Rock damage significantly affects coupled thermo-hydro-mechanical(THM)behavior in deep geothermal exploitation through changing thermal and hydrological properties of rocks.For this,a thermo-hydro-mechanical-damage(TH...Rock damage significantly affects coupled thermo-hydro-mechanical(THM)behavior in deep geothermal exploitation through changing thermal and hydrological properties of rocks.For this,a thermo-hydro-mechanical-damage(THMD)coupled model was developed to describe the coupling between rock damage and mechanical,fluid flow and heat transfer fields.The model considers rock heterogeneity,and incorporates the Mohr-Coulomb failure criterion and the maximum tensile stress criterion to evaluate shear and tensile damage.This numerical modeling methodology was first verified against analytical solutions and experimental results,and was then used to simulate the THMD coupling behavior in deep geothermal exploitation.A coupled numerical model was set up to simulate the geothermal fluids extraction and re-injection process in a reservoir at 1 km depth over a 7-year period.Rock damage was found to accelerate the propagation of cold fronts away from the injection well,and have a distinct effect on the performance of geothermal exploitation.When the rock damage was considered,the field injectivity increases by 8.4 times,the range of cooled regions increases by 18.6 times,and the vertical deformation changes by 1.2 times after 7 years of geothermal operations,compared to the scenario where it was not considered.Parametric studies have suggested that thermal contraction dominates the rock damage evolution,and that thermal-induced rock damage only occurs at a sufficiently large temperature difference between fluids injected and the reservoir.This work underscores the importance of accurately accounting for the damage effect on reservoir response during fluid injection activities that cause significant cooling of reservoir rocks.展开更多
By leveraging the unique qualities of microorganisms,engineered living materials(ELMs)offer functional and economic advantages in everyday applications along with notable ecological benefits.This study contributes to ...By leveraging the unique qualities of microorganisms,engineered living materials(ELMs)offer functional and economic advantages in everyday applications along with notable ecological benefits.This study contributes to the growing field of biodesign by examining the potential of Flavobacteria for thermochromic ELMs.Many Flavobacteria,commonly found in marine environments,produce iridescent structural colorations as their colonies expand on semi-solid surfaces through gliding motility.In this study,we analyzed the effects of temperature variations on flavobacterium Cellulophaga lytica PLY A 2,characterizing distinct changes in colony growth and iridescent colorations at a macroscopic and microscopic scale.Using scanning electron microscopy,we investigated the relationship between iridescent color and the underlying cell-based optical structures.By providing insights into the temperature-responsive behavior of Flavobacteria,our findings highlight their potential for future thermochromic ELMs-with applications ranging from sustainable food packaging to smart textiles-while encouraging further characterization studies within biodesign research.展开更多
Background In patients with coronary artery disease,age is of known significance in predicting outcomes.Data on clinical outcomes in patients≥85 years undergoing percutaneous coronary intervention(PCI)remain scarce.T...Background In patients with coronary artery disease,age is of known significance in predicting outcomes.Data on clinical outcomes in patients≥85 years undergoing percutaneous coronary intervention(PCI)remain scarce.The study aim was to determine clinical characteristics,risk of adverse cardiovascular events,and mortality in patients aged≥85 years compared to those aged<85 undergoing PCI.Methods In this retrospective study,data were obtained from the nationwide Netherlands Heart Registration on patients undergoing PCI between January 1st,2017 and January 1st,2021.The primary endpoint was all-cause mortality at long-term followup.Results A total of 155,683 patients underwent PCI,of which 100,209(64.4%)acute coronary syndrome cases.Compared to patients aged<85 years,patients aged≥85 were more often female and showed a higher number of cardiovascular comorbidities,including impaired left ventricle ejection fraction and reduced kidney function.Mortality at short-term and long-term follow-up were significantly higher in those aged≥85(P<0.001).Patients aged≥85 were more likely to have a myocardial infarction within 30 days following the index intervention(0.9%vs.0.7%;P=0.024),though they less often underwent revascularization at longterm follow-up compared to patients aged<85(P<0.001).Conclusions The elderly(≥85 years)patient requiring PCI carries an extensive cardiovascular risk profile,translating in significant risk of recurrent cardiovascular events and increased mortality rate.Clinicians should carefully weigh perceived risks and potential benefits in the individual patient,considering the patients’age,cardiovascular risk profile,and associated risk of morbidity and mortality.展开更多
非常规突发事件下,网络亲社会行为是帮助整合资源、恢复现实世界秩序的重要渠道。研究探究风险情境下风险感知是否会驱动人们更倾向于做出网络亲社会行为及其如何进一步影响非常规突发事件的走向。研究1采用问卷法,结合恐惧管理理论,验...非常规突发事件下,网络亲社会行为是帮助整合资源、恢复现实世界秩序的重要渠道。研究探究风险情境下风险感知是否会驱动人们更倾向于做出网络亲社会行为及其如何进一步影响非常规突发事件的走向。研究1采用问卷法,结合恐惧管理理论,验证了风险感知经由本体安全感对网络亲社会行为的影响以及健康自我效能感的调节作用;研究2采用基于主体的建模技术(agent based model, ABM)建模预测了网络亲社会行为通过调节医疗资源有效分配,有效减少疫情峰值人数、缩短疫情持续时间。研究拓展了对网络亲社会行为动因的理解以及对影响非常规突发事件走向的预测,启示人们通过增进网络亲社会行为对风险事件施加正向的影响。展开更多
