A systematic review of the mechanism of action and potential medicinal value of codonopsis pilosula in diseases.

As a traditional Chinese medicinal herb with a long history, Codonopsis pilosula (CP) has attracted much attention from the medical community in recent years. This review summarizes the research progress of CP in the medical field in the past 5 years. By searching and analyzing the literature, and combining with Cytoscape software, we comprehensively examined the role and mechanism of action of CP in individual application, combination drug application, and the role and mechanism of action of codonopsis pilosula's active ingredients in a variety of diseases. It also analyzes the medicinal use of CP and its application value in medicine. This review found that CP mainly manifests important roles in several diseases, such as cardiovascular system, nervous system, digestive system, immune system, etc., and regulates the development of many diseases mainly through the mechanisms of inflammation regulation, oxidative stress, immunomodulation and apoptosis. Its rich pharmacological activities and diverse medicinal effects endow CP with broad prospects and application values. This review provides valuable reference and guidance for the further development of CP in traditional Chinese medicine.

A new and unified method for regression analysis of interval-censored failure time data under semiparametric transformation models with missing covariates.

This paper discusses regression analysis of interval-censored failure time data arising from semiparametric transformation models in the presence of missing covariates. Although some methods have been developed for the problem, they either apply only to limited situations or may have some computational issues. Corresponding to these, we propose a new and unified two-step inference procedure that can be easily implemented using the existing or standard software. The proposed method makes use of a set of working models to extract partial information from incomplete observations and yields a consistent estimator of regression parameters assuming missing at random. An extensive simulation study is conducted and indicates that it performs well in practical situations. Finally, we apply the proposed approach to an Alzheimer's Disease study that motivated this study.

Preparation of Cobalt-Nitrogen Co-Doped Carbon Nanotubes for Activated Peroxymonosulfate Degradation of Carbamazepine.

Cobalt-nitrogen co-doped carbon nanotubes (Co3@NCNT-800) were synthesized via a facile and economical approach to investigate the efficient degradation of organic pollutants in aqueous environments. This material demonstrated high catalytic efficiency in the degradation of carbamazepine (CBZ) in the presence of peroxymonosulfate (PMS). The experimental data revealed that at a neutral pH of 7 and an initial CBZ concentration of 20 mg/L, the application of Co3@NCNT-800 at 0.2 g/L facilitated a degradation rate of 64.7% within 60 min. Mechanistic investigations indicated that the presence of pyridinic nitrogen and cobalt species enhanced the generation of reactive oxygen species. Radical scavenging assays and electron spin resonance spectroscopy confirmed that radical and nonradical pathways contributed to CBZ degradation, with the nonradical mechanism being predominant. This research presents the development of a novel PMS catalyst, synthesized through an efficient and stable method, which provides a cost-effective solution for the remediation of organic contaminants in water.

A semi-parametric weighted likelihood approach for regression analysis of bivariate interval-censored outcomes from case-cohort studies.

The case-cohort design was developed to reduce costs when disease incidence is low and covariates are difficult to obtain. However, most of the existing methods are for right-censored data and there exists only limited research on interval-censored data, especially on regression analysis of bivariate interval-censored data. Interval-censored failure time data frequently occur in many areas and a large literature on their analyses has been established. In this paper, we discuss the situation of bivariate interval-censored data arising from case-cohort studies. For the problem, a class of semiparametric transformation frailty models is presented and for inference, a sieve weighted likelihood approach is developed. The large sample properties, including the consistency of the proposed estimators and the asymptotic normality of the regression parameter estimators, are established. Moreover, a simulation is conducted to assess the finite sample performance of the proposed method and suggests that it performs well in practice.