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Analysis of risk factors for MRI-invisible prostate cancer—the significance of AGGF1 immunohistochemical detection and PSAD 认领 引用
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作者 Jingcheng Lyu Ruiyu Yue +1 位作者 Ye Tian Boyu Yang 《The Canadian Journal of Urology》 SCIE 2026年第2期361-375,共15页
Objectives:Patients with a multi-parameter magnetic resonance imaging(mpMRI)prostate imaging report and data system(PI-RADS)score≤3,but with clinically significant prostate cancer(CSPCa)detected by biopsy,are termed ... Objectives:Patients with a multi-parameter magnetic resonance imaging(mpMRI)prostate imaging report and data system(PI-RADS)score≤3,but with clinically significant prostate cancer(CSPCa)detected by biopsy,are termed MRIInvisible prostate cancer(MRI(-)PCa).This study aims to explore risk factors for MRI(-)PCa and identify immunohistochemical indicators with predictive significance.Methods:A retrospective analysis was conducted on 376 patients with PI-RADS score≤3 who underwent 24-needle systematic prostate biopsy at Beijing Friendship Hospital,Capital Medical University(January 2015 to October 2025).Clinical data,imaging data,and Angiogenic factor with G and FHA domain 1(AGGF1)immunohistochemical results were collected.Patients were grouped into CSPCa(n=102)and non-CSPCa(n=274).t-tests,rank sum tests,andχ2tests were used for univariate analysis,followed by multivariate Logistic regression to determine independent risk factors.Receiver Operating Characteristic(ROC)curves were drawn.Subgroup analyses were conducted based on prostate-specific antigen(PSA)status and PI-RADS score using the same statistical methods.Moreover,we also used the Kruskal-Wallis test to compare the differences in AGGF1 expression percentages across different Gleason score groups according to ISUP in CSPCa patients.Results:Multivariate Logistic regression analysis showed that prostate-specific antigen density(PSAD)[OR:0.971,95%CI:0.952,0.991]and high expression of AGGF1[OR:1.065,95%CI:1.022,1.109]were independent risk factors for MRI(-)PCa(p0.25 ng/mL/cm3,not just PSA levels.After biopsy,AGGF1 immunohistochemical staining can be supplemented to help determine the risk and the malignancy of CSPCa. 展开更多
关键词 prostatic neoplasms magnetic resonance imaging prostate-specific antigen risk factors immunohistochemical analysis
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Global, regional, and national burden of chronic kidney disease in adults, 1990-2023, and its attributable risk factors: a systematic analysis for the Global Burden of Disease Study 2023 认领 引用 被引量：9
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作者 GBD 2023 Chronic Kidney Disease Collaborators 《四川生理科学杂志》 2026年第5期1084-1084,共1页
Background:Chronic kidney disease(CKD)is common and ranks among the leading causes of mortality and morbidity.This analysis aimed to present global CKD estimates using the Global Burden of Diseases,Injuries,and Risk F... Background:Chronic kidney disease(CKD)is common and ranks among the leading causes of mortality and morbidity.This analysis aimed to present global CKD estimates using the Global Burden of Diseases,Injuries,and Risk Factors Study(GBD)2023 to inform evidence-based policies for CKD identification and treatment.Methods:This analysis focused on adults aged 20 years and older over the period 1990 to 2023,from 204 countries and territories. 展开更多
关键词 global burden disease chronic kidney disease attributable risk factors systematic analysis kidney disease ckd
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基于Delphi Method和Factor Analysis构造粤港澳大学生信用评价体系 认领 引用
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作者 陈家辉 叶萌芳 +2 位作者 祁志峰 虞思静 尹佩贤 《价值工程》 2026年第16期40-43,共4页
随着互联网消费金融市场在我国逐年的扩张,大学生参与消费金融的人数和分期交易额均呈现爆发式增长。对于大学生的金融需求由于大学生群体信用评级体系不完善,造成群体从传统金融渠道获得融资的门槛高,流程复杂,合理金融需求无法被满足... 随着互联网消费金融市场在我国逐年的扩张,大学生参与消费金融的人数和分期交易额均呈现爆发式增长。对于大学生的金融需求由于大学生群体信用评级体系不完善,造成群体从传统金融渠道获得融资的门槛高,流程复杂,合理金融需求无法被满足,同时,借款申请信息没有共享,导致多头借贷行为始终难以杜绝,给非法校园金融产品留下“野蛮生长”空间。因此,本文基于Delphi Method和Factor Analysis,形成“专家预设-实证优化”的闭环验证机制筛选指标并构建粤港澳大学生信用体系,打造多维度信用评价网络,为大湾区大学生信用体系建设的差异化、特色化方向发展提供新的思路及借鉴。 展开更多
关键词 信用评价 信用指标 大学生信用 Delphi Method Factor Analysis
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Water Quality Monitoring of River Ecosystems and Analysis of Influencing Factors 认领 引用
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作者 LIU Jinchao 《外文科技期刊数据库（文摘版）自然科学》 2026年第2期087-091,共5页
With the rapid socioeconomic development and accelerated urbanization, river ecosystems are facing increasingly severe pressures, with water quality pollution becoming a prominent issue that seriously threatens region... With the rapid socioeconomic development and accelerated urbanization, river ecosystems are facing increasingly severe pressures, with water quality pollution becoming a prominent issue that seriously threatens regional ecological security and sustainable social development. This study focuses on water quality monitoring in river ecosystems, systematically reviewing current key monitoring parameters and conventional methods, while analyzing critical factors influencing water quality changes based on practical observations. Results indicate that natural factors such as runoff replenishment and climatic conditions exert certain impacts, but human activities—particularly industrial emissions, agricultural non-point source pollution, and urban wastewater discharge—are the primary drivers of water quality deterioration. Additionally, measures like adjusting land use patterns along riverbanks and implementing environmental protection policies positively contribute to enhancing water quality management effectiveness. This research provides theoretical insights into the mechanisms underlying water quality fluctuations in river ecosystems, offers decision-making support for authorities to develop more scientific and effective river conservation strategies, and holds significant practical implications for promoting regional ecological restoration and sustainable water resource utilization. 展开更多
