Urban spatial morphology(USM)optimization is critical to balancing biodiversity conservation and sustainable urbanization.However,previous studies predominantly focused on the socio-economic efficiency and static ecol...Urban spatial morphology(USM)optimization is critical to balancing biodiversity conservation and sustainable urbanization.However,previous studies predominantly focused on the socio-economic efficiency and static ecological metrics and rarely addressed the dynamic USM optimization across spatial scales.Here,we developed a multi-level ecological network(MEN)framework to resolve the tension between urban expansion and ecological integrity.By integrating the cost-weighted distance analysis with a hierarchical network transmission mechanism,we established a cross-scale spatial optimization system,which coordinated the regional ecological corridors and local habitat patches.Comparative experiments with conventional single-scale approaches and scenario simulations using the PLUS model show that the MEN framework had superior performance in three dimensions:(1)spatial governance:the primary-level network(peri-urban natural reserves)effectively contained urban sprawl,and the secondary-level network(intra-urban green corridors)mitigated habitat fragmentation and improved the built-environment;(2)scenario robustness:the model maintained an optimal compactness-loose balance in multiple development pathways;(3)landscape metrics:patch fragmentation decreased by 18.25%,and the internal landscape richness improved by 10.66%compared to the scenario without USM optimization.The findings provide new insight to establish a hierarchical ecological optimization framework as a nature-based spatial protocol to reconcile metropolitan growth with landscape sustainability.展开更多
The influence of different solution and aging conditions on the microstructure,impact toughness,and crack initiation and propagation mechanisms of the novel α+β titanium alloy Ti6422 was systematically investigated....The influence of different solution and aging conditions on the microstructure,impact toughness,and crack initiation and propagation mechanisms of the novel α+β titanium alloy Ti6422 was systematically investigated.By adjusting the furnace cooling time after solution treatment and the aging temperature,Ti6422 alloy samples were developed with a multi-level lamellar microstructure,in-cluding microscaleαcolonies and α_(p) lamellae,as well as nanoscale α_(s) phases.Extending the furnace cooling time after solution treatment at 920℃ for 1 h from 240 to 540 min,followed by aging at 600℃ for 6 h,increased the α_(p) lamella content,reduced the α_(s) phase content,expanded theαcolonies and α_(p) lamellae size,and improved the impact toughness from 22.7 to 53.8 J/cm^(2).Additionally,under the same solution treatment,raising the aging temperature from 500 to 700℃ resulted in a decrease in the α_(s) phase content and a growth in the thickness of the α_(p) lamella and α_(s) phase.The impact toughness increased significantly with these changes.Samples with high α_(p) lamellae content or large α_(s) phase size exhibited high crack initiation and propagation energies.Impact deformation caused severe kinking of the α_(p) lamellae in crack initiation and propagation areas,leading to a uniform and high-density kernel average misorientation(KAM)distribu-tion,enhancing plastic deformation coordination and uniformity.Moreover,the multidirectional arrangement of coarserαcolonies and α_(p) lamellae continuously deflect the crack propagation direction,inhibiting crack propagation.展开更多
Traditional psychiatric diagnosis relies on subjective symptom assessment,lacking objective biomarkers that hinder early detection and personalized treatment.Plasma proteins and polygenic risk score(PRS),as potential ...Traditional psychiatric diagnosis relies on subjective symptom assessment,lacking objective biomarkers that hinder early detection and personalized treatment.Plasma proteins and polygenic risk score(PRS),as potential predictive tools,hold promise for advancing early diagnosis of mental disorders.This study aims to evaluate the predictive potential of proteomic features and PRS in multiple mental illnesses(depression,schizophrenia,and post-traumatic stress disorder(PTSD)).Using participant data from the UK Biobank-Pharma Proteomics Project,we screen protein associations with mental disorders through least absolute shrinkage and selection operator(LASSO)analysis and construct a Cox regression risk prediction model by integrating the PRS.Additionally,we evaluate predictive performance using 6 machine learning methods and Kaplan-Meier survival curves.Our findings reveal distinct predictive patterns across dis-orders.For depression,integrating plasma proteins with PRS significantly improves prediction beyond the clinical model(C-index=0.6322).For schizophrenia,adding plasma proteins enhances predictive performance,whereas PRS provides no significant improvement.For PTSD,neither plasma proteins nor PRS add substantial predictive value beyond clinical variables.Risk stratification analysis demonstrat that all three mental disorders models can clearly distinguish high-risk from low-risk groups(depression:HR=2.34,P<0.001;schizophrenia:HR=5.47,P<0.001;PTSD:HR=3.02,P<0.001).Al-though it shows good performance in short-term prediction,its long-term prediction ability has decreased,and it needs to be further optimized in the future.This study underscores the differential utility of biomarkers across mental disorders and provides a rationale for disorder-specific predictive modeling in precision psychiatry.展开更多
Objective: To analyze the effect of pain nursing combined with exercise and posture intervention on improving Visual Analogue Scale (VAS) scores in patients after kidney stone surgery. Methods: A sample of 80 patients...Objective: To analyze the effect of pain nursing combined with exercise and posture intervention on improving Visual Analogue Scale (VAS) scores in patients after kidney stone surgery. Methods: A sample of 80 patients who underwent kidney stone surgery from October 2024 to October 2025 was randomly divided into groups using a random number table. Group A received pain nursing combined with exercise and posture intervention, while Group B received conventional nursing. Postoperative recovery time, VAS scores, and postoperative complications were compared between the two groups. Results: The postoperative recovery time in Group A was shorter than that in Group B, with p < 0.05. The VAS scores at 12 hours, 24 hours, and 72 hours postoperatively in Group A were all lower than those in Group B, with p < 0.05. The postoperative complication rate in Group A was lower than that in Group B, with p < 0.05. Conclusion: Pain nursing combined with exercise and posture intervention in postoperative nursing for kidney stone patients can shorten postoperative recovery time and alleviate pain scores.展开更多
