Spatiotemporal characteristics of carbon emissions in Shaanxi, China, during 2012-2019: a machine learning method with multiple variables.

Global warming attributed to the emission of greenhouse gases has caused unprecedented extreme weather events, such as excessive heatwave and rainfall, posing enormous threats to human life and sustainable development. China, as the toppest CO2 emitter in the world, has promised to achieve carbon emission peak by 2030. However, it is difficult to estimate county-level carbon emissions in China because of the lack of statistical data. Previous studies have established relationship between carbon emission and nighttime light; however, using only nighttime light for carbon emission modeling ignores the impact of natural or other socioeconomic factors on emissions. In this paper, we adopted the back propagation neural network to estimate carbon emissions at county level in Shaanxi, China, using nighttime light, Normalized Difference Vegetation Index, precipitation, land surface temperature, elevation, and population density. Trend analysis, spatial autocorrelation, and standard deviation ellipse were employed to analyze the spatiotemporal distributions of carbon emission during 2012-2019. Three metrics (R2, root mean square error, and mean absolute error) were adopted to validate the accuracy of the proposed model, with the values of 0.95, 1.30, and 0.58 million tons, respectively, demonstrating a comparable estimation performance. The results present that carbon emissions in Shaanxi Province rise from 256.73 in 2012 to 305.87 million tons in 2019, formatting two hotspots in Xi'an and Yulin city. The proposed model can estimate carbon emissions of Shaanxi Province at a finer scale with an acceptable accuracy, which can be efficiently applied in other spatial or temporal domains after being localized, providing technical supports for carbon reduction.

Regional variation of medical expenditures attributable to hypertension in China's middle-aged and elderly population.

BACKGROUND: Hypertension is a prevalent and costly health condition in China. Little is known about variation of the inpatient and outpatient expenditures attributable to hypertension between prefecture-level administrative regions (PARs) and the drivers of such variation among China's middle-aged and elderly population. METHODS: We obtain data from China Health and Retirement Longitudinal Survey between 2011 and 2015, panel tobit models were used in our study to estimate differences across 122 PARs. Expenditure variation was explained by the characteristics of individuals and regions, including measures of healthcare supply. RESULTS: The cost of treatment for patients with hypertension varies greatly geographically, with the highest outpatient and inpatient costs being 77 and 102 times the lowest, respectively. After adjustment for the individual and PAR character, there are associations between expenditure and region bed density. CONCLUSION: There were significant regional differences in the outpatient and inpatient costs of middle-aged and elderly patients with hypertension in China, the difference between individuals may be an important reason, which has little to do with regional economic development differences, but is related to regional bed density.

Biocompatible and Rapid Cyclization of Peptides with 2,4-Difluoro-6-hydroxy-1,3,5-benzenetricarbonitrile for the Development of Cyclic Peptide Libraries.

We report a biocompatible and rapid reaction between cysteine thiols and 2,4-difluoro-6-hydroxy-1,3,5-benzenetricarbonitrile (DFB), which enables the efficient cyclization of peptides in neutral aqueous solutions. The reaction was further applied to cyclize peptides displayed on the phage surface without reducing phage infectivity, thus affording high-quality cyclic peptide libraries useful for screening of cyclic peptide ligands. Using the DFB-cyclic peptide library, we identified ligands that can distinguish the pro-survival protein Bcl-xl from its close relative Bcl-2. Therefore, this study on one hand reports a useful reaction for the construction of cyclic peptide libraries, and on the other hand presents valuable hits for further design of selective Bcl-xl ligands.

[Alprazolam use improves psychological status and reduces hospitalization costs in patients with paroxysmal supraventricular tachycardia underwent radiofrequency catheter ablation].

OBJECTIVE: To evaluate the effect of alprazolam use on psychological status and hospitalization cost in patient with paroxysmal supraventricular tachycardia underwent electrophysiology studies or radiofrequency catheter ablation. METHODS: In this prospective, randomized, double-blind, placebo-controlled study, 142 inpatients [77 males, mean age (43.1 +/- 14.5) years] were randomly assigned to receive alprazolam (0.4 mg qd at 10PM for 3 days, n = 72) or placebo (n = 70) 3 days before scheduled electrophysiology studies or radiofrequency catheter ablation. All patients were examined by the Chinese version of Symptom Checklist-90 (SCL-90) at 24 hours before the procedure. RESULTS: Compared with the placebo group, the scores of somatization (1.38 +/- 0.40 vs. 1.65 +/- 0.56, P < 0.01), anxiety (1.50 +/- 0.39 vs. 1.69 +/- 0.50, P < 0.05), phobic anxiety (1.24 +/- 0.36 vs. 1.47 +/- 0.57, P < 0.01), psychotism constructs (1.24 +/- 0.34 vs. 1.35 +/- 0.30, P < 0.05) and global severity index (1.36 +/- 0.35 vs. 1.49 +/- 0.37, P < 0.05) were significantly decreased in alprazolam group. The hospitalization costs were also significantly lower in alprazolam group (32 498 +/- 1170) yuan compared to placebo group (32 947 +/- 1096) yuan, P < 0.05. CONCLUSION: The alprazolam use before electrophysiology studies and radiofrequency catheter ablation can improve the patients' psychological status and reduce the hospitalization costs.