Extremely cold and hot temperatures increase the risk of ischaemic heart disease mortality: epidemiological evidence from China.

OBJECTIVE: To examine the effects of extremely cold and hot temperatures on ischaemic heart disease (IHD) mortality in five cities (Beijing, Tianjin, Shanghai, Wuhan and Guangzhou) in China; and to examine the time relationships between cold and hot temperatures and IHD mortality for each city. DESIGN: A negative binomial regression model combined with a distributed lag non-linear model was used to examine city-specific temperature effects on IHD mortality up to 20 lag days. A meta-analysis was used to pool the cold effects and hot effects across the five cities. PATIENTS: 16 559 IHD deaths were monitored by a sentinel surveillance system in five cities during 2004-2008. RESULTS: The relationships between temperature and IHD mortality were non-linear in all five cities. The minimum-mortality temperatures in northern cities were lower than in southern cities. In Beijing, Tianjin and Guangzhou, the effects of extremely cold temperatures were delayed, while Shanghai and Wuhan had immediate cold effects. The effects of extremely hot temperatures appeared immediately in all the cities except Wuhan. Meta-analysis showed that IHD mortality increased 48% at the 1st percentile of temperature (extremely cold temperature) compared with the 10th percentile, while IHD mortality increased 18% at the 99th percentile of temperature (extremely hot temperature) compared with the 90th percentile. CONCLUSIONS: Results indicate that both extremely cold and hot temperatures increase IHD mortality in China. Each city has its characteristics of heat effects on IHD mortality. The policy for response to climate change should consider local climate-IHD mortality relationships

The Impact of Temperature on Mortality in Tianjin, China: A Case-Crossover Design with a Distributed Lag Nonlinear Model

Background: Although interest in assessing the impacts of temperature on mortality has increased, few studies have used a case-crossover design to examine nonlinear and distributed lag effects of temperature on mortality. Additionally, little evidence is available on the temperature–mortality relationship in China or on what temperature measure is the best predictor of mortality

Metro Proximity and Built Environment on Commuting CO2 Emissions in Shanghai

To explore the impact of geographical location, built environment, public transportation service and individual socioeconomic attributes on commuting carbon dioxide (CO2) emissions, a survey was conducted in 27 residential compounds of Shanghai in 2016. In this paper, commuting distance was calculated according to a Baidu map application programming interface (API). CO2 emissions were calculated based on the mode used in each segment of commuting and distance travelled. Through the use of a multiple linear regression model, factors of personal socioeconomic attributes, including gender, occupation and apartment area, were significant to commuting CO2 emissions. In terms of the public transport service, the distance from compounds to the nearest metro station was found to be a significant factor on CO2 emissions, whereas the built environment, such as parking space and employment density, had a weak impact in our study. In addition, even when living near a metro station, the top 20% of travellers’ CO2 emissions can account for approximately 80% of the total CO2 emissions. Hence, policies to reduce those people’s commuting CO2 emissions are worth further exploring

A robust optimization method for new distribution systems based on adaptive data-driven polyhedral sets

In order to better describe the uncertainty of renewable energy output, this paper proposed a novel robust optimization method for new distribution systems based on adaptive data-driven polyhedral sets. First, an ellipsoidal uncertainty set was established using historical data on renewable energy output, and a data-driven convex hull polyhedral set was established by connecting high-dimensional ellipsoidal vertices; on this basis, an adaptive data-driven polyhedral set model was established to address the problem of high conservatism in the scaling process of convex hull polyhedral sets. Furthermore, a novel adaptive data-driven robust scheduling model for new distribution systems was established, and a column-and-constraint generation (C&CG) algorithm was used to solve the robust scheduling model. Finally, the improved IEEE-33 bus system simulation verification shows that the robust scheduling model for new distribution systems based on adaptive data-driven polyhedral sets can reduce conservatism and improve the robustness of optimization results

Regression of Gastric Cancer by Systemic Injection of RNA Nanoparticles Carrying Both Ligand and siRNA

Gastric cancer is the second leading cause of cancer-related death worldwide. RNA nanotechnology has recently emerged as an important field due to recent finding of its high thermodynamic stability, favorable and distinctive in vivo attributes. Here we reported the use of the thermostable three-way junction (3WJ) of bacteriophage phi29 motor pRNA to escort folic acid, a fluorescent image marker and BRCAA1 siRNA for targeting, imaging, delivery, gene silencing and regression of gastric cancer in animal models. In vitro assay revealed that the RNA nanoparticles specifically bind to gastric cancer cells, and knock-down the BRCAA1 gene. Apoptosis of gastric cancer cells was observed. Animal trials confirmed that these RNA nanoparticles could be used to image gastric cancer in vivo, while showing little accumulation in crucial organs and tissues. The volume of gastric tumors noticeably decreased during the course of treatment. No damage to important organs by RNA nanoparticles was detectible. All the results indicated that this novel RNA nanotechnology can overcome conventional cancer therapeutic limitations and opens new opportunities for specific delivery of therapeutics to stomach cancer without damaging normal cells and tissues, reduce the toxicity and side effect, improve the therapeutic effect, and exhibit great potential in clinical tumor therapy