As a key node of modern transportation network,the informationization management of road tunnels is crucial to ensure the operation safety and traffic efficiency.However,the existing tunnel vehicle modeling methods ge...As a key node of modern transportation network,the informationization management of road tunnels is crucial to ensure the operation safety and traffic efficiency.However,the existing tunnel vehicle modeling methods generally have problems such as insufficient 3D scene description capability and low dynamic update efficiency,which are difficult to meet the demand of real-time accurate management.For this reason,this paper proposes a vehicle twin modeling method for road tunnels.This approach starts from the actual management needs,and supports multi-level dynamic modeling from vehicle type,size to color by constructing a vehicle model library that can be flexibly invoked;at the same time,semantic constraint rules with geometric layout,behavioral attributes,and spatial relationships are designed to ensure that the virtual model matches with the real model with a high degree of similarity;ultimately,the prototype system is constructed and the case region is selected for the case study,and the dynamic vehicle status in the tunnel is realized by integrating real-time monitoring data with semantic constraints for precise virtual-real mapping.Finally,the prototype system is constructed and case experiments are conducted in selected case areas,which are combined with real-time monitoring data to realize dynamic updating and three-dimensional visualization of vehicle states in tunnels.The experiments show that the proposed method can run smoothly with an average rendering efficiency of 17.70 ms while guaranteeing the modeling accuracy(composite similarity of 0.867),which significantly improves the real-time and intuitive tunnel management.The research results provide reliable technical support for intelligent operation and emergency response of road tunnels,and offer new ideas for digital twin modeling of complex scenes.展开更多
The umbilical,a key component in offshore energy extraction,plays a vital role in ensuring the stable operation of the entire production system.The extensive variety of cross-sectional components creates highly comple...The umbilical,a key component in offshore energy extraction,plays a vital role in ensuring the stable operation of the entire production system.The extensive variety of cross-sectional components creates highly complex layout combinations.Furthermore,due to constraints in component quantity and geometry within the cross-sectional layout,filler bodies must be incorporated to maintain cross-section performance.Conventional design approaches based on manual experience suffer from inefficiency,high variability,and difficulties in quantification.This paper presents a multi-level automatic filling optimization design method for umbilical cross-sectional layouts to address these limitations.Initially,the research establishes a multi-objective optimization model that considers compactness,balance,and wear resistance of the cross-section,employing an enhanced genetic algorithm to achieve a near-optimal layout.Subsequently,the study implements an image processing-based vacancy detection technique to accurately identify cross-sectional gaps.To manage the variability and diversity of these vacant regions,the research introduces a multi-level filling method that strategically selects and places filler bodies of varying dimensions,overcoming the constraints of uniform-size fillers.Additionally,the method incorporates a hierarchical strategy that subdivides the complex cross-section into multiple layers,enabling layer-by-layer optimization and filling.This approach reduces manufac-turing equipment requirements while ensuring practical production process feasibility.The methodology is validated through a specific umbilical case study.The results demonstrate improvements in compactness,balance,and wear resistance compared with the initial cross-section,offering novel insights and valuable references for filler design in umbilical cross-sections.展开更多
BACKGROUND Emphysematous pyelonephritis(EPN)is a life-threatening necrotizing renal parenchyma infection characterized by gas formation due to severe bacterial infection,predominantly affecting diabetic and immunocomp...BACKGROUND Emphysematous pyelonephritis(EPN)is a life-threatening necrotizing renal parenchyma infection characterized by gas formation due to severe bacterial infection,predominantly affecting diabetic and immunocompromised patients.It carries high morbidity and mortality,requiring early diagnosis and timely intervention.Various prognostic scoring systems help in triaging critically ill patients.The National Early Warning Score 2(NEWS 2)scoring system is a widely used physiological assessment tool that evaluates clinical deterioration based on vital parameters,but its standard form lacks specificity for risk stratification in EPN,necessitating modifications to improve treatment decisionmaking and prognostic accuracy in this critical condition.AIM To highlight the need to modify the NEWS 2 score to enable more intense monitoring and better treatment outcomes.METHODS This prospective study was done on all EPN patients admitted to our hospital over the past 12 years.A weighted average risk-stratification index was calculated for each of the three groups,mortality risk was calculated for each of the NEWS 2 scores,and the need for intervention for each of the three groups was calculated.The NEWS 2 score was subsequently modified with 0-6,7-14 and 15-20 scores included in groups 1,2 and 3,respectively.RESULTS A total of 171 patients with EPN were included in the study,with a predominant association with diabetes(90.6%)and a female-to-male ratio of 1.5:1.The combined prognostic scoring of the three groups was 10.7,13.0,and 21.9,respectively(P<0.01).All patients managed conservatively belonged to group 1(P<0.01).Eight patients underwent early nephrectomy,with six from group 3(P<0.01).Overall mortality was 8(4.7%),with seven from group 3(87.5%).The cutoff NEWS 2 score for mortality was identified to be 15,with a sensitivity of 87.5%,specificity of 96.9%,and an overall accuracy rate of 96.5%.The area under the curve to predict mortality based on the NEWS 2 score was 0.98,with a confidence interval of(0.97,1.0)and P<0.001.CONCLUSION Modified NEWS 2(mNEWS 2)score dramatically aids in the appropriate assessment of treatment-related outcomes.MNEWS 2 scores should become the practice standard to reduce the morbidity and mortality associated with this dreaded illness.展开更多
