prognosis of breast cancer are intricately linked to psychological stress.In addition,depression is the most common psychological comorbidity among breast cancer survivors,and reportedly...Background:The development and prognosis of breast cancer are intricately linked to psychological stress.In addition,depression is the most common psychological comorbidity among breast cancer survivors,and reportedly,Fang-Xia-Dihuang decoction(FXDH)can effectively manage depression in such patients.However,its pharmacological and molecular mechanisms remain obscure.Methods:Public databases were used for obtaining active components and related targets.Main active components were further verified by ultra-high-performance liquid chromatography-high-resolution mass spectrometry(UPLC-HRMS).Protein–protein interaction and enrichment analyses were taken to predict potential hub targets and related pathways.Molecule docking was used to understand the interactions between main compounds and hub targets.In addition,an animal model of breast cancer combined with depression was established to evaluate the intervention effect of FXDH and verify the pathways screened by network pharmacology.Results:174 active components of FXDH and 163 intersection targets of FXDH,breast cancer,and depression were identified.Quercetin,methyl ferulate,luteolin,ferulaldehyde,wogonin,and diincarvilone were identified as the principal active components of FXDH.Protein–protein interaction and KEGG enrichment analyses revealed that the phosphoinositide-3-kinase–protein kinase B(PI3K/AKT)and Janus kinase/signal transducer and activator of transcription(JAK2/STAT3)signaling pathways played a crucial role in mediating the efficacy of FXDH for inhibiting breast cancer progression induced by depression.In addition,in vivo experiments revealed that FXDH ameliorated depression-like behavior in mice and inhibited excessive tumor growth in mice with breast cancer and depression.FXDH treatment downregulated the expression of epinephrine,PI3K,AKT,STAT3,and JAK2 compared with the control treatment(p<0.05).Molecular docking verified the relationship between the six primary components of FXDH and the three most important targets,including phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha(PIK3CA),AKT,and STAT3.Conclusion:This study provides a scientific basis to support the clinical application of FXDH for improving depression-like behavior and inhibiting breast cancer progression promoted by chronic stress.The therapeutic effects FXDH may be closely related to the PI3K/AKT and JAK2/STAT3 pathways.This finding helps better understand the regulatory mechanisms underlying the efficacy of FXDH.展开更多
基金the support from the National Key Research and Development Program of China(Grant No.2022YFE0137200)the Natural Science Basic Research Program of Shaanxi Province,China(Program No.2024JC-YBQN-0381,2023JC-QN-0403)+2 种基金the Natural Science Basic Research Program of Shaanxi Province,China(Program No.2022JC-37)the Innovation Capability Support Program of Shaanxi(Program No.2023-CX-TD31)the Funded by Open Foundation of Shaanxi Key Laboratory of Carbon Dioxide Sequestration and Enhanced Oil Recovery,and the Youth Innovation Team of Shaanxi Universities。
文摘Proppant transport within fractures is one of the most critical tasks in oil,gas and geothermal reservoir stimulation,as it largely determines the ultimate performance of the operating well.Proppant transport in rough fracture networks is still a relatively new area of research and the associated transport mechanisms are still unclear.In this study,representative parameters of rough fracture surfaces formed by supercritical CO_(2) fracturing were used to generate a rough fracture network model based on a spectral synthesis method.Computational fluid dynamics(CFD)coupled with the discrete element method(DEM)was used to study proppant transport in this rough fracture network.To reveal the turning transport mechanism of proppants into branching fractures at the intersections of rough fracture networks,a comparison was made with the behavior within smooth fracture networks,and the effect of key pumping parameters on the proppant placement in a secondary fracture was analyzed.The results show that the transport behavior of proppant in rough fracture networks is very different from that of the one in the smooth fracture networks.The turning transport mechanisms of proppant into secondary fractures in rough fracture networks are gravity-driven sliding,high velocity fluid suspension,and fracture structure induction.Under the same injection conditions,supercritical CO_(2)with high flow Reynolds number still has a weaker ability to transport proppant into secondary fractures than water.Thickening of the supercritical CO_(2)needs to be increased beyond a certain value to have a significant effect on proppant carrying,and under the temperature and pressure conditions of this paper,it needs to be increased more than 20 times(about 0.94 m Pa s).Increasing the injection velocity and decreasing the proppant concentration facilitates the entry of proppant into the branching fractures,which in turn results in a larger stimulated reservoir volume.The results help to understand the proppant transport and placement process in rough fracture networks formed by reservoir stimulation,and provide a theoretical reference for the optimization of proppant pumping parameters in hydraulic fracturing.
