A novel synthesized prodrug of gemcitabine based on oxygen-free radical sensitivity inhibited the growth of lung cancer cells

In the present study,we introduced the H2O2-sensitive thiazolidinone moiety at the 4th amino group of gemcitabine(GEM)to synthesize a new target compound named GEM-ZZQ,and then we confirmed its chemical structure by nuclear magnetic resonance spectroscopy.We further confirmed that GEM-ZZQ had a good chemical stability in different pH solutions in vitro and that it could be activated by H2O2 to release GEM.Pharmacodynamic studies revealed that the growth inhibition of human normal epithelial cells was weaker by GEM-ZZQ than by GEM treatment and that the inhibition of various lung cancer cell lines by GEM-ZZQ was similar to that of GEM.For the lung cancer cell lines that are resistant to the epidermal growth factor receptor(EGFR)-targeting inhibitor osimertinib,GEM-ZZQ showed less growth inhibition than GEM;however,GEM-ZZQ in combination with cisplatin showed better synergistic effects than GEM in the low-dose groups.In summary,we provided a new anti-cancer compound GEM-ZZQ for treating lung cancer by modifying the GEM structure.

Some Convergence Properties for Weighted Sums of Martingale Difference Random Vectors

Let{X_(ni),F_(ni);1≤i≤n,n≥1}be an array of R^(d)martingale difference random vectors and{A_(ni),1≤i≤n,n≥1}be an array of m×d matrices of real numbers.In this paper,the Marcinkiewicz-Zygmund type weak law of large numbers for maximal weighted sums of martingale difference random vectors is obtained with not necessarily finite p-th(1<p<2)moments.Moreover,the complete convergence and strong law of large numbers are established under some mild conditions.An application to multivariate simple linear regression model is also provided.

The Consistency of LSE Estimators in Partial Linear Regression Models under Mixing Random Errors

In this paper,we consider the partial linear regression model y_(i)=x_(i)β^(*)+g(ti)+ε_(i),i=1,2,...,n,where(x_(i),ti)are known fixed design points,g(·)is an unknown function,andβ^(*)is an unknown parameter to be estimated,random errorsε_(i)are(α,β)-mix_(i)ng random variables.The p-th(p>1)mean consistency,strong consistency and complete consistency for least squares estimators ofβ^(*)and g(·)are investigated under some mild conditions.In addition,a numerical simulation is carried out to study the finite sample performance of the theoretical results.Finally,a real data analysis is provided to further verify the effect of the model.

Almost Sure Convergence Theorem and Strong Stability for Weighted Sums of NSD Random Variables

In this paper, Kolmogorov-type inequality for negatively superadditive dependent （NSD） random variables is established. By using this inequality, we obtain the almost sure convergence for NSD sequences, which extends the corresponding results for independent sequences and negatively associated （NA） sequences. In addition, the strong stability for weighted sums of NSD random variables is studied.

Complete f-moment Convergence for Widely Orthant Dependent Random Variables and Its Application in Nonparametric Models

In this paper,we study the complete f-moment convergence for widely orthant dependent(WOD,for short)random variables.A general result on complete f-moment convergence for arrays of rowwise WOD random variables is obtained.As applications,we present some new results on complete f-moment convergence for WOD random variables.We also give an application to nonparametric regression models based onWOD errors by using the complete convergence that we established.Finally,the choice of the fixed design points and the weight functions for the nearest neighbor estimator are proposed,and a numerical simulation is provided to verify the validity of the theoretical result.

Complete Convergence and Complete Moment Convergence for Martingale Diference Sequence

In the paper,we investigate the complete convergence and complete moment convergence for the maximal partial sum of martingale diference sequence.Especially,we get the Baum–Katz-type Theorem and Hsu–Robbins-type Theorem for martingale diference sequence.As an application,a strong law of large numbers for martingale diference sequence is obtained.

Complete Moment Convergence for Arrays of Rowwise Widely Orthant Dependent Random Variables

In this paper, complete moment convergence for widely orthant dependent random vari- ables is investigated under some mild conditions. For arrays of rowwise widely orthant dependent random variables, the main results extend recent results on complete convergence to complete moment convergence. These results on complete moment convergence are shown to yield new results on complete integral convergence.

On Consistency of the Nearest Neighbor Estimator of the Density Function and Its Applications

In this paper, we mainly study the consistency of the nearest neighbor estimator of the density function based on asymptotically almost negatively associated samples. The weak consistency,strong consistency, uniformly strong consistency and the convergence rates are established under some mild conditions. As applications, we further investigate the strong consistency and the rate of strong consistency for hazard rate function estimator.