关键词 River ecosystem Water quality monitoring Factor analysis Human activities Water pollution control
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Retrospective Analysis of Coronary Angiographic Characteristics and Disease Risk Factors in Patients with Coronary Heart Disease 认领 引用
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作者 SUN Liang 《外文科技期刊数据库（文摘版）医药卫生》 2026年第7期012-016,共5页
Objective: This study primarily investigated the coronary vascular imaging manifestations in individuals with confirmed coronary heart disease (CHD) and their relationship with common cardiovascular risk factors. Meth... Objective: This study primarily investigated the coronary vascular imaging manifestations in individuals with confirmed coronary heart disease (CHD) and their relationship with common cardiovascular risk factors. Methods: A retrospective design was employed, incorporating 80 CHD patients diagnosed via angiography at our hospital during the study period as the analysis subjects. The extent of coronary stenosis was quantitatively classified based on the number of affected vessels on imaging and using the Gensini scoring system. Clinical baseline data and risk factor exposures were systematically collected and compared across groups, with correlation analyses and regression models employed to identify key determinants of lesion severity. Results: Analysis revealed that a significant proportion of patients exhibited lesions involving three major coronary arteries. Compared to those with single-vessel lesions, patients with concurrent hypertension or diabetes demonstrated higher quantitative scores for coronary stenosis. The regression model identified age, elevated blood pressure, and diabetes as independent predictors of multi-vessel involvement. Conclusion: The extent of coronary artery lesions is clearly correlated with the number and type of established risk factors, with blood pressure and glycemic control exerting prominent influences on the development of multi-vessel disease. 展开更多
关键词 Coronary heart disease Coronary angiography Risk factors Scope of lesions Retrospective analysis
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Analysis of Reflection Crack Propagation and Its Influencing Factors in Asphalt Overlay on Old Cement Concrete Pavement Based on Finite Element Method 认领 引用
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作者 Li Xu Chunlin Li Yuqing Hou 《Journal of Architectural Research and Development》 2026年第2期8-18,共11页
Reflective cracking is one of the primary early-stage distresses in asphalt overlays on existing cement concrete pavements(white-to-black resurfacing structures).To delve into its mechanical evolution mechanism,this s... Reflective cracking is one of the primary early-stage distresses in asphalt overlays on existing cement concrete pavements(white-to-black resurfacing structures).To delve into its mechanical evolution mechanism,this study established a three-dimensional thermal-mechanical coupled numerical model using the finite element software ABAQUS and quantitatively analyzed the variations in the stress intensity factor(SIF)during crack propagation using the J-integral method.The study systematically investigated the influence of material modulus,structural layer thickness,and external loads(traffic and temperature)on the SIF.Sensitivity analysis results reveal that environmental temperature drops and vehicle overloading are the core drivers of reflective crack propagation,with significantly higher sensitivity than structural material properties.Increasing the thickness of the asphalt overlay generates a notable“bridging anti-cracking”effect,representing the most effective structural means to inhibit crack propagation.The research findings provide a theoretical basis for anti-cracking design and lifespan prediction in the rehabilitation of existing pavements. 展开更多
关键词 Asphalt overlay Reflective cracking Stress intensity factor Thermal-mechanical coupled model Sensitivity analysis
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Factor analysis and machine learning for predicting endpoint carbon content in converter steelmaking 认领 引用 被引量：3
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作者 Lihua Zhao Shuai Yang +3 位作者 Yongzhao Xu Zhongliang Wang Xin Liu Yanping Bao 《International Journal of Minerals,Metallurgy and Materials》 SCIE EI CAS CSCD 2025年第10期2469-2482,共14页
The endpoint carbon content in the converter is critical for the quality of steel products,and accurately predicting this parameter is an effective way to reduce alloy consumption and improve smelting efficiency.Howev... The endpoint carbon content in the converter is critical for the quality of steel products,and accurately predicting this parameter is an effective way to reduce alloy consumption and improve smelting efficiency.However,most scholars currently focus on modifying methods to enhance model accuracy,while overlooking the extent to which input parameters influence accuracy.To address this issue,in this study,a prediction model for the endpoint carbon content in the converter was developed using factor analysis(FA)and support vector machine(SVM)optimized by improved particle swarm optimization(IPSO).Analysis of the factors influencing the endpoint carbon content during the converter smelting process led to the identification of 21 input parameters.Subsequently,FA was used to reduce the dimensionality of the data and applied to the prediction model.The results demonstrate that the performance of the FA-IPSO-SVM model surpasses several existing methods,such as twin support vector regression and support vector machine.The model achieves hit rates of 89.59%,96.21%,and 98.74%within error ranges of±0.01%,±0.015%,and±0.02%,respectively.Finally,based on the prediction results obtained by sequentially removing input parameters,the parameters were classified into high influence(5%-7%),medium influence(2%-5%),and low influence(0-2%)categories according to their varying degrees of impact on prediction accuracy.This classi-fication provides a reference for selecting input parameters in future prediction models for endpoint carbon content. 展开更多