基金Jiujiang Research Institute in Xiamen University for the partial supportthe support of QUT Faculty Centre Strategic Funding provided by the Faculty of Science and QUT Centre for a Waste-Free World+1 种基金the Australian Research Council(ARC)QUT Centre for Materials Science for partial support
文摘Ever-increasing emissions of anthropogenic carbon dioxide(CO_(2))cause global environmental and climate challenges.Inspired by biological photosynthesis,developing effective strategies NeuNlto up-cycle CO_(2)into high-value organics is crucial.Electrochemical CO_(2)reduction reaction(CO_(2)RR)is highly promising to convert CO_(2)into economically viable carbon-based chemicals or fuels under mild process conditions.Herein,mesoporous indium supported on multi-walled carbon nanotubes(mp-In@MWCNTs)is synthesized via a facile wet chemical method.The mp-In@MWCNTs electrocatalysts exhibit high CO_(2)RR performance in reducing CO_(2)into formate.An outstanding activity(current density-78.5 mA cm^(-2)),high conversion efficiency(Faradaic efficiency of formate over 90%),and persistent stability(∼30 h)for selective CO_(2)-to-formate conversion are observed.The outstanding CO_(2)RR process performance is attributed to the unique structures with mesoporous surfaces and a conductive network,which promote the adsorption and desorption of reactants and intermediates while improving electron transfer.These findings provide guiding principles for synthesizing conductive metal-based electrocatalysts for high-performance CO_(2)conversion.
基金supported in part by the National Natural Science Foundation of China(61901231)in part by the National Natural Science Foundation of China(61971238)+3 种基金in part by the Natural Science Foundation of Jiangsu Province of China(BK20180757)in part by the open project of the Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space,Ministry of Industry and Information Technology(KF20202102)in part by the China Postdoctoral Science Foundation under Grant(2020M671480)in part by the Jiangsu Planned Projects for Postdoctoral Research Funds(2020z295).
文摘In this paper,we jointly design the power control and position dispatch for Multi-Unmanned Aerial Vehicle(UAV)-enabled communication in Device-to-Device(D2D)networks.Our objective is to maximize the total transmission rate of Downlink Users(DUs).Meanwhile,the Quality of Service(QoS)of all D2D users must be satisfied.We comprehensively considered the interference among D2D communications and downlink transmissions.The original problem is strongly non-convex,which requires high computational complexity for traditional optimization methods.And to make matters worse,the results are not necessarily globally optimal.In this paper,we propose a novel Graph Neural Networks(GNN)based approach that can map the considered system into a specific graph structure and achieve the optimal solution in a low complexity manner.Particularly,we first construct a GNN-based model for the proposed network,in which the transmission links and interference links are formulated as vertexes and edges,respectively.Then,by taking the channel state information and the coordinates of ground users as the inputs,as well as the location of UAVs and the transmission power of all transmitters as outputs,we obtain the mapping from inputs to outputs through training the parameters of GNN.Simulation results verified that the way to maximize the total transmission rate of DUs can be extracted effectively via the training on samples.Moreover,it also shows that the performance of proposed GNN-based method is better than that of traditional means.
基金This work is funded in part by the Science and Technology Development Fund,Macao SAR(Grant Nos.0093/2022/A2,0076/2022/A2 and 0008/2022/AGJ)in part by the National Nature Science Foundation of China(Grant No.61872452)+3 种基金in part by Special fund for Dongguan’s Rural Revitalization Strategy in 2021(Grant No.20211800400102)in part by Dongguan Special Commissioner Project(Grant No.20211800500182)in part by Guangdong-Dongguan Joint Fund for Basic and Applied Research of Guangdong Province(Grant No.2020A1515110162)in part by University Special Fund of Guangdong Provincial Department of Education(Grant No.2022ZDZX1073).