BACKGROUND Post-hepatectomy liver failure(PHLF)after liver resection is one of the main complications causing postoperative death in patients with hepatocellular carcinoma(HCC).It is crucial to help clinicians identif...BACKGROUND Post-hepatectomy liver failure(PHLF)after liver resection is one of the main complications causing postoperative death in patients with hepatocellular carcinoma(HCC).It is crucial to help clinicians identify potential high-risk PHLF patients as early as possible through preoperative evaluation.AIM To identify risk factors for PHLF and develop a prediction model.METHODS This study included 248 patients with HCC at The Second Affiliated Hospital of Air Force Medical University between January 2014 and December 2023;these patients were divided into a training group(n=164)and a validation group(n=84)via random sampling.The independent variables for the occurrence of PHLF were identified by univariate and multivariate analyses and visualized as nomograms.Ultimately,comparisons were made with traditional models via receiver operating characteristic(ROC)curves,calibration curves,and decision curve analysis(DCA).RESULTS In this study,portal vein width[odds ratio(OR)=1.603,95%CI:1.288-1.994,P≤0.001],the preoperative neutrophil-to-lymphocyte ratio(NLR)(OR=1.495,95%CI:1.126-1.984,P=0.005),and the albumin-bilirubin(ALBI)score(OR=8.868,95%CI:2.144-36.678,P=0.003)were independent risk factors for PHLF.A nomogram prediction model was developed using these factors.ROC and DCA analyses revealed that the predictive efficacy and clinical value of this model were better than those of traditional models.CONCLUSION A new Nomogram model for predicting PHLF in HCC patients was successfully established based on portal vein width,the NLR,and the ALBI score,which outperforms the traditional model.展开更多
OBJECTIVE:To investigate the clinical efficacy of using a Jiedu formula(解毒方) as an adjunctive therapy in patients with hepatocellular carcinoma(HCC) after hepatectomy.METHODS:In total,354 patients were included in ...OBJECTIVE:To investigate the clinical efficacy of using a Jiedu formula(解毒方) as an adjunctive therapy in patients with hepatocellular carcinoma(HCC) after hepatectomy.METHODS:In total,354 patients were included in this study.All patients were categorized into the traditional herbal medicine(THM) group(n = 115) or the non-THM treatment(nTHM) group(n = 239),with the Jiedu formula administered twice a day to the patients in the THM group.The primary outcome was recurrence-free survival(RFS).Univariate and multivariate Cox regression analyses were performed to identify the prognostic factors associated with RFS.Then,the high risk of recurrence among patients was identified,and propensity score matching(PSM) and RFS analysis were performed to analyze the prognostic factors for the outcomes of patients at a high risk of recurrence in different groups.RESULTS:The one,two,three,and five-year RFS rates of the THM and nTHM groups were 76.4% vs 66.1%,65.5% vs 48.8%,57.9% vs 39.9%,and 43.9% vs 29.2%,respectively.The results of the Multivariate Cox analysis showed that giant tumors [hazard ratio(HR),1.54,P = 0.04],poor degree of differentiation,microsatellite,or microvascular invasion(HR,1.29,P = 0.09) increased the risk of recurrence.In the population with a high risk of recurrence,after PSM,the one,two,three,and five-year survival rates were 70.6% vs 68.0%,63.0% vs 43.1%,59.6% vs 33.3%,and 41.9% vs 26.4%,respectively.CONCLUSION:In this study,THM was found to be an effective agent for adjuvant therapy for HCC to prevent early recurrence of HCC after hepatic resection.展开更多
Objective We aimed to investigate the patterns of fasting blood glucose(FBG)trajectories and analyze the relationship between various occupational hazard factors and FBG trajectories in male steelworkers.Methods The s...Objective We aimed to investigate the patterns of fasting blood glucose(FBG)trajectories and analyze the relationship between various occupational hazard factors and FBG trajectories in male steelworkers.Methods The study cohort included 3,728 workers who met the selection criteria for the Tanggang Occupational Cohort(TGOC)between 2017 and 2022.A group-based trajectory model was used to identify the FBG trajectories.Environmental risk scores(ERS)were constructed using regression coefficients from the occupational hazard model as weights.Univariate and multivariate logistic regression analyses were performed to explore the effects of occupational hazard factors using the ERS on FBG trajectories.Results FBG trajectories were categorized into three groups.An association was observed between high temperature,noise exposure,and FBG trajectory(P<0.05).Using the first quartile group of ERS1 as a reference,the fourth quartile group of ERS1 had an increased risk of medium and high FBG by 1.90and 2.21 times,respectively(odds ratio[OR]=1.90,95%confidence interval[CI]:1.17–3.10;OR=2.21,95%CI:1.09–4.45).Conclusion An association was observed between occupational hazards based on ERS and FBG trajectories.The risk of FBG trajectory levels increase with an increase in ERS.展开更多
BACKGROUND Clinical predictors of dengue fever are crucial for guiding timely management and avoiding life-threatening complications.While prognostic scores are available,a systematic evaluation of these tools is lack...BACKGROUND Clinical predictors of dengue fever are crucial for guiding timely management and avoiding life-threatening complications.While prognostic scores are available,a systematic evaluation of these tools is lacking.AIM To evaluate the performance and accuracy of various proposed dengue clinical prognostic scores.METHODS Three databases,PubMed,EMBASE and Cochrane,were searched for peer-reviewed studies published from inception to 4 September 2023.Studies either developing or validating a prognostic model relevant to dengue fever were included.A total of 29 studies(n=17910)were included.RESULTS Most commonly studied outcomes were severe dengue(15 models)and mortality(8 models).For the paediatric population,Bedside Dengue Severity Score by Gayathri et al(specificity=0.98)and the nomogram model by Nguyen et al(sensitivity=0.87)performed better.For the adult population,the most specific model was reported by Leo et al(specificity=0.98).The most sensitive score is shared between Warning Signs for Severe Dengue as reported by Leo et al and Model 2 by Lee et al(sensitivity=1.00).CONCLUSION While several models demonstrated precision and reliability in predicting severe dengue and mortality,broader application across diverse geographic settings is needed to assess their external validity.展开更多
BACKGROUND Chronic liver disease is a growing global health problem,leading to hepatic decompensation characterized by an array of clinical and biochemical complic-ations.Several scoring systems have been introduced i...BACKGROUND Chronic liver disease is a growing global health problem,leading to hepatic decompensation characterized by an array of clinical and biochemical complic-ations.Several scoring systems have been introduced in assessing the severity of hepatic decompensation with the most frequent ones are Child-Pugh score,model of end-stage liver disease(MELD)score,and MELD-Na score.Anemia is frequently observed in cirrhotic patients and is linked to worsened clinical outcomes.Although studies have explored anemia in liver disease,few have investigated the correlation of hemoglobin level with the severity of hepatic decompensation.AIM To determine the relationship between hemoglobin levels and the severity of decompensated liver disease and comparing the strength of this correlation using the Child-Pugh,MELD,and MELD-Na scores.METHODS This cross-sectional study was conducted at a tertiary care hospital with 652 decompensated liver disease patients enrolled in the study.Data was collected on demographics,clinical