关键词 converter endpoint carbon content parameter classification factor analysis improved particle swarm optimization support vector machine
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Analysis of risk factors for bile leakage after laparoscopic exploration and primary suture of common bile duct 认领 引用 被引量：5
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作者 Qing-Song Yang Meng Zhang +5 位作者 Chang-Song Ma Da Teng Ao Li Ji-Dong Dong Xi-Fei Wang Fu-Bao Liu 《World Journal of Gastrointestinal Surgery》 SCIE 2025年第3期278-287,共10页
BACKGROUND Bile leakage is a common complication following laparoscopic common bile duct exploration(LCBDE)with primary duct closure(PDC).Identifying and analyzing the risk factors associated with bile leakage is cruc... BACKGROUND Bile leakage is a common complication following laparoscopic common bile duct exploration(LCBDE)with primary duct closure(PDC).Identifying and analyzing the risk factors associated with bile leakage is crucial for improving surgical outcomes.AIM To explore the value analysis of common risk factors for bile leakage after LCBDE and PDC,with a focus on strict adherence to indications.METHODS Clinical data of 106 cases undergoing LCBDE+PDC in the Hepatobiliary and Pancreatic Surgery Department(Division 1)of Chuzhou First People’s Hospital from April 2019 to March 2024 were collected.Retrospective and multiple factor regression analysis were conducted on common risk factors for bile leakage.The change in surgical time was analyzed using the cumulative summation(CUSUM)method,and the minimum number of cases required to complete the learning curve for PDC was obtained based on the proposed fitting curve by identifying the CUSUM maximum value.RESULTS Multifactor logistic regression analysis showed that fibrinous inflammation and direct bilirubin/indirect bilirubin were significant independent high-risk factors for postoperative bile leakage(P<0.05).The time to drain removal and length of hospital stay in cases without bile leakage were significantly shorter than in cases with bile leakage(P<0.05),with statistical significance.The CUSUM method indicated that a minimum of 51 cases were required for the surgeon to complete the learning curve(P=0.023).CONCLUSION With a good assessment of duodenal papilla sphincter function,unobstructed bile-pancreatic duct convergence,exact stone clearance,and sufficient surgical experience to complete the learning curve,PDC remains the preferred method for bile duct closure and is worthy of clinical promotion. 展开更多
关键词 Laparoscopic common bile duct exploration Primary duct closure Bile leakage Risk factor analysis Cumulative summation
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Changes in border-associated macrophages after stroke: Single-cell sequencing analysis 认领 引用 被引量：2
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作者 Ning Yu Yang Zhao +3 位作者 Peng Wang Fuqiang Zhang Cuili Wen Shilei Wang 《Neural Regeneration Research》 SCIE CAS CSCD 2026年第1期346-356,共11页
Border-associated macrophages are located at the interface between the brain and the periphery, including the perivascular spaces, choroid plexus, and meninges. Until recently, the functions of border-associated macro... Border-associated macrophages are located at the interface between the brain and the periphery, including the perivascular spaces, choroid plexus, and meninges. Until recently, the functions of border-associated macrophages have been poorly understood and largely overlooked. However, a recent study reported that border-associated macrophages participate in stroke-induced inflammation, although many details and the underlying mechanisms remain unclear. In this study, we performed a comprehensive single-cell analysis of mouse border-associated macrophages using sequencing data obtained from the Gene Expression Omnibus(GEO) database(GSE174574 and GSE225948). Differentially expressed genes were identified, and enrichment analysis was performed to identify the transcription profile of border-associated macrophages. CellChat analysis was conducted to determine the cell communication network of border-associated macrophages. Transcription factors were predicted using the ‘pySCENIC' tool. We found that, in response to hypoxia, borderassociated macrophages underwent dynamic transcriptional changes and participated in the regulation of inflammatory-related pathways. Notably, the tumor necrosis factor pathway was activated by border-associated macrophages following ischemic stroke. The pySCENIC analysis indicated that the activity of signal transducer and activator of transcription 3(Stat3) was obviously upregulated in stroke, suggesting that Stat3 inhibition may be a promising strategy for treating border-associated macrophages-induced neuroinflammation. Finally, we constructed an animal model to investigate the effects of border-associated macrophages depletion following a stroke. Treatment with liposomes containing clodronate significantly reduced infarct volume in the animals and improved neurological scores compared with untreated animals. Taken together, our results demonstrate comprehensive changes in border-associated macrophages following a stroke, providing a theoretical basis for targeting border-associated macrophages-induced neuroinflammation in stroke treatment. 展开更多