文摘Interference management is one of the most important issues in the device-to-device(D2D)-enabled heterogeneous cellular networks(HetCNets)due to the coexistence of massive cellular and D2D devices in which D2D devices reuse the cellular spectrum.To alleviate the interference,an efficient interference management way is to set exclusion zones around the cellular receivers.In this paper,we adopt a stochastic geometry approach to analyze the outage probabilities of cellular and D2D users in the D2D-enabled HetCNets.The main difficulties contain three aspects:1)how to model the location randomness of base stations,cellular and D2D users in practical networks;2)how to capture the randomness and interrelation of cellular and D2D transmissions due to the existence of random exclusion zones;3)how to characterize the different types of interference and their impacts on the outage probabilities of cellular and D2D users.We then run extensive Monte-Carlo simulations which manifest that our theoretical model is very accurate.
基金National Natural Science Foundation of China,Grant/Award Number:51971065Innovation Program of Shanghai Municipal Education Commission,Grant/Award Number:2019-01-07-00-07-E00028。
文摘SnO_(2) has been extensively investigated as an anode material for sodium-ion batteries(SIBs)and potassium-ion batteries(PIBs)due to its high Na/K storage capacity,high abundance,and low toxicity.However,the sluggish reaction kinetics,low electronic conductivity,and large volume changes during charge and discharge hinder the practical applications of SnO_(2)-based electrodes for SIBs and PIBs.Engineering rational structures with fast charge/ion transfer and robust stability is important to overcoming these challenges.Herein,S-doped SnO_(2)(S-SnO_(2))quantum dots(QDs)(≈3 nm)encapsulated in an N,S codoped carbon fiber networks(S-SnO_(2)-CFN)are rationally fabricated using a sequential freeze-drying,calcination,and S-doping strategy.Experimental analysis and density functional theory calculations reveal that the integration of S-SnO_(2) QDs with N,S codoped carbon fiber network remarkably decreases the adsorption energies of Na/K atoms in the interlayer of SnO_(2)-CFN,and the S doping can increase the conductivity of SnO_(2),thereby enhancing the ion transfer kinetics.The synergistic interaction between S-SnO_(2) QDs and N,S codoped carbon fiber network results in a composite with fast Na+/K+storage and extraordinary long-term cyclability.Specifically,the S-SnO_(2)-CFN delivers high rate capacities of 141.0 mAh g^(−1) at 20 A g^(−1) in SIBs and 102.8 mAh g^(−1) at 10 A g^(−1) in PIBs.Impressively,it delivers ultra-stable sodium storage up to 10,000 cycles at 5 A g^(−1) and potassium storage up to 5000 cycles at 2 A g^(−1).This study provides insights into constructing metal oxide-based carbon fiber network structures for high-performance electrochemical energy storage and conversion devices.
基金This work is funded by National Natural Science Foundation of China(Nos.42202292,42141011)the Program for Jilin University(JLU)Science and Technology Innovative Research Team(No.2019TD-35).The authors would also like to thank the reviewers and editors whose critical comments are very helpful in preparing this article.
文摘To reduce CO_(2) emissions in response to global climate change,shale reservoirs could be ideal candidates for long-term carbon geo-sequestration involving multi-scale transport processes.However,most current CO_(2) sequestration models do not adequately consider multiple transport mechanisms.Moreover,the evaluation of CO_(2) storage processes usually involves laborious and time-consuming numerical simulations unsuitable for practical prediction and decision-making.In this paper,an integrated model involving gas diffusion,adsorption,dissolution,slip flow,and Darcy flow is proposed to accurately characterize CO_(2) storage in depleted shale reservoirs,supporting the establishment of a training database.On this basis,a hybrid physics-informed data-driven neural network(HPDNN)is developed as a deep learning surrogate for prediction and inversion.By incorporating multiple sources of scientific knowledge,the HPDNN can be configured with limited simulation resources,significantly accelerating the forward and inversion processes.Furthermore,the HPDNN can more intelligently predict injection performance,precisely perform reservoir parameter inversion,and reasonably evaluate the CO_(2) storage capacity under complicated scenarios.The validation and test results demonstrate that the HPDNN can ensure high accuracy and strong robustness across an extensive applicability range when dealing with field data with multiple noise sources.This study has tremendous potential to replace traditional modeling tools for predicting and making decisions about CO_(2) storage projects in depleted shale reservoirs.
基金Supported by China Scholarship Council,No.202006920018Key Talent Program for Medical Applications of Nuclear Technology,No.XKTJ-HRC2021007+2 种基金the Second Affiliated Hospital of Soochow University,No.SDFEYBS1815 and No.SDFEYBS2008National Natural Science Foundation of China,No.82170831The Jiangsu Innovation&Career Fund for PhD 2019.