history,and laboratory findings,including hemoglobin levels,bilirubin,albumin,prothrombin time(international normalized ratio),sodium,and creatinine.The Child-Pugh,MELD,and MELD-Na scores were calculated.Statistical analysis was performed using Statistical Package for the Social Sciences version 26,and correlations between hemoglobin levels and severity scores were assessed using Spearman's correlation coefficient.RESULTS The study included 405 males(62.1%)and 247 females(37.9%)with an average age of 58.8 years.Significant inverse correlations were found between hemoglobin levels and Child-Pugh,MELD,and MELD-Na scores(P<0.01),with the MELD scoring system being the strongest correlator among all.One-way analysis of variance revealed significant differences in hemoglobin levels across the severity groups of each scoring system(P=0.001).Tukey's post hoc analysis confirmed significant internal differences among each severity group.CONCLUSION Understanding the correlation between hemoglobin and liver disease severity can improve patient management by offering insights into prognosis and guiding treatment decisions.展开更多
Background Renal and liver dysfunction,which are common complications in infectious diseases,are associated with poor clinical outcomes.This study aimed to evaluate the prognostic value of the Model for End-Stage Live...Background Renal and liver dysfunction,which are common complications in infectious diseases,are associated with poor clinical outcomes.This study aimed to evaluate the prognostic value of the Model for End-Stage Liver Disease Excluding International Normalized Ratio(MELD-XI)score for predicting short-term mortality in patients with infective endocarditis(IE)complicated by sepsis.Methods A total of 496 consecutive IE patients complicated with sepsis at Guangdong Provincial People's Hospital were enrolled and divided into three groups according to the tertiles of MELD-XI score:<7.9(n=164),7.9-14.6(n=168),and>14.6(n=164).Major adverse clinical events(MACE)were composite endpoints that included acute heart failure,renal dialysis,stroke,and death during hospitalization.Multivariate analysis was used to explore the prognostic value of MELD-XI score.Results In-hospital and 6-month mortality were 14.3%and 21.5%,respectively.In-hospital mortality and the incidence of MACE rose significantly with higher MELD-XI scores(mortality:8.5%vs.12.5%vs.14.3%,P=0.002;Incidence of MACE:24.4%vs.31%vs.51.2%,P<0.001).Receiver operating characteristic(ROC)curve analysis showed that the optimal cutoff value of MELD-XI score was 15.7[area under the curve(AUC):0.648,95%CI:0.578-0.718,P<0.001].Multivariate regression analysis revealed that MELD-XI score>15.7 was a significantly independent risk factor for both in-hospital[adjusted odds ratio(OR):2.27,95%CI:1.28-4.05,P=0.005]and 6-month mortality[adjusted hazard ratio(HR):1.69,95%CI:1.13-2.53,P=0.011].Conclusions MELD-XI score>15.7 was independently associated with short-term mortality in IE patients complicated with sepsis,suggesting its potential value as a prognostic biomarker for risk stratification in this population.展开更多
Accurate prediction of landslide displacement is crucial for effective early warning of landslide disasters.While most existing prediction methods focus on time-series forecasting for individual monitoring points,ther...Accurate prediction of landslide displacement is crucial for effective early warning of landslide disasters.While most existing prediction methods focus on time-series forecasting for individual monitoring points,there is limited research on the spatiotemporal characteristics of landslide deformation.This paper proposes a novel Multi-Relation Spatiotemporal Graph Residual Network with Multi-Level Feature Attention(MFA-MRSTGRN)that effectively improves the prediction performance of landslide displacement through spatiotemporal fusion.This model integrates internal seepage factors as data feature enhancements with external triggering factors,allowing for accurate capture of the complex spatiotemporal characteristics of landslide displacement and the construction of a multi-source heterogeneous dataset.The MFA-MRSTGRN model incorporates dynamic graph theory and four key modules:multilevel feature attention,temporal-residual decomposition,spatial multi-relational graph convolution,and spatiotemporal fusion prediction.This comprehensive approach enables the efficient analyses of multi-source heterogeneous datasets,facilitating adaptive exploration of the evolving multi-relational,multi-dimensional spatiotemporal complexities in landslides.When applying this model to predict the displacement of the Liangshuijing landslide,we demonstrate that the MFA-MRSTGRN model surpasses traditional models,such as random forest(RF),long short-term memory(LSTM),and spatial temporal graph convolutional networks(ST-GCN)models in terms of various evaluation metrics including mean absolute error(MAE=1.27 mm),root mean square error(RMSE=1.49 mm),mean absolute percentage error(MAPE=0.026),and R-squared(R^(2)=0.88).Furthermore,feature ablation experiments indicate that incorporating internal seepage factors improves the predictive performance of landslide displacement models.This research provides an advanced and reliable method for landslide displacement prediction.展开更多
基金National Key Research and Development Program of China,No.2019YFD1101304National Natural Science Foundation of China,No.52278059+1 种基金Natural Science Foundation of Hunan Province of China,No.2024JJ8316Hunan Provincial Innovation Foundation For Postgraduate,No.CX20250634。
文摘Urban spatial morphology(USM)optimization is critical to balancing biodiversity conservation and sustainable urbanization.However,previous studies predominantly focused on the socio-economic efficiency and static ecological metrics and rarely addressed the dynamic USM optimization across spatial scales.Here,we developed a multi-level ecological network(MEN)framework to resolve the tension between urban expansion and ecological integrity.By integrating the cost-weighted distance analysis with a hierarchical network transmission mechanism,we established a cross-scale spatial optimization system,which coordinated the regional ecological corridors and local habitat patches.Comparative experiments with conventional single-scale approaches and scenario simulations using the PLUS model show that the MEN framework had superior performance in three dimensions:(1)spatial governance:the primary-level network(peri-urban natural reserves)effectively contained urban sprawl,and the secondary-level network(intra-urban green corridors)mitigated habitat fragmentation and improved the built-environment;(2)scenario robustness:the model maintained an optimal compactness-loose balance in multiple development pathways;(3)landscape metrics:patch fragmentation decreased by 18.25%,and the internal landscape richness improved by 10.66%compared to the scenario without USM optimization.The findings provide new insight to establish a hierarchical ecological optimization framework as a nature-based spatial protocol to reconcile metropolitan growth with landscape sustainability.