关键词 border-associated macrophages clodronate hypoxia ischemia-reperfusion ischemic stroke liposomes neuroinflammation single-cell sequencing analysis STAT3 tumor necrosis factor
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Big data-driven analysis of shale gas enrichment patterns:A case study of the Wufeng–Longmaxi Formation in the Sichuan Basin and its periphery 认领 引用 被引量：1
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作者 Zongquan Hu Jin Meng +10 位作者 Wei Du Yitian Xiao Chuanxiang Sun Guanping Wang Baojian Shen Tianrui Ye Dongjun Feng Zengqin Liu Longfei Lu Ruyue Wang Qianru Wang 《Energy Geoscience》 EI CAS CSCD 2026年第1期166-178,共13页
The Wufeng–Longmaxi Formation derives its name from the Upper Ordovician Wufeng Formation and the Lower Silurian Longmaxi Formation,found in sequence in the Sichuan Basin.This formation hosts rich shale gas reservoir... The Wufeng–Longmaxi Formation derives its name from the Upper Ordovician Wufeng Formation and the Lower Silurian Longmaxi Formation,found in sequence in the Sichuan Basin.This formation hosts rich shale gas reservoirs,and its shale gas enrichment patterns are examined in this study using data from 1197 shale samples collected from 14 wells.Five basic and three key parameters,eight in all,are assessed for each sample.The five basic parameters include burial depth and the contents of four mineral types—quartz,clay,carbonate,and other minerals;the three key parameters,representing shale gas enrichment,are total organic carbon(TOC)content,porosity,and gas content.The SHapley Additive exPlanations(SHAP)analysis originated in game theory is used here in an interpretable machine learning framework,to address issues of heterogeneous data structure,noisy relationships,and multi-objective optimization.An evaluation of the ranking,contribution values,and conditions of changes for these parameters offers new quantitative insights into shale gas enrichment patterns.A quantitative analysis of the relationship between data-sets identifies the primary factors controlling TOC,porosity,and gas content of shale gas reservoirs.The results show that TOC and porosity jointly influence gas content;mineral content has a significant impact on both,TOC and porosity;and the burial depth governs porosity which,in turn,affects the conditions under which shale gas is preserved.Input parameter thresholds are also determined and provide a basis for the establishment of quantitative criteria to evaluate shale gas enrichment.The predictive accuracy of the model used in this study is significantly improved by the step-wise addition of two input parameters,namely TOC and porosity,separately and together.Thus,the game theory method in big data-driven analysis uses a combination of TOC and porosity to evaluate the gas content with encouraging results—suggesting that these are the key parameters that indicate source rock and reservoir properties. 展开更多
关键词 Big data-driven analysis Primary controlling factor Shale gas enrichment pattern Wufeng–Longmaxi Formation Sichuan basin
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Analysis of risk factors for disease recurrence after endoscopic submucosal dissection of early esophageal cancer 认领 引用
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作者 Yan-Mei Yang Ting Dai +1 位作者 Ling-Yu Zou Cheng-Jin Zhao 《World Journal of Gastrointestinal Surgery》 SCIE 2025年第12期148-157,共10页
BACKGROUND Endoscopic submucosal dissection(ESD)is a minimally invasive,safe,and efficient treatment technique for patients diagnosed with early esophageal cancer.However,postoperative disease recurrence remains an im... BACKGROUND Endoscopic submucosal dissection(ESD)is a minimally invasive,safe,and efficient treatment technique for patients diagnosed with early esophageal cancer.However,postoperative disease recurrence remains an important clinical challenge because it negatively alters patient prognosis and quality of life.As such,identification of relevant risk factors for recurrence can help optimize postoperative management strategies.AIM To assess factors that contribute to the risk for disease recurrence after ESD for early esophageal cancer.METHODS Clinical data from 210 patients diagnosed with early stage esophageal cancer,who underwent ESD at the authors’center between March 2012 and March 2025,were retrospectively collected and analyzed.Patients were categorized into 2 groups according to postoperative disease recurrence:Recurrence(n=30),and without recurrence(n=180).Disease recurrence was defined as the appearance of new tumor lesions or pathologically confirmed tumor recurrence during the postoperative follow-up period.Risk factors associated with postoperative recurrence were identified using univariate and multivariate logistic regression analyses.RESULTS During the follow-up period,30 patients experienced tumor recurrence,corresponding to a recurrence rate of 14.19%.Multivariate analysis revealed that poor differentiation was a significant potential cause of esophageal cancer recurrence[odds ratio(OR)=1.782,95%confidence interval(CI):1.154-2.196;P<0.001].Tumors infiltrating the submucosa were more likely to recur than those penetrating the lamina propria or muscularis mucosa(OR=1.573,95%CI:1.073-2.481;P<0.001).Furthermore,inability to completely resect the tumor greatly increased the likelihood of recurrence(OR=2.189,95%CI:1.193-3.125;P=0.001).Tumor diameter≥2 cm was an independent risk factor for postoperative recurrence(OR=1.981,95%CI:1.482-2.862;P=0.005).CONCLUSION Recurrence of early esophageal cancer after ESD is largely influenced by the degree of differentiation,depth of lesion invasion,complete resection status of the tumor,and tumor diameter. 展开更多