文摘BACKGROUND Glucagon-like peptide-1 receptor agonists(GLP-1RA)and sodium-glucose co-transporter-2 inhibitors(SGLT-2I)are associated with significant cardiovascular benefit in type 2 diabetes(T2D).However,GLP-1RA or SGLT-2I alone may not improve some cardiovascular outcomes in patients with prior cardiovascular co-morbidities.AIM To explore whether combining GLP-1RA and SGLT-2I can achieve additional benefit in preventing cardiovascular diseases in T2D.METHODS The systematic review was conducted according to PRISMA recommendations.The protocol was registered on PROSPERO(ID:42022385007).A total of 107049 participants from eligible cardiovascular outcomes trials of GLP-1RA and SGLT-2I were included in network meta-regressions to estimate cardiovascular benefit of the combination treatment.Effect modification of prior myocardial infarction(MI)and heart failure(HF)was also explored to provide clinical insight as to when the INTRODUCTION The macro-and micro-vascular benefits of glucagon-like peptide-1 receptor agonists(GLP-1RA)and sodium-glucose co-transporter-2 inhibitors(SGLT-2I)are independent of their glucose-lowering effects[1].In patients with type 2 diabetes(T2D),the major cardiovascular outcome trials(CVOT)showed that dipeptidyl peptidase-4 inhibitors(DPP-4I)did not improve cardiovascular outcomes[2],whereas cardiovascular benefit of GLP-1RA or SGLT-2I was significant[3,4].Further subgroup analyses indicated that the background cardiovascular risk should be considered when examining the cardiovascular outcomes of these newer glucose-lowering medications.For instance,prevention of major adverse cardiovascular events(MACE)was only seen in those patients with baseline atherosclerotic cardiovascular disease[3,4].Moreover,a series of CVOT conducted in patients with heart failure(HF)have demonstrated that(compared with placebo)SGLT-2I significantly reduced risk of hospitalization for HF or cardiovascular death,irrespective of their history of T2D[5-8].However,similar cardiovascular benefits were not observed in those with myocardial infarction(MI)[9,10].Cardiovascular co-morbidities are not only approximately twice as common but are also associated with dispropor-tionately worse cardiovascular outcomes in patients with T2D,compared to the general population[11].Therefore,it is of clinical importance to investigate whether the combination treatment of GLP-1RA and SGLT-2I could achieve greater cardiovascular benefit,particularly when considering patients with cardiovascular co-morbidities who may not gain sufficient cardiovascular protection from the monotherapies.This systematic review with multiple network meta-regressions was mainly aimed to explore whether combining GLP-1RA and SGLT-2I can provide additional cardiovascular benefit in T2D.Cardiovascular outcomes of these newer antidiabetic medications were also estimated under effect modification of prior cardiovascular diseases.This was to provide clinical insight as to when the combination treatment might be prioritized.
基金Guangxi Key R&D Program Project(GuiKe AB18221095)National and Autonomous Region-Level College Student Innovation and Entrepreneurship Training Funding Project(202210599009)High-level Talent Research Project of Youjiang Medical University for Nationalities(01002018079).
文摘[Objectives]To explore the mechanism of Gegen Qinlian Decoction in treating type 2 diabetes mellitus(T2DM)complicated with non-alcoholic fatty liver disease(NAFLD)by analyzing the effective components of Gegen Qinlian Decoction.[Methods]TCMSP database was used to analyze the active components of Gegen Qinlian Decoction,and pubchem and Swiss ADME databases were also used to predict drug targets,extract T2DM complicated with NAFLD targets from OMIM and Genecards databases.Venny plot was drawn to obtain intersection targets,and finally Cytoscape was used to make core target maps and drug-target-disease network maps.Using DAVID and Metascape database to analyze the intersection targets,the gene ontology information of Go and KEGG was obtained.Microbial informatics technology was used to visualize GO,and Cytoscape was used to make drug-target-disease network map-enrichment pathway map.[Results]The network pharmacological analysis showed that Gegen Qinlian Decoction acted on the key targets of type 2 diabetes mellitus complicated with non-alcoholic fatty liver disease,such as ALB and ALT1,through many components,and achieved the purpose of treating this disease.The chemical constituents of the drug include formononetin,5-hydroxyisomucronulatol-2,5-2-O-glucoside,cholesteryl laurate,isoliquiritigenin,etc.[Conclusions]This study provides a new idea and theoretical support for future drug research and clinical practice.