基金supported by the National Natural Science Foundation of China(No.52090041).
文摘The influence of different solution and aging conditions on the microstructure,impact toughness,and crack initiation and propagation mechanisms of the novel α+β titanium alloy Ti6422 was systematically investigated.By adjusting the furnace cooling time after solution treatment and the aging temperature,Ti6422 alloy samples were developed with a multi-level lamellar microstructure,in-cluding microscaleαcolonies and α_(p) lamellae,as well as nanoscale α_(s) phases.Extending the furnace cooling time after solution treatment at 920℃ for 1 h from 240 to 540 min,followed by aging at 600℃ for 6 h,increased the α_(p) lamella content,reduced the α_(s) phase content,expanded theαcolonies and α_(p) lamellae size,and improved the impact toughness from 22.7 to 53.8 J/cm^(2).Additionally,under the same solution treatment,raising the aging temperature from 500 to 700℃ resulted in a decrease in the α_(s) phase content and a growth in the thickness of the α_(p) lamella and α_(s) phase.The impact toughness increased significantly with these changes.Samples with high α_(p) lamellae content or large α_(s) phase size exhibited high crack initiation and propagation energies.Impact deformation caused severe kinking of the α_(p) lamellae in crack initiation and propagation areas,leading to a uniform and high-density kernel average misorientation(KAM)distribu-tion,enhancing plastic deformation coordination and uniformity.Moreover,the multidirectional arrangement of coarserαcolonies and α_(p) lamellae continuously deflect the crack propagation direction,inhibiting crack propagation.
基金The National Natural Science Foundation of China-Regional Science“Identification of novel drug targets for lung cancer via Mendelian randomization analysis based on blood proteomics”(62362062)The 2025 Xinjiang University Excellent Graduate Innovation Project“Research on identification of therapeutic targets and predictive factors for mental disorders based on proteomics”(XJDX2025YJS151)。
文摘Traditional psychiatric diagnosis relies on subjective symptom assessment,lacking objective biomarkers that hinder early detection and personalized treatment.Plasma proteins and polygenic risk score(PRS),as potential predictive tools,hold promise for advancing early diagnosis of mental disorders.This study aims to evaluate the predictive potential of proteomic features and PRS in multiple mental illnesses(depression,schizophrenia,and post-traumatic stress disorder(PTSD)).Using participant data from the UK Biobank-Pharma Proteomics Project,we screen protein associations with mental disorders through least absolute shrinkage and selection operator(LASSO)analysis and construct a Cox regression risk prediction model by integrating the PRS.Additionally,we evaluate predictive performance using 6 machine learning methods and Kaplan-Meier survival curves.Our findings reveal distinct predictive patterns across dis-orders.For depression,integrating plasma proteins with PRS significantly improves prediction beyond the clinical model(C-index=0.6322).For schizophrenia,adding plasma proteins enhances predictive performance,whereas PRS provides no significant improvement.For PTSD,neither plasma proteins nor PRS add substantial predictive value beyond clinical variables.Risk stratification analysis demonstrat that all three mental disorders models can clearly distinguish high-risk from low-risk groups(depression:HR=2.34,P<0.001;schizophrenia:HR=5.47,P<0.001;PTSD:HR=3.02,P<0.001).Al-though it shows good performance in short-term prediction,its long-term prediction ability has decreased,and it needs to be further optimized in the future.This study underscores the differential utility of biomarkers across mental disorders and provides a rationale for disorder-specific predictive modeling in precision psychiatry.
文摘Objective: To analyze the effect of pain nursing combined with exercise and posture intervention on improving Visual Analogue Scale (VAS) scores in patients after kidney stone surgery. Methods: A sample of 80 patients who underwent kidney stone surgery from October 2024 to October 2025 was randomly divided into groups using a random number table. Group A received pain nursing combined with exercise and posture intervention, while Group B received conventional nursing. Postoperative recovery time, VAS scores, and postoperative complications were compared between the two groups. Results: The postoperative recovery time in Group A was shorter than that in Group B, with p < 0.05. The VAS scores at 12 hours, 24 hours, and 72 hours postoperatively in Group A were all lower than those in Group B, with p < 0.05. The postoperative complication rate in Group A was lower than that in Group B, with p < 0.05. Conclusion: Pain nursing combined with exercise and posture intervention in postoperative nursing for kidney stone patients can shorten postoperative recovery time and alleviate pain scores.
基金National Natural Science Foundation of China(Nos.42301473,42271424,42171397)Chinese Postdoctoral Innovation Talents Support Program(No.BX20230299)+2 种基金China Postdoctoral Science Foundation(No.2023M742884)Natural Science Foundation of Sichuan Province(Nos.24NSFSC2264,2025ZNSFSC0322)Key Research and Development Project of Sichuan Province(No.24ZDYF0633).