关键词 Endoscopic submucosal dissection Early stage esophageal cancer Risk factors Relapse Multivariate analysis
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A Proportional Integral Controller-Enhanced Non-Negative Latent Factor Analysis Model 认领 引用
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作者 Ye Yuan Siyang Lu Xin Luo 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2025年第6期1246-1259,共14页
A non-negative latent factor(NLF)model is able to be built efficiently via a single latent factor-dependent,non-negative and multiplicative update(SLF-NMU)algorithm for performing precise representation to high-dimens... A non-negative latent factor(NLF)model is able to be built efficiently via a single latent factor-dependent,non-negative and multiplicative update(SLF-NMU)algorithm for performing precise representation to high-dimensional and incomplete(HDI)matrix from many kinds of big-data-related applications.However,an SLF-NMU algorithm updates a latent factor relying on the current update increment only without considering past learning information,making a resultant model suffer from slow convergence.To address this issue,this study proposes a proportional integral(PI)controller-enhanced NLF(PI-NLF)model with two-fold ideas:1)Designing an increment refinement(IR)mechanism,which formulates the current and past update increments as the proportional and integral terms of a PI controller,thereby assimilating the past update information into the learning scheme smoothly with high efficiency;2)Deriving an IR-based SLF-NMU(ISN)algorithm,which updates a latent factor following the principle of an IR mechanism,thus significantly accelerating an NLF model's convergence rate.The simulation results on eight HDI matrices collected by real applications validate that a PI-NLF model outstrips several leading-edge models in both computational efficiency and accuracy when estimating missing data within an HDI matrix.The proposed PI-NLF model can be effectively applied to applications involving HDI matrix like e-commerce system,social network,and cloud service system.The code is available at http://gffzz188fe103f8f1460as556knqxf00vx6pon.ffgz.tsg.suse.edu.cn/yuanyeswu/PINLF/blob/mainIPINLF-code.zip. 展开更多
关键词 High-dimensional and incomplete(HDI)data learning algorithm non-negative latent factor(NLF)analysis proportional integral(PI)controller
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Quantitative analyzing method for floor acceleration amplification factor based on instrumented buildings 认领 引用
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作者 Wang Tao Pan Rui +2 位作者 Xu Guoshan Meng Liyan Liu Jisheng 《Earthquake Engineering and Engineering Vibration》 SCIE EI CSCD 2026年第2期501-516,共16页
Precise analysis of the floor acceleration amplification(FAA)factor is crucial for accurately predicting the acceleration on acceleration-sensitive nonstructural components and estimating the seismic safety of nonstru... Precise analysis of the floor acceleration amplification(FAA)factor is crucial for accurately predicting the acceleration on acceleration-sensitive nonstructural components and estimating the seismic safety of nonstructural components.However,the existing literature on FAA did not analyze various influencing factors quantitatively.For solving this problem,one novel quantitative analyzing method of FAA considering various influencing factors in terms of structural type,structural height,site category,structural period,relative height and ground motion intensity based on instrumented buildings data from the Center for Engineering Strong Motion Data(CESMD)is proposed.The analysis results revealed that the site categories can significantly affect the FAA values of various types of structures,however,which has not been emphasized in previous studies.Correlation analysis reveals that the relative height is strongly correlated with the FAA,which is consistent with several seismic design codes.While,the parameters in terms of the site category,structural height and structural type also significantly correlated with the FAA.The results indicate that these three factors should be incorporated into the seismic design code.This study offers valuable insights and recommendations for the design of acceleration-sensitive nonstructural components in terms of FAA. 展开更多
关键词 floor acceleration amplification factor instrumented buildings acceleration-sensitive nonstructural components seismic performance site categories correlation analysis
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Dynamic patterns and driving factors of productive cropland in Ukraine before and after Russia-Ukraine conflict 认领 引用
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作者 Yiliang Li Kaixuan Yao +5 位作者 Qingxiang Meng Yujie Wang Rui Xiao Yuhang Liu Sensen Wu Yansheng Li 《Geography and Sustainability》 CSCD 2026年第1期106-118,共13页