基金supported by Sichuan Province Science and Technology Support Program(NO.2020JDJQ0063,NO.2020YFS0566 and NO.2021JDKY0037,A-2021N-Z-5).
文摘Background:Radix Aconiti Lateralis Preparata(Fu-zi)is a traditional Chinese medicinal herb,which has been widely used in the clinic and has potent anti-inflammatory activities.we aimed to explore the mechanisms of extract containing alkaloids from different Fu-zi Processed Products(FPP)in treating inflammation,especially rheumatoid arthritis(RA).Methods:Firstly,using network pharmacology technology,the ingredients,and targets of Fu-zi were obtained by searching and screening,the targets involving RA were acquired,the intersection targets were constructed a"component-target-pathway"network.A comprehensive investigation was conducted on the anti-rheumatoid arthritis mechanisms of 5 FPPs in lipopolysaccharide(LPS)induced RAW264.7 cells,which serve as a model for RA.The production of NO and inflammatory cytokines were measured by ELISA kit.Quantitative Real-time PCR(qRT-PCR)was utilized to measure the mRNA levels.COX-2/PGE2 signaling pathway-associated proteins were determined by western blot.Results:According to a network pharmacological study,16 chemical components and 43 common targets were found in Fu-zi and 6 key targets including PTGS2 were closely related to the mechanism of Fu-zi in treating RA.The in vitro study revealed that the levels of NO,TNF-α,and IL-1βwere substantially decreased by the 5 FPPs.The 5 FPPs significantly suppressed the expression of proteins COX-2,iNOS,and NF-κB,with particularly notable effects observed for PFZ and XFZ.Conclusion:Altogether,these results demonstrated that the 5 PPS containing alkaloids have a good anti-RA-related inflammatory effect,and the mechanism may be related to COX-2/PGE2 signaling pathway,particularly,Fu-zi prepared utilizing a traditional Chinese technique.
基金supported in part by the National Natural Science Foundation of China(62171322,62006173)the 2021-2023 China-Serbia Inter-Governmental S&T Cooperation Project(No.6)+1 种基金support of the Sino-German Center of Intelligent Systems,Tongji University。
文摘In highly dynamic and heterogeneous vehicular communication networks,it is challenging to efficiently utilize network resources and ensure demanding performance requirements of safetyrelated applications.This paper investigates machinelearning-assisted transmission design in a typical multi-user vehicle-to-vehicle(V2V)communication scenario.The transmission process proceeds sequentially along the discrete time steps,where several source nodes intend to deliver multiple different types of messages to their respective destinations within the same spectrum.Due to rapid movement of vehicles,real-time acquirement of channel knowledge and central coordination of all transmission actions are in general hard to realize.We consider applying multi-agent deep reinforcement learning(MADRL)to handle this issue.By transforming the transmission design problem into a stochastic game,a multi-agent proximal policy optimization(MAPPO)algorithm under a centralized training and decentralized execution framework is proposed such that each source decides its own transmission message type,power level,and data rate,based on local observations of the environment and feedback,to maximize its energy efficiency.Via simulations we show that our method achieves better performance over conventional methods.
基金supported by the Ministry of Science and Technology of the People’s Republic of China(2021YFC0863400)Institute of Zoology,Chinese Academy of Sciences(E0517111,E122G611)。
文摘The coronavirus disease 2019(COVID-19)pandemic has greatly damaged human society,but the origins and early transmission patterns of the severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)pathogen remain unclear.Here,we reconstructed the transmission networks of SARS-CoV-2 during the first three and six months since its first report based on ancestor-offspring relationships using BANAL-52-referenced mutations.We explored the position(i.e.,root,middle,or tip)of early detected samples in the evolutionary tree of SARS-CoV-2.In total,6799 transmission chains and 1766 transmission networks were reconstructed,with chain lengths ranging from 1-9 nodes.The root node samples of the 1766 transmission networks were from 58 countries or regions and showed no common ancestor,indicating the occurrence of many independent or parallel transmissions of SARS-CoV-2 when first detected(i.e.,all samples were located at the tip position of the evolutionary tree).No root node sample was found in any sample(n=31,all from the Chinese mainland)collected in the first 15 days from 24 December 2019.Results using six-month data or RaTG13-referenced mutation data were similar.The reconstruction method was verified using a simulation approach.Our results suggest that SARS-CoV-2 may have already been spreading independently worldwide before the outbreak of COVID-19 in Wuhan,China.Thus,a comprehensive global survey of human and animal samples is essential to explore the origins of SARS-CoV-2 and its natural reservoirs and hosts.