文摘As a key node of modern transportation network,the informationization management of road tunnels is crucial to ensure the operation safety and traffic efficiency.However,the existing tunnel vehicle modeling methods generally have problems such as insufficient 3D scene description capability and low dynamic update efficiency,which are difficult to meet the demand of real-time accurate management.For this reason,this paper proposes a vehicle twin modeling method for road tunnels.This approach starts from the actual management needs,and supports multi-level dynamic modeling from vehicle type,size to color by constructing a vehicle model library that can be flexibly invoked;at the same time,semantic constraint rules with geometric layout,behavioral attributes,and spatial relationships are designed to ensure that the virtual model matches with the real model with a high degree of similarity;ultimately,the prototype system is constructed and the case region is selected for the case study,and the dynamic vehicle status in the tunnel is realized by integrating real-time monitoring data with semantic constraints for precise virtual-real mapping.Finally,the prototype system is constructed and case experiments are conducted in selected case areas,which are combined with real-time monitoring data to realize dynamic updating and three-dimensional visualization of vehicle states in tunnels.The experiments show that the proposed method can run smoothly with an average rendering efficiency of 17.70 ms while guaranteeing the modeling accuracy(composite similarity of 0.867),which significantly improves the real-time and intuitive tunnel management.The research results provide reliable technical support for intelligent operation and emergency response of road tunnels,and offer new ideas for digital twin modeling of complex scenes.
基金financially supported by Guangdong Province Basic and Applied Basic Research Fund Project(Grant No.2022B1515250009)Liaoning Provincial Natural Science Foundation-Doctoral Research Start-up Fund Project(Grant No.2024-BSBA-05)+1 种基金Major Science and Technology Innovation Project in Shandong Province(Grant No.2024CXGC010803)the National Natural Science Foundation of China(Grant Nos.52271269 and 12302147).
文摘The umbilical,a key component in offshore energy extraction,plays a vital role in ensuring the stable operation of the entire production system.The extensive variety of cross-sectional components creates highly complex layout combinations.Furthermore,due to constraints in component quantity and geometry within the cross-sectional layout,filler bodies must be incorporated to maintain cross-section performance.Conventional design approaches based on manual experience suffer from inefficiency,high variability,and difficulties in quantification.This paper presents a multi-level automatic filling optimization design method for umbilical cross-sectional layouts to address these limitations.Initially,the research establishes a multi-objective optimization model that considers compactness,balance,and wear resistance of the cross-section,employing an enhanced genetic algorithm to achieve a near-optimal layout.Subsequently,the study implements an image processing-based vacancy detection technique to accurately identify cross-sectional gaps.To manage the variability and diversity of these vacant regions,the research introduces a multi-level filling method that strategically selects and places filler bodies of varying dimensions,overcoming the constraints of uniform-size fillers.Additionally,the method incorporates a hierarchical strategy that subdivides the complex cross-section into multiple layers,enabling layer-by-layer optimization and filling.This approach reduces manufac-turing equipment requirements while ensuring practical production process feasibility.The methodology is validated through a specific umbilical case study.The results demonstrate improvements in compactness,balance,and wear resistance compared with the initial cross-section,offering novel insights and valuable references for filler design in umbilical cross-sections.
文摘BACKGROUND Emphysematous pyelonephritis(EPN)is a life-threatening necrotizing renal parenchyma infection characterized by gas formation due to severe bacterial infection,predominantly affecting diabetic and immunocompromised patients.It carries high morbidity and mortality,requiring early diagnosis and timely intervention.Various prognostic scoring systems help in triaging critically ill patients.The National Early Warning Score 2(NEWS 2)scoring system is a widely used physiological assessment tool that evaluates clinical deterioration based on vital parameters,but its standard form lacks specificity for risk stratification in EPN,necessitating modifications to improve treatment decisionmaking and prognostic accuracy in this critical condition.AIM To highlight the need to modify the NEWS 2 score to enable more intense monitoring and better treatment outcomes.METHODS This prospective study was done on all EPN patients admitted to our hospital over the past 12 years.A weighted average risk-stratification index was calculated for each of the three groups,mortality risk was calculated for each of the NEWS 2 scores,and the need for intervention for each of the three groups was calculated.The NEWS 2 score was subsequently modified with 0-6,7-14 and 15-20 scores included in groups 1,2 and 3,respectively.RESULTS A total of 171 patients with EPN were included in the study,with a predominant association with diabetes(90.6%)and a female-to-male ratio of 1.5:1.The combined prognostic scoring of the three groups was 10.7,13.0,and 21.9,respectively(P<0.01).All patients managed conservatively belonged to group 1(P<0.01).Eight patients underwent early nephrectomy,with six from group 3(P<0.01).Overall mortality was 8(4.7%),with seven from group 3(87.5%).The cutoff NEWS 2 score for mortality was identified to be 15,with a sensitivity of 87.5%,specificity of 96.9%,and an overall accuracy rate of 96.5%.The area under the curve to predict mortality based on the NEWS 2 score was 0.98,with a confidence interval of(0.97,1.0)and P<0.001.CONCLUSION Modified NEWS 2(mNEWS 2)score dramatically aids in the appropriate assessment of treatment-related outcomes.MNEWS 2 scores should become the practice standard to reduce the morbidity and mortality associated with this dreaded illness.
基金Supported by Shaanxi Provincial Social Development Fund,No.2024SF-YBXM-140.
