Objective: To evaluate the effect of high air temperature on diabetes mortality in six cities in China. Methods: Daily diabetes mortality and meteorological data were collected from January 1, 2008 to December 31, 2013 in Beijing, Tianjin, Shanghai, Chongqing, Guangzhou, and Shenyang. Distributed lag nonlinear model was used to evaluate the association between high air temperature and diabetes mortality after controlling for the long-term trend and the effect of "day of week" . Results: The effect of high air temperature on diabetes mortality varied in different cities, the maximum cumulative relative risk of Beijing, Tianjin, Shanghai, Chongqing, Guangzhou and Shenyang were 1.37 (lag 2 days), 1.32 (lag 0 days), 1.40 (lag 0 days), 1.26 (lag 2 days), 1.48 (lag 2 days) and 1.67 (lag 3 days). The daily diabetes death numbers were similar in men and women, but the death number in women were slightly higher than that in men, no gender specific characteristics were found. The death number was highest in age group 65-84 years, accounting for >60% of the total deaths, the difference was significant. Conclusion: The mortality of diabetes increased obviously in the context of high air temperature environment.
Air Pollution ; Beijing/epidemiology* ; China/epidemiology* ; Cities ; Diabetes Mellitus/mortality* ; Female ; Fever ; Hot Temperature ; Humans ; Male ; Nonlinear Dynamics ; Risk ; Risk Factors ; Temperature ; Urban Population

Objective: To understand the associations between changes of high air temperature and mortality in summer in 31 cities in China. Methods: Daily mortality and meteorological data in 31 cities in China from January 1, 2008 to December 31, 2013 were collected. Distributed lag nonlinear model was used to evaluate the association between high air temperature change and mortality in early summer and late summer after controlling for the long-term trend and the effect of "day of week" . Results: The relative risk of high air temperature on mortality was higher in early summer, with relative risk in the range of 1.08-2.14 in early summer and 1.03-1.67 in late summer. In early summer, the influence of high temperature on mortality was mainly below 5(th) of percentile and above 50(th) of percentile, while in late summer it was mainly above 95(th) of percentile. The lag effect of high air temperature on mortality in early summer was 6 days, while the lag effect in late summer was only about 2 days. Conclusions: Association existed between high air temperature and mortality. The influence of high air temperature on mortality in early summer was stronger than that in late summer. It is necessary to take targeted protection measures.
Air Pollution ; China ; Cities ; Hot Temperature/adverse effects* ; Mortality ; Nonlinear Dynamics ; Temperature

To address the increasing need for detecting and validating protein biomarkers in clinical specimens, mass spectrometry (MS)-based targeted proteomic techniques, including the selected reaction monitoring (SRM), parallel reaction monitoring (PRM), and massively parallel data-independent acquisition (DIA), have been developed. For optimal performance, they require the fragment ion spectra of targeted peptides as prior knowledge. In this report, we describe a MS pipe-line and spectral resource to support targeted proteomics studies for human tissue samples. To build the spectral resource, we integrated common open-source MS computational tools to assemble a freely accessible computational workflow based on Docker. We then applied the workflow to gen-erate DPHL, a comprehensive DIA pan-human library, from 1096 data-dependent acquisition (DDA) MS raw files for 16 types of cancer samples. This extensive spectral resource was then applied to a proteomic study of 17 prostate cancer (PCa) patients. Thereafter, PRM validation was applied to a larger study of 57 PCa patients and the differential expression of three proteins in prostate tumor was validated. As a second application, the DPHL spectral resource was applied to a study consisting of plasma samples from 19 diffuse large B cell lymphoma (DLBCL) patients and 18 healthy control subjects. Differentially expressed proteins between DLBCL patients and healthy control subjects were detected by DIA-MS and confirmed by PRM. These data demonstrate that the DPHL supports DIA and PRM MS pipelines for robust protein biomarker discovery. DPHL is freely accessible at https://www.iprox.org/page/project.html?id=IPX0001400000.