Ukraine,as one of the world’s largest agricultural producers and exporters,plays a critical role in global food security.It is essential to understand the spatiotemporal dynamics and drivers of productive cropland in... Ukraine,as one of the world’s largest agricultural producers and exporters,plays a critical role in global food security.It is essential to understand the spatiotemporal dynamics and drivers of productive cropland in Ukraine,particularly in the context of the 2022 Russia-Ukraine conflict.We provide the first comprehensive assessment of both conflict-and non-conflict-related factors that influenced the distribution and productivity of Ukraine’s cropland from 2013 to 2023.In addition,we propose a novel method using machine learning models to isolate the impact of conflict on cropland.Our findings reveal that,prior to the conflict,the spatial pattern of Ukraine’s mean cultivation rate was primarily shaped by natural factors—such as climate,soil properties,and elevation—whereas socio-economic factors(e.g.,GDP and population size)exerted a weaker influence.Interannual dynamics in productive cropland area were largely driven by climate variability.The onset of conflict in 2022 dramatically altered this landscape,with nearly half of the cropland grid cells experiencing a conflict-induced reduction.Notably,almost half of the interannual reduction in productive cropland in 2022 was attributed to climate change.Remarkably,in 2023,the return of displaced populations and favorable climatic conditions in many oblasts contributed to a positive trend in cropland reclamation.Despite this,the total area of productive cropland in 2023 remained below expected levels,due to ongoing conflict and localized droughts.Finally,we highlight the urgent need to adopt a two-pronged approach that addresses both the immediate impacts of conflict and the ongoing threats posed by climate change to ensure the resilience and sustainability of agricultural systems in post-conflict areas. 展开更多
关键词 Ukraine’s cropland dynamics Driving factors analysis Time-series remote sensing Russia-Ukraine conflict
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Big data analysis of waterflood performance in mature conventional oilfields in Eastern China 认领 引用
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作者 Tianrui Ye Zhiqiang Chen Cheng Dai 《Energy Geoscience》 EI CAS CSCD 2026年第2期17-28,共12页
Most conventional oilfields in Eastern China with waterflood operations have reached ultra-high water cut in recent decade.The high water injection demand and produced water treatment cost pose significant environment... Most conventional oilfields in Eastern China with waterflood operations have reached ultra-high water cut in recent decade.The high water injection demand and produced water treatment cost pose significant environmental threats.Therefore,optimizing waterflood performance is key to improving production efficiency.This study performs data analysis on waterflood operations of all the oilfields operated by Sinopec across Eastern China.The production mechanisms and most effective operations for different reservoir types at diverse production stages are identified using data-driven methods.Random Forest models(RFMs)are constructed and integrated with Shapley Additive exPlanations(SHAP)analysis to quantify the weights and patterns of key geological and engineering features.A comparison of the estimated ultimate recovery factors for different blocks shows that geological factors play dominant roles in medium-to-high permeability reservoirs while development parameters are more critical for low-permeability reservoirs.The analysis of temporal data regarding field development and production history is conducted to select oil production-increasing operations in blocks.The results show that the most influential field operations vary for the diverse production stages,and well patterns should be carefully designed to improve production efficiency and reduce ineffective water circulation. 展开更多
关键词 Random Forest model(RFM) Big data analysis Waterflood performance Key factor analysis
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Epidemiological Characteristics,Risk Factors,and Countermeasures of Imported Malaria—China,2017–2024 认领 引用
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作者 Zhigui Xia Tao Zhang +6 位作者 Weidong Li Deye Meng Chi Zhang Boyu Yi Hejun Zhou Yuqi Dai Shizhu Li 《China CDC weekly》 SCIE CSCD 2026年第25期765-771,I0001,共7页
Introduction:This study aimed to analyze the epidemiological characteristics of imported malaria in China,identify transmission risks from the global malaria burden and China’s international population exchanges,and ... Introduction:This study aimed to analyze the epidemiological characteristics of imported malaria in China,identify transmission risks from the global malaria burden and China’s international population exchanges,and propose a two-stage prevention and control strategy for overseas and post-entry periods of outbound personnel.Methods:A descriptive epidemiological analysis was performed on the National Infectious Disease Surveillance Information System,including the number of patients with imported malaria,Plasmodium species distribution,spatiotemporal patterns,demographic characteristics,and countries of infection origin.Results:Between 2017 and 2024,16,571 patients with imported malaria,including 75 deaths,were reported,with a U-shaped temporal trend.The annual number of patients with imported malaria remained stable at 2,600–2,800 from 2017 to 2019,dropped to 798 in 2021,and rebounded to 3,155 in 2024.Plasmodium falciparum(10,593 patients)and Plasmodium vivax(3,288 patients)were the dominant species.P.falciparum was imported from Africa,whereas P.vivax was from Myanmar.Patients with imported malaria were distributed across China,with Yunnan,Guangdong,and Guangxi emerging as the top three provincial-level adminsitrative divisions(PLADs).The high-risk population was male overseas laborers aged 30–59.Severe illness and fatality rates among individuals with imported malaria remained low with no upward trend.Conclusion:The global malaria epidemic and China’s international exchanges have increased the pressure on malaria importation.Strengthening multisectoral collaboration in health services for outbound personnel and improving targeted surveillance and treatment capacity in key post-entry areas are crucial to prevent severe illness,deaths,and secondary transmission and to consolidate China's malaria elimination achievements. 展开更多
