miR-221/222/PUMA Axis Promotes Oral Squamous Cell Carcinoma Apoptosis

Background: To investigate the therapeutic activity of the miR-221/222 inhibitor against OSCC in vitro and in vivo. Materials and Methods: HSC3 and HSC6 were treated with miR-221/222 inhibitor and the empty vector respectively. After the recombinants were transfected into HSC3 and HSC6 with LipofectamineTM MAX, the expression of miR-221/222 and PUMA was analyzed by RT-PCR. The proliferation and migration of HSC3 and HSC6 were detected by CCK-8 assay and Wound-healing assay. Cell cycle and apoptosis were detected by flow cytometry. The effect of the miR-221/222 inhibitor was also assessed in OSCC xenografts in BALB/c-nu mice. Results: Transfection of the miR-221/222 inhibitor increased cell apoptosis and upregulated PUMA expression in OSCC cell lines HSC3 and HSC6 with the significantly reduced expression of miR-221 and miR-222. Furthermore, the miR-221/222 inhibitor suppressed cell growth and invasion and blocked the cell cycle at the G1 phase. Obvious anti-tumor activity was achieved in BALB/c-nu mice by treatment with the miR-221/222 inhibitor, together with the upregulation of PUMA protein in tumors retrieved from the mice. Conclusions: There was a significant inhibitory effect of the miR-221/222 inhibitor on the growth of OSCC both in vitro and in vivo, and there might be a regulatory loop between miR-221/222 and PUMA. These findings demonstrated that downregulation of miR-221/222 could induce cell apoptosis, and it might be considered as a candidate target for gene therapy of OSCC.

Comparison of Several Data Mining Methods in Credit Card Default Prediction

LightGBM is an open-source, distributed and high-performance GB framework built by Microsoft company. LightGBM has some advantages such as fast learning speed, high parallelism efficiency and high-volume data, and so on. Based on the open data set of credit card in Taiwan, five data mining methods, Logistic regression, SVM, neural network, Xgboost and LightGBM, are compared in this paper. The results show that the AUC, F1-Score and the predictive correct ratio of LightGBM are the best, and that of Xgboost is second. It indicates that LightGBM or Xgboost has a good performance in the prediction of categorical response variables and has a good application value in the big data era.

Optimization design of autofocusing metasurface for ultrasound wave application

In this paper,two optimized autofocusing metasurfaces(AFMs)with different desired focal distances are designed by using particle swarm optimization(PSO)algorithm.Based on the ffnite element simulation software COMSOL Multiphysics,the performance of ultrasound transducer(UT)with AFM at different design parameters in Airy distributions(r0,ω)and the bottom thickness(d)of AFM are simulated and analyzed.Based on the simulation data,the artiffcial neural network model is trained to describe the complex relationship between the design parameters of AFM and the performance parameters of UT.Then,the multiobjective optimization function for AFM is determined according to the desired performance parameters of UT,including focal position,lateral resolution,longitudinal resolution and absolute sound pressure.In order to obtain AFMs with the desired performance,PSO algorithm is adopted to optimize the design parameters of AFM according to the multiobjective optimization function,and two AFMs are optimized and fabricated.The experimental results well agree with the simulation and optimization results,and the optimized AFMs can achieve the desired performance.The fabricated AFM can be easily integrated with UT,which has great potential applications in wave ffeld modulation underwater,acoustic tweezers,biomedical imaging,industrial nondestructive testing and neural regulation.

The computational fluid dynamic modeling of downwash flow field for a six-rotor UAV

The downwash flow field of the multi-rotor unmanned aerial vehicle(UAV), formed by propellers during operation, has a significant influence on the deposition, drift and distribution of droplets as well as the spray width of the UAV for plant protection. To study the general characteristics of the distribution of the downwash airflow and simulate the static wind field of multi-rotor UAVs in hovering state, a 3 D full-size physical model of JF01-10 six-rotor plant protection UAV was constructed using Solid Works. The entire flow field surrounding the UAV and the rotation flow fields around the six rotors were established in UG software. The physical model and flow fields were meshed using unstructured tetrahedral elements in ANSYS software.Finally, the downwash flow field of UAV was simulated.With an increased hovering height, the ground effect was reduced and the minimum current velocity increased initially and then decreased. In addition, the spatial proportion of the turbulence occupied decreased. Furthermore, the appropriate operational hovering height for the JF01-10 is considered to be 3 m. These results can be applied to six-rotor plant protection UAVs employed in pesticide spraying and spray width detection.

