Objective To observe the expression of pancreatic K_(ATP) channels (Kir6.2/SUR1) in rats with chronic pancreatitis and explore the intervention of nateglinide on the changes.Methods Wistar rats were induced to suffer from chronic pancreatitis and then randomized into model group, nateglinide group and control group.Then OGTT of them were observed.RT-PCR was used to detect the expression of Kir6.2 and SUR1 mRNA, and western blot to detect the expression of Kir6.2 and SUR1 proteins.Results Model rats displayed impaired glucose tolerance (IGT).The expression of Kir6.2 and SUR1 in model group decreased significantly(P＜0.05), and nateglinide displayed up-reg-ulation to the expression in some degree.Conclusion The expression of pancreatic K_(ATP) channels in rats with chronic pancreatitis diminished, which might be the important mechanism of the development of pancreatogenic diabetes.Nateglinide can up-regulate the expression in some degree, which indicates that it may have latent effect of ameliorating the prognosis of patients with chronic pancreatitis.

Two-factor factorial design refers to the research involving two experimental factors and the number of the experimental groups equals to the product of the levels of the two experimental factors. In other words, it is the complete combination of the levels of the two experimental factors. The research subjects are randomly divided into the experimental groups. The two experimental factors are performed on the subjects at the same time, meaning that there is no order. The two experimental factors are equal during statistical analysis, that is to say, there is no primary or secondary distinction, nor nested relation. This article introduces estimation of sample size and testing power of quantitative data with two-factor factorial design.

Objective To investigate the protective effect of hydrogen-rich water (HRW) on radiation-induced hematopoietic stem and progenitor cells (HSPCs) injury.Methods Totally 32 C57BL/6 mice were randomly divided into four groups with 8 mice in each group,including control,HRW,radiation and radiation + HRW.Mice in HRW and radiation + HRW groups received 0.5 ml hydrogen-rich water per day by intragastric administration 5 min before irradiation until 7 d post-irradiation.Mice in other groups received 0.5 ml distilled water.Mice in radiation and radiation + HRW group were irradiated with 2 Gy of total body irradiation.Bone marrow cells were isolated at 15 d post-irradiation,and LSK cells were examined for the percentage of hematopoietic stem and progenitor cells,the ability of colony formation and reconstitution,reactive oxygen species (ROS) levels and cell apoptosis.Results Compared with radiation group,the percentages of hematopoietic progenitor cells and LSK cells,colony number of bone marrow cells were significantly increased in radiation + HRW group (t =-4.935,-7.898,5.488,P ＜ 0.05).An elevation of donor chimerism was also found in recipient mice administered HRW after competitive bone marrow transplantation (t =-12.769,P ＜ 0.05).Compared with radiation group,the ROS levels and cell apoptosis in LSK cells were significantly decreased (t =4.380,3.954,P ＜ 0.05).Conclusions Hydrogen-rich water exhibited a protective effect on radiation-induced HSPCs injury.

Research factors are a very important element in any research design. Research factors include experimental and non-experimental factors. The former is the general term used to describe the similar experimental conditions that researchers are interested in, while the latter are other factors that researchers have little interest in but may influence the result. This article mainly focuses on the following issues: the definition of research factors, the selection and arrangement of experimental factors and non-experimental factors, the interaction between research factors, the standardization of research factors and the common mistakes frequently made by researchers.

This article introduces the definition and sample size estimation of three special tests (namely, non-inferiority test, equivalence test and superiority test) for qualitative data with the design of one factor with two levels having a binary response variable. Non-inferiority test refers to the research design of which the objective is to verify that the efficacy of the experimental drug is not clinically inferior to that of the positive control drug. Equivalence test refers to the research design of which the objective is to verify that the experimental drug and the control drug have clinically equivalent efficacy. Superiority test refers to the research design of which the objective is to verify that the efficacy of the experimental drug is clinically superior to that of the control drug. By specific examples, this article introduces formulas of sample size estimation for the three special tests, and their SAS realization in detail.

Sample size estimation is necessary for any experimental or survey research. An appropriate estimation of sample size based on known information and statistical knowledge is of great significance. This article introduces methods of sample size estimation of difference test for data with the design of one factor with two levels, including sample size estimation formulas and realization based on the formulas and the POWER procedure of SAS software for quantitative data and qualitative data with the design of one factor with two levels. In addition, this article presents examples for analysis, which will play a leading role for researchers to implement the repetition principle during the research design phase.

ABSTRACT: Estimation of sample size and testing power is an important component of research design. This article introduced methods for sample size and testing power estimation of difference test for quantitative and qualitative data with the single-group design, the paired design or the crossover design. To be specific, this article introduced formulas for sample size and testing power estimation of difference test for quantitative and qualitative data with the above three designs, the realization based on the formulas and the POWER procedure of SAS software and elaborated it with examples, which will benefit researchers for implementing the repetition principle.

The research subject is the first key element of the three key elements in the research design. An appropriate selection of research subjects is crucial to the success of the research. This article summarizes the general principles for the selection of research subjects, the types and numbers of research subjects and the common mistakes that researchers tend to make in the selection of the research subjects. This article also provides the methodology suggestions for the selection of research subjects.

This article introduces the general concepts and methods of sample size estimation and testing power analysis. It focuses on parametric methods of sample size estimation, including sample size estimation of estimating the population mean and the population probability. It also provides estimation formulas and introduces how to realize sample size estimation manually and by SAS software.