Background The potential of exercise as a concurrent therapy for actively treated primary tumors has been suggested by emerging preclinical and observational studies.However,clinical trials regarding this question are...Background The potential of exercise as a concurrent therapy for actively treated primary tumors has been suggested by emerging preclinical and observational studies.However,clinical trials regarding this question are scarce.Therefore,we conducted a randomized controlled trial investigating the effects of aerobic or resistance exercise concomitant to neoadjuvant chemotherapy(NACT)on tumor size.Methods In the BENEFIT study(German title:Bewegung bei neoadjuvanter chemotherapie zur verbesserung der fitness),patients with breast cancer scheduled for NACT were randomly assigned to supervised resistance training(RT,n=60)or aerobic training(AT,n=60)twice weekly during NACT or to a waitlist control group(WCG,n=60).The primary outcome,“change in tumor size”,as well as the secondary clinical outcomes pathologic complete response(pCR),type of surgery(breast conserving/mastectomy),axillary lymph node dissection(ALND,yes/no),premature discontinuation of chemotherapy(yes/no),and relative dose intensity(RDI)were derived from clinical records.Due to the highly skewed distribution,the primary outcome was categorized.Multiple(ordinal)logistic regression analyses were performed.Results Overall,there was no significant difference in post-intervention tumor size between RT or AT and WCG.However,there was a significant effect modification by hormone receptor(HR)status(P_(interaction)=0.030).Among patients with HR+tumors,results suggest a beneficial effect of AT on tumor shrinkage(odds ratio(OR)=2.37,95%confidence interval(95%CI):0.97‒5.78),on pCR(OR=3.21,95%CI:0.97‒10.61);and on ALND(OR=3.76,95%CI:0.78‒18.06)compared to WCG.The effects of RT were slightly less pronounced.For HR−subtypes,beneficial effects on RDI were found for AT(OR=3.71,95%CI:1.20‒11.50)and similarly for RT(OR=2.58,95%CI:0.88‒7.59).Both AT and RT had favorable effects on premature discontinuation of chemotherapy(OR(no vs.yes)=2.34,95%CI:1.10‒5.06),irrespective of tumor receptor status.Conclusion While there was no significant effect on the primary outcome in the overall group,aerobic and resistance exercise concomitant to NACT seem to beneficially affect tumor shrinkage and pCR,reduce the need for ALND among patients with HR+breast cancers,and prevent low RDI among patients with HR–breast cancers.These results warrant confirmation in further trials.展开更多
Cryotherapy is a treatment modality that uses extreme cold to destroy unwanted tissue through both immediate and delayed cellular injury.This therapy is increasingly being adopted across various medical specialties du...Cryotherapy is a treatment modality that uses extreme cold to destroy unwanted tissue through both immediate and delayed cellular injury.This therapy is increasingly being adopted across various medical specialties due to its minimally invasive nature and technological advancements that have been made.In the esophagus,cryotherapy is particularly utilized for the management of Barrett esophagus.It has been demonstrated to be effective and safe with potential benefits,such as a reduction in pain,over radiofrequency ablation.Additionally,it might offer a valuable alternative for patients unresponsive to radiofrequency ablation.Cryotherapy is applied for other conditions as well,including esophageal squamous cell neoplasia and malignant dysphagia.More research is needed to gain understanding of the utility in these conditions.Interestingly,cryotherapy has shown the ability to enhance the host’s immune response in reaction to antigens left in situ after treatment.While preclinical data have demonstrated promising results,the immune response is often insufficient to induce tumor regression in the clinical setting.Therefore,there is growing interest in the combination of cryotherapy and immunotherapy where ablation creates an antigen depot,and the immune system is subsequently stimulated.This combination holds promise for the future and potentially opens new doors for a breakthrough in cancer treatment.展开更多
This research investigates the influence of indoor and outdoor factors on photovoltaic(PV)power generation at Utrecht University to accurately predict PV system performance by identifying critical impact factors and i...This research investigates the influence of indoor and outdoor factors on photovoltaic(PV)power generation at Utrecht University to accurately predict PV system performance by identifying critical impact factors and improving renewable energy efficiency.To predict plant efficiency,nineteen variables are analyzed,consisting of nine indoor photovoltaic panel characteristics(Open Circuit Voltage(Voc),Short Circuit Current(Isc),Maximum Power(Pmpp),Maximum Voltage(Umpp),Maximum Current(Impp),Filling Factor(FF),Parallel Resistance(Rp),Series Resistance(Rs),Module Temperature)and ten environmental factors(Air Temperature,Air Humidity,Dew Point,Air Pressure,Irradiation,Irradiation Propagation,Wind Speed,Wind Speed Propagation,Wind Direction,Wind Direction Propagation).This study provides a new perspective not previously addressed in the literature.In this study,different machine learning methods such as Multilayer Perceptron(MLP),Multivariate Adaptive Regression Spline(MARS),Multiple Linear Regression(MLR),and Random Forest(RF)models are used to predict power values using data from installed PVpanels.Panel values obtained under real field conditions were used to train the models,and the results were compared.The Multilayer Perceptron(MLP)model was achieved with the highest classification accuracy of 0.990%.The machine learning models used for solar energy forecasting show high performance and produce results close to actual values.Models like Multi-Layer Perceptron(MLP)and Random Forest(RF)can be used in diverse locations based on load demand.展开更多
The impact of different global and local variables in urban development processes requires a systematic study to fully comprehend the underlying complexities in them.The interplay between such variables is crucial for...The impact of different global and local variables in urban development processes requires a systematic study to fully comprehend the underlying complexities in them.The interplay between such variables is crucial for modelling urban growth to closely reflects reality.Despite extensive research,ambiguity remains about how variations in these input variables influence urban densification.In this study,we conduct a global sensitivity analysis(SA)using a multinomial logistic regression(MNL)model to assess the model’s explanatory and predictive power.We examine the influence of global variables,including spatial resolution,neighborhood size,and density classes,under different input combinations at a provincial scale to understand their impact on densification.Additionally,we perform a stepwise regression to identify the significant explanatory variables that are important for understanding densification in the Brussels Metropolitan Area(BMA).Our results indicate that a finer spatial resolution of 50 m and 100 m,smaller neighborhood size of 5×5 and 3×3,and specific density classes—namely 3(non-built-up,low and high built-up)and 4(non-built-up,low,medium and high built-up)—optimally explain and predict urban densification.In line with the same,the stepwise regression reveals that models with a coarser resolution of 300 m lack significant variables,reflecting a lower explanatory power for densification.This approach aids in identifying optimal and significant global variables with higher explanatory power for understanding and predicting urban densification.Furthermore,these findings are reproducible in a global urban context,offering valuable insights for planners,modelers and geographers in managing future urban growth and minimizing modelling.展开更多