文摘BACKGROUND Post-hepatectomy liver failure(PHLF)after liver resection is one of the main complications causing postoperative death in patients with hepatocellular carcinoma(HCC).It is crucial to help clinicians identify potential high-risk PHLF patients as early as possible through preoperative evaluation.AIM To identify risk factors for PHLF and develop a prediction model.METHODS This study included 248 patients with HCC at The Second Affiliated Hospital of Air Force Medical University between January 2014 and December 2023;these patients were divided into a training group(n=164)and a validation group(n=84)via random sampling.The independent variables for the occurrence of PHLF were identified by univariate and multivariate analyses and visualized as nomograms.Ultimately,comparisons were made with traditional models via receiver operating characteristic(ROC)curves,calibration curves,and decision curve analysis(DCA).RESULTS In this study,portal vein width[odds ratio(OR)=1.603,95%CI:1.288-1.994,P≤0.001],the preoperative neutrophil-to-lymphocyte ratio(NLR)(OR=1.495,95%CI:1.126-1.984,P=0.005),and the albumin-bilirubin(ALBI)score(OR=8.868,95%CI:2.144-36.678,P=0.003)were independent risk factors for PHLF.A nomogram prediction model was developed using these factors.ROC and DCA analyses revealed that the predictive efficacy and clinical value of this model were better than those of traditional models.CONCLUSION A new Nomogram model for predicting PHLF in HCC patients was successfully established based on portal vein width,the NLR,and the ALBI score,which outperforms the traditional model.
基金Natural Science Foundation-funded Project:Mechanism of Action of Detoxification Formula to Inhibit Hypoxia-Inducible Factor 1 Alpha-Exosomal MicroRNA-130b-3p-Sterile Alpha Motif Domain-Containing Protein 90-mediated Macrophage M2-type Polarisation to Improve the Immunosuppressive Microenvironment in Hepatocellular Carcinoma (No.82374540)Medical Innovation Research Project of Shanghai Science and Technology Commission:a Multicenter Prospective Randomized Controlled Study of “Arsenic Target” Combination Therapy for Unresectable Hepatocellular Carcinoma (No.22Y11921200)。
文摘OBJECTIVE:To investigate the clinical efficacy of using a Jiedu formula(解毒方) as an adjunctive therapy in patients with hepatocellular carcinoma(HCC) after hepatectomy.METHODS:In total,354 patients were included in this study.All patients were categorized into the traditional herbal medicine(THM) group(n = 115) or the non-THM treatment(nTHM) group(n = 239),with the Jiedu formula administered twice a day to the patients in the THM group.The primary outcome was recurrence-free survival(RFS).Univariate and multivariate Cox regression analyses were performed to identify the prognostic factors associated with RFS.Then,the high risk of recurrence among patients was identified,and propensity score matching(PSM) and RFS analysis were performed to analyze the prognostic factors for the outcomes of patients at a high risk of recurrence in different groups.RESULTS:The one,two,three,and five-year RFS rates of the THM and nTHM groups were 76.4% vs 66.1%,65.5% vs 48.8%,57.9% vs 39.9%,and 43.9% vs 29.2%,respectively.The results of the Multivariate Cox analysis showed that giant tumors [hazard ratio(HR),1.54,P = 0.04],poor degree of differentiation,microsatellite,or microvascular invasion(HR,1.29,P = 0.09) increased the risk of recurrence.In the population with a high risk of recurrence,after PSM,the one,two,three,and five-year survival rates were 70.6% vs 68.0%,63.0% vs 43.1%,59.6% vs 33.3%,and 41.9% vs 26.4%,respectively.CONCLUSION:In this study,THM was found to be an effective agent for adjuvant therapy for HCC to prevent early recurrence of HCC after hepatic resection.
基金supported by the Key Research and Development Program of the Ministry of Science and Technology of China(grant number:2016YF0900605)the Key Research and Development Program of Hebei Province(grant number:192777129D)+1 种基金the Joint Fund for Iron and Steel of the Natural Science Foundation of Hebei Province(grant number:H2016209058)the National Natural Science Foundation for Regional Joint Fund of China(grant number:U22A20364)。
文摘Objective We aimed to investigate the patterns of fasting blood glucose(FBG)trajectories and analyze the relationship between various occupational hazard factors and FBG trajectories in male steelworkers.Methods The study cohort included 3,728 workers who met the selection criteria for the Tanggang Occupational Cohort(TGOC)between 2017 and 2022.A group-based trajectory model was used to identify the FBG trajectories.Environmental risk scores(ERS)were constructed using regression coefficients from the occupational hazard model as weights.Univariate and multivariate logistic regression analyses were performed to explore the effects of occupational hazard factors using the ERS on FBG trajectories.Results FBG trajectories were categorized into three groups.An association was observed between high temperature,noise exposure,and FBG trajectory(P<0.05).Using the first quartile group of ERS1 as a reference,the fourth quartile group of ERS1 had an increased risk of medium and high FBG by 1.90and 2.21 times,respectively(odds ratio[OR]=1.90,95%confidence interval[CI]:1.17–3.10;OR=2.21,95%CI:1.09–4.45).Conclusion An association was observed between occupational hazards based on ERS and FBG trajectories.The risk of FBG trajectory levels increase with an increase in ERS.
文摘BACKGROUND Clinical predictors of dengue fever are crucial for guiding timely management and avoiding life-threatening complications.While prognostic scores are available,a systematic evaluation of these tools is lacking.AIM To evaluate the performance and accuracy of various proposed dengue clinical prognostic scores.METHODS Three databases,PubMed,EMBASE and Cochrane,were searched for peer-reviewed studies published from inception to 4 September 2023.Studies either developing or validating a prognostic model relevant to dengue fever were included.A total of 29 studies(n=17910)were included.RESULTS Most commonly studied outcomes were severe dengue(15 models)and mortality(8 models).For the paediatric population,Bedside Dengue Severity Score by Gayathri et al(specificity=0.98)and the nomogram model by Nguyen et al(sensitivity=0.87)performed better.For the adult population,the most specific model was reported by Leo et al(specificity=0.98).The most sensitive score is shared between Warning Signs for Severe Dengue as reported by Leo et al and Model 2 by Lee et al(sensitivity=1.00).CONCLUSION While several models demonstrated precision and reliability in predicting severe dengue and mortality,broader application across diverse geographic settings is needed to assess their external validity.
