No expenditure difference among patients with liver cancer at stageⅠ-ⅣV:Findings from a multicenter cross-sectional study in China

Objective:The number of liver cancer patients in China accounts for more than half of the world.However,China currently lacks national,multicenter economic burden data,and meanwhile,measuring the differences among different subgroups will be informative to formulate corresponding policies in liver cancer control.Thus,the aim of the study was to measure the economic burden of liver cancer by various subgroups.Methods:A hospital-based,multicenter and cross-sectional survey was conducted during 2012・2014,covering 39 hospitals and 21 project sites in 13 provinces across China.The questionnaire covers clinical information,sociology,expenditure,and related variables.All expenditure data were reported in Chinese Yuan(CNY)using 2014 values.Results:A total of 2,223 liver cancer patients were enrolled,of whom 59.61%were late-stage cases(III-IV),and 53.8%were hepatocellular carcinoma.The average total expenditure per liver cancer patient was estimated as 53,220 CNY,including 48,612 CNY of medical expenditures(91.3%)and 4,608 CNY of non-medical expenditures(8.7%).The average total expenditures in stage I,H,m and stage IV were 52,817 CNY,50,877 CNY,50,678 CNY and 54,089 CNY(P>0.05),respectively.Non-medical expenditures including additional meals,additional nutrition care,transportation,accommodation and hired informal nursing were 1,453 CNY,839 CNY,946 CNY,679 CNY and 200 CNY,respectively.The one-year out-of-pocket expenditure of a newly diagnosed patient was 24,953 CNY,and 77.2%of the patients suffered an unmanageable financial burden.Multivariate analysis showed that overall expenditure differed in almost all subgroups(P<0.05),except for sex,clinical stage,and pathologic type.Conclusions:There was no difference in treatment expenditure for liver cancer patients at different clinical stages,which suggests that maintaining efforts on treatment efficacy improvement is important but not enough.To fiirtherly reduce the overall economic burden from liver cancer,more effort should be given to primary and secondary prevention strategies.

Valence modulated nickel oxynitride network as integrated bifunctional electrodes for enhanced energy storage

As promising electrode materials,transition metal oxides have attracted considerable attention owing to their excellent performance in electrochemical energy storage.However,their poor conductivity and fragile structure limit their practical application.In this study,a binder-free nickel oxide/oxynitride network(NiON WS)bifunctional electrodes with cation multivalent states that exhibit high energy storage performance were synthesized for the first time.The massive active sites,high specific surface areas,and multiple cation valence states of NiON WS were advantageous for electrochemical redox reaction during its application in supercapacitors(1283.5 mF cm^(-2))and lithium-ion batteries(1345.0 mA h g^(-1)).Particularly,the NiON WS based flexible asymmetric SCs exhibit excellent capacitance and energy densities.First-principle calculations were employed to study the mechanism of the electrochemical performance improvement of NiON WS.This study demonstrates the potential of transition metal oxides electrode with high capacity and activity for electrochemical energy storage and conversion.

Inflammation and tumor progression:signaling pathways and targeted intervention

Cancer development and its response to therapy are regulated by inflammation,which either promotes or suppresses tumor progression,potentially displaying opposing effects on therapeutic outcomes.Chronic inflammation facilitates tumor progression and treatment resistance,whereas induction of acute inflammatory reactions often stimulates the maturation of dendritic cells(DCs)and antigen presentation,leading to anti-tumor immune responses.In addition,multiple signaling pathways,such as nuclear factor kappa B(NF-kB),Janus kinase/signal transducers and activators of transcription(JAK-STAT),toll-like receptor(TLR)pathways,cGAS/STING,and mitogen-activated protein kinase(MAPK);inflammatory factors,including cytokines(e.g.,interleukin(IL),interferon(IFN),and tumor necrosis factor(TNF)-a),chemokines(e.g.,C-C motif chemokine ligands(CCLs)and C-X-C motif chemokine ligands(CXCLs)),growth factors(e.g.,vascular endothelial growth factor(VEGF),transforming growth factor(TGF)-P),and inflammasome;as well as inflammatory metabolites including prostaglandins,leukotrienes,thromboxane,and specialized proresolving mediators(SPM),have been identified as pivotal regulators of the initiation and resolution of inflammation.Nowadays,local irradiation,recombinant cytokines,neutralizing antibodies,small-molecule inhibitors,DC vaccines,oncolytic viruses,TLR agonists,and SPM have been developed to specifically modulate inflammation in cancer therapy,with some of these factors already undergoing clinical trials.Herein,we discuss the initiation and resolution of inflammation,the crosstalk between tumor development and inflammatory processes.We also highlight potential targets for harnessing inflammation in the treatment of cancer.