Plant growth-promoting rhizobacteria(PGPR)have been widely used for the promotion of plant performance.Predatory protists can influence the taxonomic and functional composition of rhizosphere bacteria.However,research...Plant growth-promoting rhizobacteria(PGPR)have been widely used for the promotion of plant performance.Predatory protists can influence the taxonomic and functional composition of rhizosphere bacteria.However,research on the impact of the interaction between protist and PGPR on plant performance remains at a very early stage.Here,we examined the impacts of individual inoculation of protist(Colpoda inflata,Dimastigella trypaniformis,or Vermamoeba vermiformis)or the PGPR strain Bacillus velezensis SQR9 as well as the co-inoculation of the protist C.inflata and B.velezensis SQR9 on the growth of tomato plants.We found that all individual protists and Bacillus could promote plant growth compared to the control with no microbe inoculation,with the co-inoculation of C.inflata and B.velezensis SQR9 achieving the greatest performance,including plant height,fresh weight,and dry weight.Different protists harbored distinct rhizosphere bacterial communities,with the co-inoculation of protist and Bacillus resulting in the lowest bacterial diversity and driving significant changes in community structure and composition,particularly by increasing the relative abundance of Proteobacteria.Random forest model highlighted Cellvibrio as the most important bacterial predictor of plant growth,which was enriched after protist inoculation,especially after the mixed inoculation of protist and Bacillus.We further found that bacterial functional genes of nitrogen metabolism were the key determinants of plant growth.These results indicate that the interaction between protists and Bacillus can support plant growth by reshaping rhizosphere bacterial community composition and function.Understanding the interaction mechanisms between protist and PGPR is crucial for their effective utilization in sustainable agriculture.展开更多
BACKGROUND Partial hepatectomy continues to be the primary treatment approach for liver tumors,and post-hepatectomy liver failure(PHLF)remains the most critical lifethreatening complication following surgery.AIM To co...BACKGROUND Partial hepatectomy continues to be the primary treatment approach for liver tumors,and post-hepatectomy liver failure(PHLF)remains the most critical lifethreatening complication following surgery.AIM To comprehensively review the PHLF prognostic models developed in recent years and objectively assess the risk of bias in these models.METHODS This review followed the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guideline.Three databases were searched from November 2019 to December 2022,and references as well as cited literature in all included studies were manually screened in March 2023.Based on the defined inclusion criteria,articles on PHLF prognostic models were selected,and data from all included articles were extracted by two independent reviewers.The PROBAST was used to evaluate the quality of each included article.RESULTS A total of thirty-four studies met the eligibility criteria and were included in the analysis.Nearly all of the models(32/34,94.1%)were developed and validated exclusively using private data sources.Predictive variables were categorized into five distinct types,with the majority of studies(32/34,94.1%)utilizing multiple types of data.The area under the curve for the training models included ranged from 0.697 to 0.956.Analytical issues resulted in a high risk of bias across all studies included.CONCLUSION The validation performance of the existing models was substantially lower compared to the development models.All included studies were evaluated as having a high risk of bias,primarily due to issues within the analytical domain.The progression of modeling technology,particularly in artificial intelligence modeling,necessitates the use of suitable quality assessment tools.展开更多
A promising structured catalyst was developed through proper coating of boron-modified ZSM-5 using SiO_(2) and Al_(2)O_(3)-containing binders to investigate catalytic performance as well as mechanical stability of the...A promising structured catalyst was developed through proper coating of boron-modified ZSM-5 using SiO_(2) and Al_(2)O_(3)-containing binders to investigate catalytic performance as well as mechanical stability of the catalyst in a monolithic reactor.The reference and boron-modified ZSM-5 catalysts were synthesized by hydrothermal route.The adherence strength of catalyst samples was characterized using ultrasonic vibration method and FESEM analysis.A series of comparative performance tests were also conducted in two reactors,including monolithic and extruded catalysts for the production of propylene from methanol at atmospheric pressure,reaction temperatures of 500℃,and methanol weight hourly space velocity(WHSV)of 1.5 h^(-1).Initial findings demonstrate that applying the B-modified ZSM-5zeolite in a monolith reactor increased propylene selectivity by about 26%compared to the conventional extruded ZSM-5 catalyst.Moreover,silica bonded to the B-ZSM-5 catalyst in the monolithic reactor,owning sufficient adhesion properties;the proposed catalyst showed the best catalytic performance,with not only a high propylene selectivity(58.5%)but also a large propylene/ethylene(P/E)ratio(8.6).The findings attained in this work would be useful in the production of new efficient catalysts based on a zeolite-coated honeycomb monolith in the methanol-to-propylene process.展开更多