基金2020 MajorNatural Science Research Project of Jiangsu Province Colleges and Universities:Research on Forensic Modeling and Analysis of the Internet of Things(20KJA520004)2020 Open Project of National and Local Joint Engineering Laboratory of Radio Frequency Integration andMicro-assembly Technology:Research on the Security Performance of Radio Frequency Energy Collection Cooperative Communication Network(KFJJ20200201)+1 种基金2021 Jiangsu Police Officer Academy Scientific Research Project:Research on D2D Cache Network Resource Optimization Based on Edge Computing Technology(2021SJYZK01)High-level Introduction of Talent Scientific Research Start-up Fund of Jiangsu Police Institute(JSPI19GKZL407).
文摘In this work,we consider the performance analysis of state dependent priority traffic and scheduling in device to device(D2D)heterogeneous networks.There are two priority transmission types of data in wireless communication,such as video or telephone,which always meet the requirements of high priority(HP)data transmission first.If there is a large amount of low priority(LP)data,there will be a large amount of LP data that cannot be sent.This situation will cause excessive delay of LP data and packet dropping probability.In order to solve this problem,the data transmission process of high priority queue and low priority queue is studied.Considering the priority jump strategy to the priority queuing model,the queuing process with two priority data is modeled as a two-dimensionalMarkov chain.A state dependent priority jump queuing strategy is proposed,which can improve the discarding performance of low priority data.The quasi birth and death process method(QBD)and fixed point iterationmethod are used to solve the causality,and the steady-state probability distribution is further obtained.Then,performance parameters such as average queue length,average throughput,average delay and packet dropping probability for both high and low priority data can be expressed.The simulation results verify the correctness of the theoretical derivation.Meanwhile,the proposed priority jump queuing strategy can significantly improve the drop performance of low-priority data.
文摘针对火电机组SO_(2)排放质量浓度的影响因素众多,难以准确预测的问题,提出一种改进向量加权平均(weighted mean of vectors,INFO)算法与双向长短期记忆(bi-directional long short term memory,Bi-LSTM)神经网络相结合的预测模型(改进INFO-Bi-LSTM模型)。采用Circle混沌映射和反向学习产生高质量初始化种群,引入自适应t分布提升INFO算法跳出局部最优解和全局搜索的能力。选取改进INFO-Bi-LSTM模型和多种预测模型对炉内外联合脱硫过程中4种典型工况下的SO_(2)排放质量浓度进行预测,将预测结果进行验证对比。结果表明:改进INFO算法的寻优能力得到提升,并且改进INFO-Bi-LSTM模型精度更高,更加适用于SO_(2)排放质量浓度的预测,可为变工况下的脱硫控制提供控制理论支撑。
基金Korea Institute of Energy Technology Evaluation and Planning,Grant/Award Number:20214000000320Samsung Research Funding&Incubation Center of Samsung Electronics,Grant/Award Number:SRFC-MA1901-06。
文摘Realizing a lithium sulfide(Li_(2)S)cathode with both high energy density and a long lifespan requires an innovative cathode design that maximizes electrochemical performance and resists electrode deterioration.Herein,a high-loading Li_(2)S-based cathode with micrometric Li_(2)S particles composed of two-dimensional graphene(Gr)and one-dimensional carbon nanotubes(CNTs)in a compact geometry is developed,and the role of CNTs in stable cycling of high-capacity Li–S batteries is emphasized.In a dimensionally combined carbon matrix,CNTs embedded within the Gr sheets create robust and sustainable electron diffusion pathways while suppressing the passivation of the active carbon surface.As a unique point,during the first charging process,the proposed cathode is fully activated through the direct conversion of Li_(2)S into S_(8) without inducing lithium polysulfide formation.The direct conversion of Li_(2)S into S_(8) in the composite cathode is ubiquitously investigated using the combined study of in situ Raman spectroscopy,in situ optical microscopy,and cryogenic transmission electron microscopy.The composite cathode demonstrates unprecedented electrochemical properties even with a high Li_(2)S loading of 10 mg cm^(–2);in particular,the practical and safe Li–S full cell coupled with a graphite anode shows ultra-long-term cycling stability over 800 cycles.