关键词 analyze epidemiological characteristics Epidemiological Characteristics imported malariaplasm Risk Factors imported malaria infectious disease surveillance information descriptive epidemiological analysis global malaria
Spatiotemporal Graph Neural Network-Incorporated Latent Factorization of Tensors for Dynamic QoS Estimation 认领 引用
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作者 Xin Luo Fanghui Bi Tiantian He 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2026年第7期1642-1656,共15页
Quality of service(Qo S)data that characterize historical user-service invocations that vary over time are vital to discovering patterns of cloud services and understanding user behaviors.Though effective,prevalent ap... Quality of service(Qo S)data that characterize historical user-service invocations that vary over time are vital to discovering patterns of cloud services and understanding user behaviors.Though effective,prevalent approaches never consider higher-order spatiotemporal connectivity within Qo S data,thus suffering from inferior performance.To address this critical issue,this paper presents spatiotemporal graph convolutional network(GCN)that is equipped with the functionality of latent factorization of tensors(SGLFT).It is achieved by introducing three key innovations:1)Proposing a tensor graph convolution based on the generalized tensor product technique for uniformly modeling the temporal and spatial patterns within dynamic user-service graphs;2)Incorporating the built layer-wise graph convolution into tensor factorization for efficiently capturing the implied spatiotemporal high-order connectivity;and 3)Developing a nodelevel attention pooling mechanism to perceive feature differences among neighbors and across time slots.Theoretical derivations are conducted to demonstrate that the expressivity of the graph neural network proposed in this paper is evidently higher than that of vanilla GCNs.Empirical studies on eight large-scale testing cases arising from two real-world dynamic Qo S datasets show that SGLFT substantially outperforms state-of-the-art Qo S estimators regarding estimation accuracy for missing dynamic QoS data. 展开更多
关键词 Cloud service data science dynamic quality-of-service estimation graph convolutional networks(GCNs) latent factorization of tensors latent feature analysis non-euclidean data representation learning tensor product
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Expression Analysis and Functional Validation of Lily LoWRKY22 认领 引用
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作者 Ling He Shun Tao +4 位作者 Qian Wang Yu-Pei Yin Xin-Yu He Shuo Shi Chun-Yan Wang 《Phyton-International Journal of Experimental Botany》 SCIE 2026年第6期366-380,共15页
As essential regulatory proteins,WRKY transcription factors participate in the regulation of plant growth,development and stress resistance;however,the functions of LoWRKY22 in the‘Siberia’cultivar of Lilium remain ... As essential regulatory proteins,WRKY transcription factors participate in the regulation of plant growth,development and stress resistance;however,the functions of LoWRKY22 in the‘Siberia’cultivar of Lilium remain uncharacterized.In this study,LoWRKY22 was cloned and subjected to comprehensive functional analyses.Phylogenetic analysis revealed that LoWRKY22 belongs to the WRKY-IIe type subgroup,featuring a conserved WRKY domain and a C2H2-type zinc finger motif,indicating evolutionary conservation with WRKY homologs from Arabidopsis thaliana.Subcellular localization and transactivation assays confirmed its nuclear localization and transcriptional activation activity,supporting its role as a transcriptional regulator.Structural characterization of the LoWRKY22 promoter identified multiple cis-elements responsive to light,low temperature,and gibberellin,suggesting its involvement in environmental and hormonal signaling pathways.Tissue expression analysis demonstrated predominant expression of LoWRKY22 in leaves,consistent with its proposed roles in photosynthesisand senescence-related processes.The heterologous overexpression of LoWRKY22 in Arabidopsis thaliana induced early flowering,reduced plant height,and accelerated silique maturation relative to those in wild-type plants.Quantitative real-time polymerase chain reaction(PCR)revealed that LoWRKY22 overexpression significantly upregulated senescence-associated genes(AtWRKY53,AtSAG12,and AtSAG13)and flowering-promoting genes(AtFT and AtAP1),while downregulating the floral repressor AtFLC.These findings indicate that LoWRKY22 functions as a positive regulator of flowering and senescence,potentially coordinating the transition from vegetative to reproductive growth via the modulation of key regulatory networks.Collectively,this research firstly identified and explored the functions of LoWRKY22 in the‘Siberia’cultivar of Lilium,elucidating its regulatory role in growth-phase transitions and establishing a molecular foundation for its potential utilization as a candidate gene in genetic breeding programs aimed at optimizing growth,flowering time,and developmental traits in lilies. 展开更多