The use ofrenewable energyisan important way toachieve sustainable agriculturalandeconomic development.However,there are differences in accessto renewable energy between the Global North and Global South.This study ut...The use ofrenewable energyisan important way toachieve sustainable agriculturalandeconomic development.However,there are differences in accessto renewable energy between the Global North and Global South.This study utilisedan autoregressive distributed lag-error correctionmodel and thedata spanning from 1991to 2021 to comparatively analyse the dynamic relationship amongrenewable energy consumption,the value of agricultural production,gross domestic product(GDP),economic diversificationindex,urban population,the total water extraction for agricultural withdrawal,and trade balancein the Netherlands and South Africa.In the shortrun,renewable energy consumption was increased by the value of agricultural productionbut decreased by GDPin South Africa.In the longrun,renewable energy consumption and GDP increased the value of agricultural production,while the value of agricultural production also increased GDP in South Africa.However,in the Netherlands,there was no short-and long-run relationship betweenrenewable energy consumption and agricultural and economic development.The results revealedthat there was a short-and long-run relationship in South Africa.Moreover,in the Netherlands,the adjustment speed was-1.46 forrenewable energy consumption with an error correction of 0.68 a(8.22 months).In South Africa,the adjustment speedwas-1.28 forrenewable energy consumption with an error correction of 0.78 a(9.38 months).Therefore,compared to South Africa,renewable energy consumptionin the Netherlands takes less time to return to balance after a shock.Thesefindings signify different trajectories on sectoral and economic transition initiatives spurred usingrenewable energy between the Netherlands and South Africa.Policy relating to initiatives such as“agro-energy communities”in Global South countries such as South Africa should be emphasised to promote the use of renewable energy in the agricultural sector.展开更多
Regolith,widely distributed on the Earth’s surface,constitutes a significant compartment of the Critical Zone,resulting from intricate interactions among the atmosphere,lithosphere,hydrosphere,and biosphere.Regolith ...Regolith,widely distributed on the Earth’s surface,constitutes a significant compartment of the Critical Zone,resulting from intricate interactions among the atmosphere,lithosphere,hydrosphere,and biosphere.Regolith formation critically influences nutrient release,soil production,and long-term climate regulation.Regolith development is governed by two primary processes:production and denudation.An urgent need exists to comprehensively understand these processes to refine our understanding of Critical Zone functions.This study investigates an in-situ regolith profile developed on granitic bedrock from a tropical region(Sanya,China).We conducted geochemical analyses,encompassing major,trace elements and mineralogical compositions as well as U-series isotopes,and applied the U-series disequilibrium method to investigate the formation history of this profile.Alternatively,dividing the regolith profile into sub-weathering zones provides a better explanation for the geochemical results,and a multi-stage model based on this subdivision effectively interprets the evolution of deep regolith.Utilizing this multi-stage model,regolith production rates is derived from the“gain and loss”model,ranging from 1.27±0.03 to 42.42±24.24 m/Ma.The production rates first increase from surface until a maximum rate is reached at the depth of∼160 cm and then decrease at further deeper horizons along the depth profile,and the variation of production rates follows a so-called“humped function”.This pioneering investigation into regolith production rates in the Chinese tropical region indicates that(1)the studied profile deviates from a steady state compared to the denudation rate derived from cosmogenic nuclides(^(10)Be_in-situ);(2)subdividing the deep profile based on geochemical data and U-series isotopic activity ratios is imperative for accurately determining regolith production rates;and(3)the combination of U-series disequilibrium and cosmogenic nuclides robustly evaluates the quantitative evolution state of regolith over long time scales.展开更多
Background:Lung cancer is the leading cause of cancer-related mortality,and while low-dose computed tomography screening may reduce mortality,emerging prognostic models show superior discriminative efficacy compared t...Background:Lung cancer is the leading cause of cancer-related mortality,and while low-dose computed tomography screening may reduce mortality,emerging prognostic models show superior discriminative efficacy compared to age-and smoking history-based screening.However,further research is needed to assess their reliability in predicting lung cancer risk in high-risk patients.Methods:This study evaluated the predictive performance and quality of existing lung cancer prognostic models through a systematic review and meta-analysis.A comprehensive search was conducted in PubMed,Cochrane,Web of Science,CNKI,and Wanfang for articles published between January 1,2000,and February 13,2025,identifying population-basedmodels incorporating all available modeling data.Results:Among 72 analyzed studies,models were developed from Asian(28 studies,including 23 Chinese cohorts)and European/American(48 studies)populations,with only 6 focusing on nonsmokers.Twenty-one models included genetic markers,15 used clinical factors,and 40 integrated epidemiological predictors.Although 37 models underwent external validation,only 4 demonstrated minimal bias and clinical applicability.A meta-analysis of 11 repeatedly validated models revealed calibration and discrimination,though some lacked calibration data.Conclusions:Few lung cancer prognostic models exist for nonsmokers.Most models exhibit poor predictive performance in external validations,with significant bias and limited application scope.Widespread external validation,standardized model development,and reporting techniques are needed to accurately identify high-risk individuals and ensure applicability across diverse populations.展开更多
基金funded by the Major National Science and Technology Project for Deep Earth of China(Grant No.2024ZD1003805)the National Natural Science Foundation of China(Grant Nos.52311530070 and 52004015).