Numerical simulation of debris-removal trajectories on the transport mirrors in high-power laser systems

In high-power laser systems(HPLSs), understanding debris-removal trajectories is important in eliminating debris from the surfaces of transport mirrors online and keeping other optical components free from contamination. NS equations, the RNG k–ε model and the discrete phase model of the Euler–Lagrange method are used to conduct numerical simulations on the trajectories of contaminant particles of different sizes and types on the mirror surface using Fluent commercial software. A useful device is fabricated based on the simulation results. This device can capture and collect debris from the mirror surface online. Consequently, the effect of debris contamination on other optical components is avoided,cleaning time is shortened, and ultimately, the cleanliness of the mirrors in HPLSs is ensured.

Radiation model of a xenon flash lamp in a laser amplifier pump cavity

Understanding the radiation model of a flash lamp is essential for the reflector design of a laser amplifier. Reflector design often involves several simplifying assumptions, like a point or Lambertian source; either of these assumptions may lead to significant errors in the output distribution. In practice, source non-idealities usually result in sacrificing the amplifier's gain coefficient. We propose a novel test technique for attaining the xenon flash lamp absolute spectral intensity at various angles of view, and then accurately predict radiation distributions and generate the reflector shape. It is shown that due to the absorption of emitted radiation by the lamp itself, the behavior of the radiation model at various wavelengths is different. Numerical results of xenon plasma absorption coefficient were compared with the measured data. A reasonable agreement was obtained for the absorption coefficient parameters. Thus, this work provides a useful analytical tool for the engineering design of laser amplifier reflectors using xenon flash lamps as pumps.

Preparation and optimization of freestanding GaN using low-temperature GaN layer

In this work,a method to acquire freestanding GaN by using low temperature(LT)-GaN layer was put forward.To obtain porous structure and increase the crystallinity,LT-GaN layers were annealed at high temperature.The morphology of LTGaN layers with different thickness and annealing temperature before and after annealing was analyzed.Comparison of GaN films using different LT-GaN layers was made to acquire optimal LT-GaN process.According to HRXRD and Raman results,GaN grown on 800 nm LT-GaN layer which was annealed at 1090℃ has good crystal quality and small stress.The GaN film was successfully separated from the substrate after cooling down.The self-separation mechanism of this method was discussed.Cross-sectional EBSD mapping measurements were carried out to investigate the effect of LT-buffer layer on improvement of crystal quality and stress relief.The optical property of the obtained freestanding GaN film was also determined by PL measurement.

Comparison of nomogram and machine-learning methods for predicting the survival of non-small cell lung cancer patients

Background:Most patients with advanced non-small cell lung cancer(NSCLC)have a poor prognosis.Predicting overall survival using clinical data would benefit cancer patients by allowing providers to design an optimum treatment plan.We compared the performance of nomograms with machine-learning models at predicting the overall survival of NSCLC patients.This comparison benefits the development and selection of models during the clinical decision-making process for NSCLC patients.Methods:Multiple machine-learning models were used in a retrospective cohort of 6586 patients.First,we modeled and validated a nomogram to predict the overall survival of NSCLC patients.Subsequently,five machine-learning models(logistic regression,random forest,XGBoost,decision tree,and light gradient boosting machine)were used to predict survival status.Next,we evaluated the performance of the models.Finally,the machine-learning model with the highest accuracy was chosen for comparison with the nomogram at predicting survival status by observing a novel performance measure:time-dependent prediction accuracy.Results:Among the five machine-learning models,the accuracy of random forest model outperformed the others.Compared with the nomogram for time-dependent prediction accuracy with a follow-up time ranging from 12 to 60 months,the prediction accuracies of both the nomogram and machinelearning models changed as time varied.The nomogram reached a maximum prediction accuracy of 0.85 in the 60th month,and the random forest algorithm reached a maximum prediction accuracy of 0.74 in the 13th month.Conclusions:Overall,the nomogram provided more reliable prognostic assessments of NSCLC patients than machine-learning models over our observation period.Although machine-learning methods have been widely adopted for predicting clinical prognoses in recent studies,the conventional nomogram was competitive.In real clinical applications,a comprehensive model that combines these two methods may demonstrate superior capabilities.