Prenylated isoflavonoids with anti-inflammatory activities from the twigs and leaves of Maclura fruticosa.

Six new prenylated isoflavonoids, named maccosas A-F (1-6), together with ten known prenylated isoflavonoids (7-16) were isolated from the twigs and leaves of Maclura fruticosa. Compounds were isolated by various column chromatographic methods including silica gel, sephadex LH-20, and semi-preparative HPLC. Their structures were elucidated by a combination of 1D and 2D NMR techniques, mass spectrometry, and comparison of their spectral data with those in the literature.

Discovery of potential small molecular SARS-CoV-2 entry blockers targeting the spike protein.

An epidemic of pneumonia caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is spreading worldwide. SARS-CoV-2 relies on its spike protein to invade host cells by interacting with the human receptor protein Angiotensin-Converting Enzymes 2 (ACE2). Therefore, designing an antibody or small-molecular entry blockers is of great significance for virus prevention and treatment.

Initiation Condition of Hemodialysis Is Independently Associated with All-Cause Mortality in Maintenance Hemodialysis Patients: A Retrospective Study.

Background: Despite the progression of dialysis techniques,  the mortality of hemodialysis (HD) patients is still high in China. Here, a retrospective study was performed to investigate the neglected risk factors of all-cause mortality during maintenance HD (MHD).

Methods: We investigated 117 MHD patients who died between 2011 and 2016 in the Second Xiangya Hospital of Central South University HD center.

Confidence intervals construction for difference of two means with incomplete correlated data.

Background: Incomplete data often arise in various clinical trials such as crossover trials, equivalence trials, and pre and post-test comparative studies. Various methods have been developed to construct confidence interval (CI) of risk difference or risk ratio for incomplete paired binary data. But, there is little works done on incomplete continuous correlated data.

A new framework of statistical inferences based on the valid joint sampling distribution of the observed counts in an incomplete contingency table.

Some existing confidence interval methods and hypothesis testing methods in the analysis of a contingency table with incomplete observations in both margins entirely depend on an underlying assumption that the sampling distribution of the observed counts is a product of independent multinomial/binomial distributions for complete and incomplete counts. However, it can be shown that this independency assumption is incorrect and can result in unreliable conclusions because of the under-estimation of the uncertainty. Therefore, the first objective of this paper is to derive the valid joint sampling distribution of the observed counts in a contingency table with incomplete observations in both margins.

Confidence interval construction for the difference between two correlated proportions with missing observations.

Under the assumption of missing at random, eight confidence intervals (CIs) for the difference between two correlated proportions in the presence of incomplete paired binary data are constructed on the basis of the likelihood ratio statistic, the score statistic, the Wald-type statistic, the hybrid method incorporated with the Wilson score and Agresti-Coull (AC) intervals, and the Bootstrap-resampling method. Extensive simulation studies are conducted to evaluate the performance of the presented CIs in terms of coverage probability and expected interval width. Our empirical results evidence that the Wilson-score-based hybrid CI and the Wald-type CI together with the constrained maximum likelihood estimates perform well for small-to-moderate sample sizes in the sense that (i) their empirical coverage probabilities are quite close to the prespecified confidence level, (ii) their expected interval widths are shorter, and (iii) their ratios of the mesial non-coverage to non-coverage probabilities lie in interval [0.

Confidence-interval construction for rate ratio in matched-pair studies with incomplete data.

Matched-pair design is often used in clinical trials to increase the efficiency of establishing equivalence between two treatments with binary outcomes. In this article, we consider such a design based on rate ratio in the presence of incomplete data. The rate ratio is one of the most frequently used indices in comparing efficiency of two treatments in clinical trials.

[Study of tacrolimus intranasal treatment for allergic asthma in mice].

Objective: To explore the efficacy of intranasal treatment by immunosuppressant tacrolimus for allergic asthma and its mechanism in mice.

Methods: 24 female BALB/c mice were randomly divided into 4 groups: group A (negative control), group B (model control), group C (low dose treatment), and group D (high dose treatment). Mice in group A were treated with saline (100 microl).

Homogeneity test of rate ratios in stratified matched-pair studies.

This paper investigates homogeneity test of rate ratios in stratified matched-pair studies on the basis of asymptotic and bootstrap-resampling methods. Based on the efficient score approach, we develop a simple and computationally tractable score test statistic. Several other homogeneity test statistics are also proposed on the basis of the weighted least-squares estimate and logarithmic transformation.

Confidence interval construction for proportion ratio in paired studies based on hybrid method.

In this article, we consider confidence interval construction for proportion ratio in paired samples. Previous studies usually reported that score-based confidence intervals consistently outperformed other asymptotic confidence intervals for correlated proportion difference and ratio. However, score-based confidence intervals may not possess closed-form solutions and iterative procedures are therefore required.

A comparison of methods for the construction of confidence interval for relative risk in stratified matched-pair designs.

A stratified matched-pair study is often designed for adjusting a confounding effect or effect of different trails/centers/ groups in modern medical studies. The relative risk is one of the most frequently used indices in comparing efficiency of two treatments in clinical trials. In this paper, we propose seven confidence interval estimators for the common relative risk and three simultaneous confidence interval estimators for the relative risks in stratified matched-pair designs.