文摘Rock damage significantly affects coupled thermo-hydro-mechanical(THM)behavior in deep geothermal exploitation through changing thermal and hydrological properties of rocks.For this,a thermo-hydro-mechanical-damage(THMD)coupled model was developed to describe the coupling between rock damage and mechanical,fluid flow and heat transfer fields.The model considers rock heterogeneity,and incorporates the Mohr-Coulomb failure criterion and the maximum tensile stress criterion to evaluate shear and tensile damage.This numerical modeling methodology was first verified against analytical solutions and experimental results,and was then used to simulate the THMD coupling behavior in deep geothermal exploitation.A coupled numerical model was set up to simulate the geothermal fluids extraction and re-injection process in a reservoir at 1 km depth over a 7-year period.Rock damage was found to accelerate the propagation of cold fronts away from the injection well,and have a distinct effect on the performance of geothermal exploitation.When the rock damage was considered,the field injectivity increases by 8.4 times,the range of cooled regions increases by 18.6 times,and the vertical deformation changes by 1.2 times after 7 years of geothermal operations,compared to the scenario where it was not considered.Parametric studies have suggested that thermal contraction dominates the rock damage evolution,and that thermal-induced rock damage only occurs at a sufficiently large temperature difference between fluids injected and the reservoir.This work underscores the importance of accurately accounting for the damage effect on reservoir response during fluid injection activities that cause significant cooling of reservoir rocks.
基金partial support from the Living Circular Labels project,funded by the Taskforce for Applied Research SIA’s KIEM programme(No.CIE.06.007)in the Netherlands。
文摘By leveraging the unique qualities of microorganisms,engineered living materials(ELMs)offer functional and economic advantages in everyday applications along with notable ecological benefits.This study contributes to the growing field of biodesign by examining the potential of Flavobacteria for thermochromic ELMs.Many Flavobacteria,commonly found in marine environments,produce iridescent structural colorations as their colonies expand on semi-solid surfaces through gliding motility.In this study,we analyzed the effects of temperature variations on flavobacterium Cellulophaga lytica PLY A 2,characterizing distinct changes in colony growth and iridescent colorations at a macroscopic and microscopic scale.Using scanning electron microscopy,we investigated the relationship between iridescent color and the underlying cell-based optical structures.By providing insights into the temperature-responsive behavior of Flavobacteria,our findings highlight their potential for future thermochromic ELMs-with applications ranging from sustainable food packaging to smart textiles-while encouraging further characterization studies within biodesign research.
文摘Background In patients with coronary artery disease,age is of known significance in predicting outcomes.Data on clinical outcomes in patients≥85 years undergoing percutaneous coronary intervention(PCI)remain scarce.The study aim was to determine clinical characteristics,risk of adverse cardiovascular events,and mortality in patients aged≥85 years compared to those aged<85 undergoing PCI.Methods In this retrospective study,data were obtained from the nationwide Netherlands Heart Registration on patients undergoing PCI between January 1st,2017 and January 1st,2021.The primary endpoint was all-cause mortality at long-term followup.Results A total of 155,683 patients underwent PCI,of which 100,209(64.4%)acute coronary syndrome cases.Compared to patients aged<85 years,patients aged≥85 were more often female and showed a higher number of cardiovascular comorbidities,including impaired left ventricle ejection fraction and reduced kidney function.Mortality at short-term and long-term follow-up were significantly higher in those aged≥85(P<0.001).Patients aged≥85 were more likely to have a myocardial infarction within 30 days following the index intervention(0.9%vs.0.7%;P=0.024),though they less often underwent revascularization at longterm follow-up compared to patients aged<85(P<0.001).Conclusions The elderly(≥85 years)patient requiring PCI carries an extensive cardiovascular risk profile,translating in significant risk of recurrent cardiovascular events and increased mortality rate.Clinicians should carefully weigh perceived risks and potential benefits in the individual patient,considering the patients’age,cardiovascular risk profile,and associated risk of morbidity and mortality.
文摘非常规突发事件下,网络亲社会行为是帮助整合资源、恢复现实世界秩序的重要渠道。研究探究风险情境下风险感知是否会驱动人们更倾向于做出网络亲社会行为及其如何进一步影响非常规突发事件的走向。研究1采用问卷法,结合恐惧管理理论,验证了风险感知经由本体安全感对网络亲社会行为的影响以及健康自我效能感的调节作用;研究2采用基于主体的建模技术(agent based model, ABM)建模预测了网络亲社会行为通过调节医疗资源有效分配,有效减少疫情峰值人数、缩短疫情持续时间。研究拓展了对网络亲社会行为动因的理解以及对影响非常规突发事件走向的预测,启示人们通过增进网络亲社会行为对风险事件施加正向的影响。
基金supported by an intramural proof of concept grant of the NCT Heidelberg.