文摘BACKGROUND Chronic liver disease is a growing global health problem,leading to hepatic decompensation characterized by an array of clinical and biochemical complic-ations.Several scoring systems have been introduced in assessing the severity of hepatic decompensation with the most frequent ones are Child-Pugh score,model of end-stage liver disease(MELD)score,and MELD-Na score.Anemia is frequently observed in cirrhotic patients and is linked to worsened clinical outcomes.Although studies have explored anemia in liver disease,few have investigated the correlation of hemoglobin level with the severity of hepatic decompensation.AIM To determine the relationship between hemoglobin levels and the severity of decompensated liver disease and comparing the strength of this correlation using the Child-Pugh,MELD,and MELD-Na scores.METHODS This cross-sectional study was conducted at a tertiary care hospital with 652 decompensated liver disease patients enrolled in the study.Data was collected on demographics,clinical history,and laboratory findings,including hemoglobin levels,bilirubin,albumin,prothrombin time(international normalized ratio),sodium,and creatinine.The Child-Pugh,MELD,and MELD-Na scores were calculated.Statistical analysis was performed using Statistical Package for the Social Sciences version 26,and correlations between hemoglobin levels and severity scores were assessed using Spearman's correlation coefficient.RESULTS The study included 405 males(62.1%)and 247 females(37.9%)with an average age of 58.8 years.Significant inverse correlations were found between hemoglobin levels and Child-Pugh,MELD,and MELD-Na scores(P<0.01),with the MELD scoring system being the strongest correlator among all.One-way analysis of variance revealed significant differences in hemoglobin levels across the severity groups of each scoring system(P=0.001).Tukey's post hoc analysis confirmed significant internal differences among each severity group.CONCLUSION Understanding the correlation between hemoglobin and liver disease severity can improve patient management by offering insights into prognosis and guiding treatment decisions.
文摘Background Renal and liver dysfunction,which are common complications in infectious diseases,are associated with poor clinical outcomes.This study aimed to evaluate the prognostic value of the Model for End-Stage Liver Disease Excluding International Normalized Ratio(MELD-XI)score for predicting short-term mortality in patients with infective endocarditis(IE)complicated by sepsis.Methods A total of 496 consecutive IE patients complicated with sepsis at Guangdong Provincial People's Hospital were enrolled and divided into three groups according to the tertiles of MELD-XI score:<7.9(n=164),7.9-14.6(n=168),and>14.6(n=164).Major adverse clinical events(MACE)were composite endpoints that included acute heart failure,renal dialysis,stroke,and death during hospitalization.Multivariate analysis was used to explore the prognostic value of MELD-XI score.Results In-hospital and 6-month mortality were 14.3%and 21.5%,respectively.In-hospital mortality and the incidence of MACE rose significantly with higher MELD-XI scores(mortality:8.5%vs.12.5%vs.14.3%,P=0.002;Incidence of MACE:24.4%vs.31%vs.51.2%,P<0.001).Receiver operating characteristic(ROC)curve analysis showed that the optimal cutoff value of MELD-XI score was 15.7[area under the curve(AUC):0.648,95%CI:0.578-0.718,P<0.001].Multivariate regression analysis revealed that MELD-XI score>15.7 was a significantly independent risk factor for both in-hospital[adjusted odds ratio(OR):2.27,95%CI:1.28-4.05,P=0.005]and 6-month mortality[adjusted hazard ratio(HR):1.69,95%CI:1.13-2.53,P=0.011].Conclusions MELD-XI score>15.7 was independently associated with short-term mortality in IE patients complicated with sepsis,suggesting its potential value as a prognostic biomarker for risk stratification in this population.
基金the funding support from the National Natural Science Foundation of China(Grant No.52308340)Chongqing Talent Innovation and Entrepreneurship Demonstration Team Project(Grant No.cstc2024ycjh-bgzxm0012)the Science and Technology Projects supported by China Coal Technology and Engineering Chongqing Design and Research Institute(Group)Co.,Ltd.(Grant No.H20230317).
文摘Accurate prediction of landslide displacement is crucial for effective early warning of landslide disasters.While most existing prediction methods focus on time-series forecasting for individual monitoring points,there is limited research on the spatiotemporal characteristics of landslide deformation.This paper proposes a novel Multi-Relation Spatiotemporal Graph Residual Network with Multi-Level Feature Attention(MFA-MRSTGRN)that effectively improves the prediction performance of landslide displacement through spatiotemporal fusion.This model integrates internal seepage factors as data feature enhancements with external triggering factors,allowing for accurate capture of the complex spatiotemporal characteristics of landslide displacement and the construction of a multi-source heterogeneous dataset.The MFA-MRSTGRN model incorporates dynamic graph theory and four key modules:multilevel feature attention,temporal-residual decomposition,spatial multi-relational graph convolution,and spatiotemporal fusion prediction.This comprehensive approach enables the efficient analyses of multi-source heterogeneous datasets,facilitating adaptive exploration of the evolving multi-relational,multi-dimensional spatiotemporal complexities in landslides.When applying this model to predict the displacement of the Liangshuijing landslide,we demonstrate that the MFA-MRSTGRN model surpasses traditional models,such as random forest(RF),long short-term memory(LSTM),and spatial temporal graph convolutional networks(ST-GCN)models in terms of various evaluation metrics including mean absolute error(MAE=1.27 mm),root mean square error(RMSE=1.49 mm),mean absolute percentage error(MAPE=0.026),and R-squared(R^(2)=0.88).Furthermore,feature ablation experiments indicate that incorporating internal seepage factors improves the predictive performance of landslide displacement models.This research provides an advanced and reliable method for landslide displacement prediction.