文摘目的比较非奈利酮与钠-葡萄糖共转运蛋白-2(sodium-glucose cotransporter-2,SGLT2)抑制剂对2型糖尿病和/或慢性肾脏病患者心血管事件的影响。方法检索PubMed、Cochrane Library、Web of Science和Embase数据库关于2型糖尿病和/或慢性肾脏病患者的随机对照试验,时间为建库至2023年7月3日。基于频率模型,使用STATA 17.0软件进行网状荟萃分析(network meta-analysis,NMA)。结果共纳入7项随机对照试验,包括33206例患者。涉及的治疗方式包括非奈利酮和SGLT2抑制剂,其中SGLT2抑制剂包含恩格列净、卡格列净、达格列净和索格列净(双重SGLT抑制剂)。在心血管复合事件方面,根据累计曲线下的概率面积(surface under the cumulative ranking area,SUCRA)排序,索格列净最有效。在心血管死亡方面,根据SUCRA排序,恩格列净最有效。在心力衰竭住院方面,根据SUCRA排序,卡格列净最有效。在全因死亡方面,根据SUCRA排序,达格列净最有效。非奈利酮和SGLT2抑制剂在不良事件、严重不良事件和急性肾损害的安全性方面比较,差异均无统计学意义(均P>0.05)。与采用非奈利酮治疗的患者相比,采用SGLT2抑制剂治疗的患者高钾血症发生率更低(RR=0.41,95%CI 0.32~0.52)。结论与非奈利酮相比,SGLT2抑制剂能更好地降低心血管事件的发生率,可作为2型糖尿病和/或慢性肾脏病患者的基础治疗,帮助预防或减少心血管事件。
基金supported by the Xiamen High-Level Health Talents Introduction and Training Project(Xiaweidang 2021-124)the National Natural Science Foundation of China(No.81774319).
文摘Background:The development and prognosis of breast cancer are intricately linked to psychological stress.In addition,depression is the most common psychological comorbidity among breast cancer survivors,and reportedly,Fang-Xia-Dihuang decoction(FXDH)can effectively manage depression in such patients.However,its pharmacological and molecular mechanisms remain obscure.Methods:Public databases were used for obtaining active components and related targets.Main active components were further verified by ultra-high-performance liquid chromatography-high-resolution mass spectrometry(UPLC-HRMS).Protein–protein interaction and enrichment analyses were taken to predict potential hub targets and related pathways.Molecule docking was used to understand the interactions between main compounds and hub targets.In addition,an animal model of breast cancer combined with depression was established to evaluate the intervention effect of FXDH and verify the pathways screened by network pharmacology.Results:174 active components of FXDH and 163 intersection targets of FXDH,breast cancer,and depression were identified.Quercetin,methyl ferulate,luteolin,ferulaldehyde,wogonin,and diincarvilone were identified as the principal active components of FXDH.Protein–protein interaction and KEGG enrichment analyses revealed that the phosphoinositide-3-kinase–protein kinase B(PI3K/AKT)and Janus kinase/signal transducer and activator of transcription(JAK2/STAT3)signaling pathways played a crucial role in mediating the efficacy of FXDH for inhibiting breast cancer progression induced by depression.In addition,in vivo experiments revealed that FXDH ameliorated depression-like behavior in mice and inhibited excessive tumor growth in mice with breast cancer and depression.FXDH treatment downregulated the expression of epinephrine,PI3K,AKT,STAT3,and JAK2 compared with the control treatment(p<0.05).Molecular docking verified the relationship between the six primary components of FXDH and the three most important targets,including phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha(PIK3CA),AKT,and STAT3.Conclusion:This study provides a scientific basis to support the clinical application of FXDH for improving depression-like behavior and inhibiting breast cancer progression promoted by chronic stress.The therapeutic effects FXDH may be closely related to the PI3K/AKT and JAK2/STAT3 pathways.This finding helps better understand the regulatory mechanisms underlying the efficacy of FXDH.