文摘Background The potential of exercise as a concurrent therapy for actively treated primary tumors has been suggested by emerging preclinical and observational studies.However,clinical trials regarding this question are scarce.Therefore,we conducted a randomized controlled trial investigating the effects of aerobic or resistance exercise concomitant to neoadjuvant chemotherapy(NACT)on tumor size.Methods In the BENEFIT study(German title:Bewegung bei neoadjuvanter chemotherapie zur verbesserung der fitness),patients with breast cancer scheduled for NACT were randomly assigned to supervised resistance training(RT,n=60)or aerobic training(AT,n=60)twice weekly during NACT or to a waitlist control group(WCG,n=60).The primary outcome,“change in tumor size”,as well as the secondary clinical outcomes pathologic complete response(pCR),type of surgery(breast conserving/mastectomy),axillary lymph node dissection(ALND,yes/no),premature discontinuation of chemotherapy(yes/no),and relative dose intensity(RDI)were derived from clinical records.Due to the highly skewed distribution,the primary outcome was categorized.Multiple(ordinal)logistic regression analyses were performed.Results Overall,there was no significant difference in post-intervention tumor size between RT or AT and WCG.However,there was a significant effect modification by hormone receptor(HR)status(P_(interaction)=0.030).Among patients with HR+tumors,results suggest a beneficial effect of AT on tumor shrinkage(odds ratio(OR)=2.37,95%confidence interval(95%CI):0.97‒5.78),on pCR(OR=3.21,95%CI:0.97‒10.61);and on ALND(OR=3.76,95%CI:0.78‒18.06)compared to WCG.The effects of RT were slightly less pronounced.For HR−subtypes,beneficial effects on RDI were found for AT(OR=3.71,95%CI:1.20‒11.50)and similarly for RT(OR=2.58,95%CI:0.88‒7.59).Both AT and RT had favorable effects on premature discontinuation of chemotherapy(OR(no vs.yes)=2.34,95%CI:1.10‒5.06),irrespective of tumor receptor status.Conclusion While there was no significant effect on the primary outcome in the overall group,aerobic and resistance exercise concomitant to NACT seem to beneficially affect tumor shrinkage and pCR,reduce the need for ALND among patients with HR+breast cancers,and prevent low RDI among patients with HR–breast cancers.These results warrant confirmation in further trials.
文摘Cryotherapy is a treatment modality that uses extreme cold to destroy unwanted tissue through both immediate and delayed cellular injury.This therapy is increasingly being adopted across various medical specialties due to its minimally invasive nature and technological advancements that have been made.In the esophagus,cryotherapy is particularly utilized for the management of Barrett esophagus.It has been demonstrated to be effective and safe with potential benefits,such as a reduction in pain,over radiofrequency ablation.Additionally,it might offer a valuable alternative for patients unresponsive to radiofrequency ablation.Cryotherapy is applied for other conditions as well,including esophageal squamous cell neoplasia and malignant dysphagia.More research is needed to gain understanding of the utility in these conditions.Interestingly,cryotherapy has shown the ability to enhance the host’s immune response in reaction to antigens left in situ after treatment.While preclinical data have demonstrated promising results,the immune response is often insufficient to induce tumor regression in the clinical setting.Therefore,there is growing interest in the combination of cryotherapy and immunotherapy where ablation creates an antigen depot,and the immune system is subsequently stimulated.This combination holds promise for the future and potentially opens new doors for a breakthrough in cancer treatment.
文摘This research investigates the influence of indoor and outdoor factors on photovoltaic(PV)power generation at Utrecht University to accurately predict PV system performance by identifying critical impact factors and improving renewable energy efficiency.To predict plant efficiency,nineteen variables are analyzed,consisting of nine indoor photovoltaic panel characteristics(Open Circuit Voltage(Voc),Short Circuit Current(Isc),Maximum Power(Pmpp),Maximum Voltage(Umpp),Maximum Current(Impp),Filling Factor(FF),Parallel Resistance(Rp),Series Resistance(Rs),Module Temperature)and ten environmental factors(Air Temperature,Air Humidity,Dew Point,Air Pressure,Irradiation,Irradiation Propagation,Wind Speed,Wind Speed Propagation,Wind Direction,Wind Direction Propagation).This study provides a new perspective not previously addressed in the literature.In this study,different machine learning methods such as Multilayer Perceptron(MLP),Multivariate Adaptive Regression Spline(MARS),Multiple Linear Regression(MLR),and Random Forest(RF)models are used to predict power values using data from installed PVpanels.Panel values obtained under real field conditions were used to train the models,and the results were compared.The Multilayer Perceptron(MLP)model was achieved with the highest classification accuracy of 0.990%.The machine learning models used for solar energy forecasting show high performance and produce results close to actual values.Models like Multi-Layer Perceptron(MLP)and Random Forest(RF)can be used in diverse locations based on load demand.
基金funded by the INTER program and cofunded by the Fond National de la Recherche,Luxembourg(FNR)and the Fund for Scientific Research-FNRS,Belgium(F.R.S-FNRS),T.0233.20-‘Sustainable Residential Densification’project(SusDens,2020–2024).