关键词 Lilium‘Siberia’ LoWRKY22 WRKY transcription factor flowering senescence Arabidopsis heterologous transformation phylogenetic analysis
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Genome-wide identification and expression analysis of WRKY transcription factor family members in seashore paspalum under salt stress 认领 引用 被引量：1
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作者 Xuanyang Wu Zicheng Tian +7 位作者 Ting Wang Xiaochen Hu Qi Sun Yuzhu Wang Wenjie Lu Zhanfeng Ren Junxiang Qi Xueli Wu 《Grass Research》 2025年第1期168-181,共14页
Although WRKY transcription factors(TFs)are established key regulators of plant stress responses,their contributions to highly salt-tolerant halophytesremain poorly understood.This study presents the first comprehensi... Although WRKY transcription factors(TFs)are established key regulators of plant stress responses,their contributions to highly salt-tolerant halophytesremain poorly understood.This study presents the first comprehensive genome-wide characterization of the WRKY gene family in the exceptionally salttoleranthalophyte,seashore paspalum(Paspalum vaginatum).Using HMM profile searches and conserved domain analysis,126 nonredundant PvWRKYsequences were identified.These were subsequently classified phylogenetically by comparison to Arabidopsis orthologs into established groups:Group I(n=22),Group Ⅱ(n=58,subgroups Ⅱa-Ⅱe),and Group ⅡI(n=46).Protein characterization revealed unstable hydrophilic PvWRKYs predominantly localizedto the nucleus(84.92%),consistent with their transcriptional regulatory roles.Promoter cis-element analysis identified enrichment in stress-responsivemotifs,with ABA-responsive elements(ABRE;present in 116 genes)and MeJA-responsive elements(detected in 115 genes),highlighting hormonalintegration in salt adaptation.Intraspecific collinearity and tandem duplication events on chromosomes 2,3,5,and 9 suggested evolutionary expansion viagene duplication.Transcriptome and quantitative reverse transcription(qRT-PCR)analyses revealed spatiotemporal expression dynamics under salt stress:PvWRKY105/117/126 exhibited root-specific upregulation during prolonged stress,whereas PvWRKY84/58/90 were leaf-predominant responders.Functionalannotation(GO)linked PvWRKYs to root development(GO:0048364),oxidative stress response,and MAPK signaling,with protein-protein interaction(PPI)networks identifying PvWRKY52 as a central hub interacting with key stress regulators(MKS1,MPK3/MPK4).Additionally,PvWRKY123 showed ABA signalingsynergism via ABI4/ABI5 interactions,while PvWRKY86 was associated with SUMOylation-mediated regulation through BZIP8 and SUMO1.This genomewideexploration of the WRKY family in seashore paspalum emphasizes its regulatory potential in salt adaptation and offers a foundation for futurefunctional analyses. 展开更多
关键词 paspalum paspalum vaginatum using WRKY transcription factor family hmm profile searches Seashore paspalum salt stress genome wide identification expression analysis conserved domain analysis
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Correlation of anxiety and depression with ankle function in chronic ankle instability patients and analysis of risk factors 认领 引用 被引量：1
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作者 Zu-Po Yu 《World Journal of Psychiatry》 SCIE 2025年第7期83-90,共8页
BACKGROUND Psychological comorbidities,such as anxiety and depression,in patients with chronic ankle instability(CAI)may impede ankle function improvement,although the precise nature of this association warrants furth... BACKGROUND Psychological comorbidities,such as anxiety and depression,in patients with chronic ankle instability(CAI)may impede ankle function improvement,although the precise nature of this association warrants further investigation.AIM To analyze the correlation of anxiety and depression with ankle function in patients with CAI and discussing the risk factors.METHODS This study included 116 patients with CAI,who were admitted to our hospital from July 2022 to July 2024.Anxiety and depression states of patients were assessed with the self-rating anxiety scale(SAS)and self-rating depression scale(SDS),respectively,and their ankle joint function was assessed with the anklehindfoot function score of the American Orthopedic Foot and Ankle Society.Further,the ankle function of patients with CAI with different anxiety and depression states was discussed.Furthermore,the Pearson correlation coefficient was used to analyze the correlation of anxiety and depression with ankle joint function in such patients.Univariate and multivariate analyses were conducted to investigate the factors affecting ankle joint function in patients with CAI.RESULTS Among the 116 patients with CAI,97,13,5,and 1 cases demonstrated none,mild,moderate,and severe anxiety,whereas 95,15,6,and 0 cases showed none,mild,moderate,and severe depression,respectively.The average ankle joint function score was 74.82±6.93 points.The ankle joint function in patients with CAI presented a significant downward tendency as the degree of anxiety and depression increased.Correlation analysis revealed that both the SAS and SDS scores of patients with CAI were significantly negatively correlated with the ankle joint function score.Univariate and multivariate analyses indicated that the risk factors affecting patients’ankle joint function included early functional rehabilitation,visual analog scale,and SDS.CONCLUSION A substantial number of patients with CAI suffer from anxiety and depression,and these negative emotions,to a certain extent,harm the smooth rehabilitation of ankle joint function. 展开更多
关键词 Chronic ankle instability Anxiety and depression Ankle function Correlation analysis Risk factors
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