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BackgroundBeta-blockers are antihypertensive drugs and have shown potential in cancer prognosis. However, this benefit has not been well defined due to inconsistent results from the published studies.MethodsTo investigate the association between administration of beta-blocker and cancer prognosis, we performed a meta-analysis. A literature search of PubMed, Embase, Cochrane Library, and Web of Science was conducted to identify all relevant studies published up to September 1, 2017. Thirty-six studies involving 319,006 patients were included. Hazard ratios were pooled using a random-effects model. Subgroup analyses were conducted by stratifying ethnicity, duration of drug use, cancer stage, sample size, beta-blocker type, chronological order of drug use, and different types of cancers.ResultsOverall, there was no evidence to suggest an association between beta-blocker use and overall survival (HR=0.94, 95% CI: 0.87–1.03), all-cause mortality (HR=0.99, 95% CI: 0.94–1.05), disease-free survival (HR=0.59, 95% CI: 0.30–1.17), progression-free survival (HR=0.90, 95% CI: 0.79–1.02), and recurrence-free survival (HR=0.99, 95% CI: 0.76–1.28), as well. In contrast, beta-blocker use was significantly associated with better cancer-specific survival (CSS) (HR=0.78, 95% CI: 0.65–0.95). Subgroup analysis generally supported main results. But there is still heterogeneity among cancer types that beta-blocker use is associated with improved survival among patients with ovarian cancer, pancreatic cancer, and melanoma.ConclusionThe present meta-analysis generally demonstrates no association between beta-blocker use and cancer prognosis except for CSS in all population groups examined. High-quality studies should be conducted to confirm this conclusion in future.

Background The triglyceride-glucose index (TyG) is a reliable predictor of non-alcoholic fatty liver disease (NAFLD). Its association with the severity of hepatic steatosis and liver fibrosis in NAFLD is poorly understood. This study evaluated the relationship between these factors in NAFLD. Methods A total of 4784 participants who underwent ultrasonography were enrolled. Anthropometric and biochemical measurements were assessed. Participants with NAFLD were diagnosed by ultrasound. The degree of hepatic steatosis and liver stiffness was evaluated with transient elastography. Results The TyG index was significantly correlated with the severity of hepatic steatosis and the presence of liver fibrosis in patients with NAFLD. TyG quartile values correlated with increasing prevalence of NAFLD (Q1 30.9%, Q2 53.3%, Q3 71.7%, and Q4 86.4%, P < 0.001) and with the presence of liver fibrosis (Q1 13.5%, Q2 17.6%, Q3 18.8%, and Q4 26.1%, P < 0.001). The AUROC for the TyG index to predict NAFLD was 0.761, resulting in a cut-off value of 8.7. However, the AUC value of the TyG index was 0.589 for liver fibrosis, which was insufficient to predict this condition. The adjusted odds of having hepatic steatosis or liver fibrosis were more strongly associated with TyG values compared with HOMA-IR. Conclusion The TyG index is positively related to the severity of hepatic steatosis and the presence of liver fibrosis in NAFLD. The index also performed better than HOMA-IR.

Background: Insulin resistance (IR) is a significant risk factor for cardiovascular disease (CVD). In this study, the association of the triglyceride glucose (TyG) index, a simple surrogate marker of IR, with arterial stiffness and 10-year CVD risk was evaluated.Methods: A total of 13,706 participants were enrolled. Anthropometric and cardiovascular risk factors were determined in all participants, while serum insulin levels were only measured in 955 participants. Arterial stiffness was measured through brachial-ankle pulse wave velocity (baPWV), and 10-year CVD risk was evaluated using the Framingham risk score.Results: All participants were classified into four groups according to the quartile of the TyG index. BaPWV and the percentage of participants in the 10-year CVD risk categories significantly increased with increasing quartiles of the TyG index. Logistic regression analysis showed that the TyG index was independently associated with a high baPWV and 10-year CVD risk after adjusting for traditional CVD risk factors. The area under the receiver operating characteristics curve (AUROC) of the TyG index for predicting a high baPWV was 0.708 (95%CI 0.693–0.722, P &lt; 0.001) in women, higher than that in men. However, the association of the homeostatic model assessment of IR (HOMA-IR) with a high baPWV and the 10-year CVD risk was absent when adjusting for multiple risk factors in 955 participants.Conclusions: The TyG index is independently associated with arterial stiffness and 10-year CVD risk.

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As an essential factor of production, energy is receiving increased attention. Yet, other than some fundamental policy suggestions towards China’s energy issues, there have been very few investigations into energy misallocation so far. The measurements of energy misallocation index and carbon emission efficiency were made based on the panel data from 30 provinces in China. To empirically study the impact of energy misallocation on carbon emission efficiency, a spatial econometric model was built. It is found that during the survey period, there was a certain degree of energy misallocation in all regions of China, and the differences between the regions were obvious. There is an inverted U-shaped relationship between the impact of energy misallocation and carbon emission efficiency in which intensified allocation distortion accelerates the arrival of the critical point that is not conducive to energy conservation and emission reduction. The results viewed by regions show that due to a low degree o*f misallocation, the impact of carbon emission efficiency in the east region is positive, while that of the central and west regions are mostly negative. Accordingly, it is necessary to accelerate the marketization process of the energy market and improve the ecological quality.

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This paper expanded the Logarithmic Mean Divisia Index (LMDI) model through the introduction of urbanization, residents' consumption, and other factors, and decomposed carbon emission changes in China into carbon emission factor effect, energy intensity effect, consumption inhibitory factor effect, urbanization effect, residents' consumption effect, and population scale effect, and then explored contribution rates and action mechanisms of the above six factors on change in carbon emissions in China. Then, the effect of population structure change on carbon emission was analyzed by taking 2003-2012 as a sample period, and combining this with the panel data of 30 provinces in China. Results showed that in 2003-2012, total carbon emission increased by 4.2117 billion tons in China. The consumption inhibitory factor effect, urbanization effect, residents' consumption effect, and population scale effect promoted the increase in carbon emissions, and their contribution ratios were 27.44%, 12.700%, 74.96%, and 5.90%, respectively. However, the influence of carbon emission factor effect (´2.54%) and energy intensity effect (´18.46%) on carbon emissions were negative. Population urbanization has become the main population factor which affects carbon emission in China. The "Eastern aggregation" phenomenon caused the population scale effect in the eastern area to be significantly higher than in the central and western regions, but the contribution rate of its energy intensity effect (´11.10 million tons) was significantly smaller than in the central (´21.61 million tons) and western regions (´13.29 million tons), and the carbon emission factor effect in the central area (´3.33 million tons) was significantly higher than that in the eastern (´2.00 million tons) and western regions (´1.08 million tons). During the sample period, the change in population age structure, population education structure, and population occupation structure relieved growth of carbon emissions in China, but the effects of change of population, urban and rural structure, regional economic level, and population size generated increases in carbon emissions. Finally, the change of population sex structure had no significant influence on changes in carbon emissions.