文摘The impact of different global and local variables in urban development processes requires a systematic study to fully comprehend the underlying complexities in them.The interplay between such variables is crucial for modelling urban growth to closely reflects reality.Despite extensive research,ambiguity remains about how variations in these input variables influence urban densification.In this study,we conduct a global sensitivity analysis(SA)using a multinomial logistic regression(MNL)model to assess the model’s explanatory and predictive power.We examine the influence of global variables,including spatial resolution,neighborhood size,and density classes,under different input combinations at a provincial scale to understand their impact on densification.Additionally,we perform a stepwise regression to identify the significant explanatory variables that are important for understanding densification in the Brussels Metropolitan Area(BMA).Our results indicate that a finer spatial resolution of 50 m and 100 m,smaller neighborhood size of 5×5 and 3×3,and specific density classes—namely 3(non-built-up,low and high built-up)and 4(non-built-up,low,medium and high built-up)—optimally explain and predict urban densification.In line with the same,the stepwise regression reveals that models with a coarser resolution of 300 m lack significant variables,reflecting a lower explanatory power for densification.This approach aids in identifying optimal and significant global variables with higher explanatory power for understanding and predicting urban densification.Furthermore,these findings are reproducible in a global urban context,offering valuable insights for planners,modelers and geographers in managing future urban growth and minimizing modelling.
基金supported by the National Natural Science Foundation of China(Nos.42377296 and 42107141)the National Key Research and Development Program of China(Nos.2023YFD1901402 and 2023YFD1901105)the Fundamental Research Funds for the Central Universities,China(No.YDZX2025046).
文摘Plant growth-promoting rhizobacteria(PGPR)have been widely used for the promotion of plant performance.Predatory protists can influence the taxonomic and functional composition of rhizosphere bacteria.However,research on the impact of the interaction between protist and PGPR on plant performance remains at a very early stage.Here,we examined the impacts of individual inoculation of protist(Colpoda inflata,Dimastigella trypaniformis,or Vermamoeba vermiformis)or the PGPR strain Bacillus velezensis SQR9 as well as the co-inoculation of the protist C.inflata and B.velezensis SQR9 on the growth of tomato plants.We found that all individual protists and Bacillus could promote plant growth compared to the control with no microbe inoculation,with the co-inoculation of C.inflata and B.velezensis SQR9 achieving the greatest performance,including plant height,fresh weight,and dry weight.Different protists harbored distinct rhizosphere bacterial communities,with the co-inoculation of protist and Bacillus resulting in the lowest bacterial diversity and driving significant changes in community structure and composition,particularly by increasing the relative abundance of Proteobacteria.Random forest model highlighted Cellvibrio as the most important bacterial predictor of plant growth,which was enriched after protist inoculation,especially after the mixed inoculation of protist and Bacillus.We further found that bacterial functional genes of nitrogen metabolism were the key determinants of plant growth.These results indicate that the interaction between protists and Bacillus can support plant growth by reshaping rhizosphere bacterial community composition and function.Understanding the interaction mechanisms between protist and PGPR is crucial for their effective utilization in sustainable agriculture.
基金Supported by The Science and Technology Innovation 2030-Major Project,No.2021ZD0140406.
文摘BACKGROUND Partial hepatectomy continues to be the primary treatment approach for liver tumors,and post-hepatectomy liver failure(PHLF)remains the most critical lifethreatening complication following surgery.AIM To comprehensively review the PHLF prognostic models developed in recent years and objectively assess the risk of bias in these models.METHODS This review followed the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guideline.Three databases were searched from November 2019 to December 2022,and references as well as cited literature in all included studies were manually screened in March 2023.Based on the defined inclusion criteria,articles on PHLF prognostic models were selected,and data from all included articles were extracted by two independent reviewers.The PROBAST was used to evaluate the quality of each included article.RESULTS A total of thirty-four studies met the eligibility criteria and were included in the analysis.Nearly all of the models(32/34,94.1%)were developed and validated exclusively using private data sources.Predictive variables were categorized into five distinct types,with the majority of studies(32/34,94.1%)utilizing multiple types of data.The area under the curve for the training models included ranged from 0.697 to 0.956.Analytical issues resulted in a high risk of bias across all studies included.CONCLUSION The validation performance of the existing models was substantially lower compared to the development models.All included studies were evaluated as having a high risk of bias,primarily due to issues within the analytical domain.The progression of modeling technology,particularly in artificial intelligence modeling,necessitates the use of suitable quality assessment tools.
基金Sahand University of Technology and Utrecht University for the project's financial supportthe Iran Nanotechnology Initiative Council for their additional financial assistance。
文摘A promising structured catalyst was developed through proper coating of boron-modified ZSM-5 using SiO_(2) and Al_(2)O_(3)-containing binders to investigate catalytic performance as well as mechanical stability of the catalyst in a monolithic reactor.The reference and boron-modified ZSM-5 catalysts were synthesized by hydrothermal route.The adherence strength of catalyst samples was characterized using ultrasonic vibration method and FESEM analysis.A series of comparative performance tests were also conducted in two reactors,including monolithic and extruded catalysts for the production of propylene from methanol at atmospheric pressure,reaction temperatures of 500℃,and methanol weight hourly space velocity(WHSV)of 1.5 h^(-1).Initial findings demonstrate that applying the B-modified ZSM-5zeolite in a monolith reactor increased propylene selectivity by about 26%compared to the conventional extruded ZSM-5 catalyst.Moreover,silica bonded to the B-ZSM-5 catalyst in the monolithic reactor,owning sufficient adhesion properties;the proposed catalyst showed the best catalytic performance,with not only a high propylene selectivity(58.5%)but also a large propylene/ethylene(P/E)ratio(8.6).The findings attained in this work would be useful in the production of new efficient catalysts based on a zeolite-coated honeycomb monolith in the methanol-to-propylene process.