Model migration for CFD and verification of a six-rotor UAV downwash

Currently,Computational Fluid Dynamics(CFD)has been used to investigate agricultural UAV downwash.However,the validations of CFD models are difficult to deal with.Current verification methods are to use either water-sensitive papers or wind-speed arrays,which could get wind distribution or speed only.In this study,model migration was used to develop and verify downwash CFD models.The basic idea is to try to use the results of a scaled-down drone to represent that of a real-used UAV.The CFD models of both a real-used six-rotor UAV,JF01-10,and a 1:10 scaled-down small drone were developed by ANSYS.Then,the scaled-down drone was utilized to conduct trials by particle image velocimetry(PIV),so that not only distribution and speed but also flowing direction of downwash could be obtained.Results indicated the relative error between the PIV tests and the CFD models of the small UAV was less than 12%,while that between the tests and the CFD models of JF01-10 was less than 34%.It could be indicated that model migration could reflect multiple downwash characteristics but should be optimized in some complex details.This study was a preliminary but fundamental attempt to investigate CFD modelling and validation of agricultural UAVs and provided a novel thinking of downwash verification.

Economic development level and urban settlement intentions of the new-generation migrants in China: direct or interaction effect?

Based on a theoretical framework,this paper uses a multilevel model to examine the factors that correlate with the settlement intentions of China’s new-generation migrants.The level of regional economic development exerts not only random effects,but also an interaction effect with social integration on urban settlement intentions.Economic factors,including household income and home ownership,have a significant positive correlation with settlement intentions,while social char-acteristics such as social integration and social identification also have a positive correlation with the settlement intentions of new-generation migrants.Moreover,family migration strategies,parental migration experiences,short migration dis-tances,and long migration durations enhance urban settlement intentions.The set-tlement intentions exhibit significant inter-group differences between the migrants born in the 1980s and in the 1990s.Differences in the effects of the determinants are observed between these group samples and the total sample.

China fertility survey 2017:design and implementation

This paper examines the design and the process used to carry out the China Fertility Survey 2017,a national representative survey that collected data on fertility desire,childbearing behavior,the use of childbearing services,and the determinants of childbearing behavior.The sampling method adopted was three-stage stratified probabilities proportional to size(PPS),and survey implementation made use of Computer Assisted Personal Interviewing(CAPI).CAPI played a significant role in survey design,last-stage sampling,interviewer training,face-to-face interviews,and questionnaire review and quality control.The survey results were compared with relevant data in the Integrated Management Information System for Population and Family Planning to check consistency.Ex post facto weighting was applied to correct sample structure bias.The process used to acquire accurate personal information is summarized.Suggestions based on consideration of sampling frame distortion by population mobility and other factors are put forward in the hope of improving similar sampling surveys in the future.

Changes in family structure in China:the impact of residence patterns and demographic factors

Based on census data from China,this paper uses SOCSIM microscopic simulation method to decompose the key factors of family transition into demographic and residence pattern factors.The former are further broken down into demographic inertia,fertility,mortality and marriage rate.The results indicate that the current demographic changes are relatively small and,thus,the small fluctuations caused by demographic changes contribute much less than residence pattern to the family transition.Among the demographic factors,demographic inertia and fertility have a greater effect on family transition and the impacts caused by fertility and marriage rate are consistent with the direction of the overall influence of demographic factors:increasing the proportion of single-person households,one-generation households,and two-generation households,and decreasing the proportion of three-generation or more households.In contrast,the effect of mortality rate was opposite to that of fertility rate,which increased the proportion of populations living in single-person,one-generation,and two-generation households,but the decreased the proportion of the population living in three-generation or more households.