Health Impacts of Long-Term NO2 Exposure and Inequalities among the Chinese Population from 2013 to 2020.

Nitrogen dioxide (NO2) is associated with mortality and many other adverse health outcomes. In 2021, the World Health Organization established a new NO2 air quality guideline (AQG) (annual average <10 µg/m3). However, the burden of diseases attributable to long-term NO2 exposure above the AQG is unknown in China. Nitrogen oxide is a major air pollutant in populous cities, which are disproportionately impacted by NO2; this represents a form of environmental inequality. We conducted a nationwide risk assessment of premature deaths attributable to long-term NO2 exposure from 2013 to 2020 based on the exposure-response relationship, high-resolution annual NO2 concentrations, and gridded population data (considering sex, age, and residence [urban vs rural]). We calculated health metrics including attributable deaths, years of life lost (YLL), and loss of life expectancy (LLE). Inequality in the distribution of attributable deaths and YLLs was evaluated by the Lorenz curve and Gini index. According to the health impact assessments, in 2013, long-term NO2 exposure contributed to 315,847 (95% confidence interval [CI]: 306,709-319,269) premature deaths, 7.90 (7.68-7.99) million YLLs, and an LLE of 0.51 (0.50-0.52) years. The high-risk subgroup (top 20%) accounted for 85.7% of all NO2-related deaths and 85.2% of YLLs, resulting in Gini index values of 0.81 and 0.67, respectively. From 2013 to 2020, the estimated health impact from NO2 exposure was significantly reduced, but inequality displayed a slightly increasing trend. Our study revealed a considerable burden of NO2-related deaths in China, which were disproportionally frequent in a small high-risk subgroup. Future clean air initiatives should focus not only on reducing the average level of NO2 exposure but also minimizing inequality.

Randomization tests for multiarmed randomized clinical trials.

We examine the use of randomization-based inference for analyzing multiarmed randomized clinical trials, including the application of conditional randomization tests to multiple comparisons. The view is taken that the linkage of the statistical test to the experimental design (randomization procedure) should be recognized. A selected collection of randomization procedures generalized to multiarmed treatment allocation is summarized, and generalizations for two randomization procedures that heretofore were designed for only two treatments are developed. We explain the process of computing the randomization test and conditional randomization test via Monte Carlo simulation, developing an efficient algorithm that makes multiple comparisons possible that would not be possible using a standard algorithm, demonstrate the preservation of type I error rate, and explore the relationship of statistical power to the randomization procedure in the presence of a time trend and outliers. We distinguish between the interpretation of the p-value in the randomization test and in the population test and verify that the randomization test can be approximated by the population test on some occasions. Data from two multiarmed clinical trials from the literature are reanalyzed to illustrate the methodology.

A novel molecularly imprinted electrochemical sensor based on graphene quantum dots coated on hollow nickel nanospheres with high sensitivity and selectivity for the rapid determination of bisphenol S.

In this paper, a novel molecularly imprinted electrochemical sensor (MIECS) based on a glassy carbon electrode (GCE) modified with graphene quantum dots (GQDs) coated on hollow nickel nanospheres (hNiNS) for the rapid determination of bisphenol S (BPS) was proposed for the first time. HNiNS and GQDs as electrode modifications were used to enlarge the active area and electron-transport ability for amplifying the sensor signal, while molecularly imprinted polymer (MIP) film was electropolymerized by using pyrrole as monomer and BPS as template to detect BPS via cyclic voltammetry (CV). Scanning electron microscope (SEM), energy-dispersive spectrometry (EDS), CV and differential pulse voltammetry (DPV) were employed to characterize the fabricated sensor. Experimental conditions, such as molar ratio of monomer to template, electropolymerization cycles, pH, incubation time and elution time were optimized. The DPV response of the MIECS to BPS was obtained in the linear range from 0.1 to 50µM with a low limit of detection (LOD) of 0.03µM (S/N = 3) under the optimized conditions. The MIECS exhibited excellent response towards BPS with high sensitivity, selectivity, good reproducibility, and stability. In addition, the proposed MIECS was also successfully applied for the determination of BPS in the plastic samples with simple sample pretreatment.