基金research supported wholly by the National Research Foundation (NRF) of South Africathe Dutch Research Council (NWO) Project (UID 129352)
文摘The use ofrenewable energyisan important way toachieve sustainable agriculturalandeconomic development.However,there are differences in accessto renewable energy between the Global North and Global South.This study utilisedan autoregressive distributed lag-error correctionmodel and thedata spanning from 1991to 2021 to comparatively analyse the dynamic relationship amongrenewable energy consumption,the value of agricultural production,gross domestic product(GDP),economic diversificationindex,urban population,the total water extraction for agricultural withdrawal,and trade balancein the Netherlands and South Africa.In the shortrun,renewable energy consumption was increased by the value of agricultural productionbut decreased by GDPin South Africa.In the longrun,renewable energy consumption and GDP increased the value of agricultural production,while the value of agricultural production also increased GDP in South Africa.However,in the Netherlands,there was no short-and long-run relationship betweenrenewable energy consumption and agricultural and economic development.The results revealedthat there was a short-and long-run relationship in South Africa.Moreover,in the Netherlands,the adjustment speed was-1.46 forrenewable energy consumption with an error correction of 0.68 a(8.22 months).In South Africa,the adjustment speedwas-1.28 forrenewable energy consumption with an error correction of 0.78 a(9.38 months).Therefore,compared to South Africa,renewable energy consumptionin the Netherlands takes less time to return to balance after a shock.Thesefindings signify different trajectories on sectoral and economic transition initiatives spurred usingrenewable energy between the Netherlands and South Africa.Policy relating to initiatives such as“agro-energy communities”in Global South countries such as South Africa should be emphasised to promote the use of renewable energy in the agricultural sector.
基金supported by The National Natural Science Foundation of China(42303060)The China Scholarship Council(CSC,201906250131).
文摘Regolith,widely distributed on the Earth’s surface,constitutes a significant compartment of the Critical Zone,resulting from intricate interactions among the atmosphere,lithosphere,hydrosphere,and biosphere.Regolith formation critically influences nutrient release,soil production,and long-term climate regulation.Regolith development is governed by two primary processes:production and denudation.An urgent need exists to comprehensively understand these processes to refine our understanding of Critical Zone functions.This study investigates an in-situ regolith profile developed on granitic bedrock from a tropical region(Sanya,China).We conducted geochemical analyses,encompassing major,trace elements and mineralogical compositions as well as U-series isotopes,and applied the U-series disequilibrium method to investigate the formation history of this profile.Alternatively,dividing the regolith profile into sub-weathering zones provides a better explanation for the geochemical results,and a multi-stage model based on this subdivision effectively interprets the evolution of deep regolith.Utilizing this multi-stage model,regolith production rates is derived from the“gain and loss”model,ranging from 1.27±0.03 to 42.42±24.24 m/Ma.The production rates first increase from surface until a maximum rate is reached at the depth of∼160 cm and then decrease at further deeper horizons along the depth profile,and the variation of production rates follows a so-called“humped function”.This pioneering investigation into regolith production rates in the Chinese tropical region indicates that(1)the studied profile deviates from a steady state compared to the denudation rate derived from cosmogenic nuclides(^(10)Be_in-situ);(2)subdividing the deep profile based on geochemical data and U-series isotopic activity ratios is imperative for accurately determining regolith production rates;and(3)the combination of U-series disequilibrium and cosmogenic nuclides robustly evaluates the quantitative evolution state of regolith over long time scales.
基金funded by theGuangzhou Municipal Science and Tech-nology Bureau(No.2023A03J0507).
文摘Background:Lung cancer is the leading cause of cancer-related mortality,and while low-dose computed tomography screening may reduce mortality,emerging prognostic models show superior discriminative efficacy compared to age-and smoking history-based screening.However,further research is needed to assess their reliability in predicting lung cancer risk in high-risk patients.Methods:This study evaluated the predictive performance and quality of existing lung cancer prognostic models through a systematic review and meta-analysis.A comprehensive search was conducted in PubMed,Cochrane,Web of Science,CNKI,and Wanfang for articles published between January 1,2000,and February 13,2025,identifying population-basedmodels incorporating all available modeling data.Results:Among 72 analyzed studies,models were developed from Asian(28 studies,including 23 Chinese cohorts)and European/American(48 studies)populations,with only 6 focusing on nonsmokers.Twenty-one models included genetic markers,15 used clinical factors,and 40 integrated epidemiological predictors.Although 37 models underwent external validation,only 4 demonstrated minimal bias and clinical applicability.A meta-analysis of 11 repeatedly validated models revealed calibration and discrimination,though some lacked calibration data.Conclusions:Few lung cancer prognostic models exist for nonsmokers.Most models exhibit poor predictive performance in external validations,with significant bias and limited application scope.Widespread external validation,standardized model development,and reporting techniques are needed to accurately identify high-risk individuals and ensure applicability across diverse populations.
