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Aims There is an emerging interest in elucidating the natural history and prognosis for patients with heart failure with reduced ejection fraction (HFrEF) in whom left ventricular ejection fraction (LVEF) subsequently improves. The characteristics and outcomes were compared between heart failure with recovered ejection fraction (HFrecEF) and persistent HFrEF. Methods and results This is a retrospective study of adults who underwent at least two echocardiograms 3 months apart between 1 November 2015 and 31 October 2019 with an initial diagnosis of HFrEF. The subjects were divided into HFrecEF group (second LVEF > 40%, ≥10% absolute improvement in LVEF) and persistent HFrEF group (20% subgroups. The primary outcomes were all‐cause mortality and rehospitalization. A total of 1160 HFrEF patients were included [70.2% male, mean (standard deviation) age: 62 ± 13 years]. On the second echocardiogram, 284 patients (24.5%) showed HFrecEF and 876 patients (75.5%) showed persistent HFrEF. All‐cause mortality was identified in 23 (8.10%) HFrecEF and 165 (18.84%) persistent HFrEF, whilst 76 (26.76%) and 426 (48.63%) showed rehospitalizations, respectively. Survival analysis showed that the persistent HFrEF subgroup experienced a significantly higher mortality at 12 and 24 months and a higher hospitalization at 12, 24, 48, and more than 48 months following discharge. Multivariate Cox regression showed that persistent HFrEF had a higher risk of all‐cause mortality [hazard ratio (HR) 2.30, 95% confidence interval (CI) 1.49–3.56, P = 0.000] and rehospitalization (HR 1.85, 95% CI 1.45–2.36, P = 0.000) than the HFrecEF group. Subgroup analysis showed that the LVEF ≥ 20% improvement subgroup had lower rates of adverse outcomes compared with those with less improvement of 10–20%. Conclusions Heart failure with recovered ejection fraction is a distinct HF phenotype with better clinical outcomes compared with those with persistent HFrEF. HFrecEF patients have a relatively better short‐term mortality at 24 months but not thereafter.

Aims: HFA-PEFF score has been proposed for diagnosing heart failure with preserved ejection fraction (HFpEF). Currently, there are only a limited number of tools for predicting the prognosis. In this study, we evaluated whether the HFA-PEFF score can predict mortality in patients with HFpEF.Methods: This single-center, retrospective observational study enrolled patients diagnosed with HFpEF at the First Affiliated Hospital of Dalian Medical University between January 1, 2015, and April 30, 2018. The subjects were divided according to their HFA-PEFF score into low (0–2 points), intermediate (3–4 points), and high (5–6 points) score groups. The primary outcome was all-cause mortality.Results: A total of 358 patients (mean age: 70.21 ± 8.64 years, 58.1% female) were included. Of these, 63 (17.6%), 156 (43.6%), and 139 (38.8%) were classified into the low, intermediate, and high score groups, respectively. Over a mean follow-up of 26.9 months, 46 patients (12.8%) died. The percentage of patients who died in the low, intermediate, and high score groups were 1 (1.6%), 18 (11.5%), and 27 (19.4%), respectively. A multivariate Cox regression identified HFA-PEFF score as an independent predictor of all-cause mortality [hazard ratio (HR):1.314, 95% CI: 1.013–1.705, P = 0.039]. A Cox analysis demonstrated a significantly higher rate of mortality in the intermediate (HR: 4.912, 95% CI 1.154–20.907, P = 0.031) and high score groups (HR: 5.291, 95% CI: 1.239–22.593, P = 0.024) than the low score group. A receiver operating characteristic (ROC) analysis indicated that the HFA-PEFF score can effectively predict all-cause mortality after adjusting for age and New York Heart Association (NYHA) class [area under the curve (AUC) 0.726, 95% CI 0.651–0.800, P = 0.000]. With an HFA-PEFF score cut-off value of 3.5, the sensitivity and specificity were 78.3 and 54.8%, respectively. The AUC on ROC analysis for the biomarker component of the score was similar to that of the total score.Conclusions: The HFA-PEFF score can be used both to diagnose HFpEF and predict the prognosis. The higher scores are associated with higher all-cause mortality.

To explore the present treatment strategies for ischemic stroke lowered by ischemia-reperfusion (I/R) injury, to hypothesize the effect of d-Carvone on cerebral I/R brain injury induced neuroinflammation through oxidative stress markers mechanism via NRLP3 and TLR4 marker expressions in rat model. The rats were divided into four groups: Sham, I/R vehicle, I/R + D-carvone (10 mg/kg/bw), I/R + D-carvone (20 mg/kg/bw). Supplementation of d-carvone at dose of 10 and 20 m/kg/bw increased the water content, reduced infract volume, attenuated neurological score depicts, furthermore it had antioxidative, anti-inflammatory, and anti-apoptotic effects against cerebral I/R brain injury. In the brain tissues decreased proinflammatory cytokines IL-1β and TNF-α reduced interleukins IL-6, IL-4, IL-10 & VEGF dose dependently, and mRNA expressions of NLRP3, caspase -1, TNF-α, ASC, IL-1β and TLR3 down regulated in cerebral I/R induced rats. Finally d- carvone can successfully improve the cerebral I/R induced rats neuroinflammation, in the hippocampus and cortical areas of the brain finally reduces cerebral I/R induced injury. These results were hypothesized that d-carvone contributed to cerebral stroke associated with the TLR3, giving an excellent therapeutic approach for cerebral I/R brain injury.

BackgroundThe recent emergence and rapid global spread of coronavirus disease 2019 (COVID-19) is leading to public health crises worldwide. Alcohol consumption and cigarette smoking (CS) are two known risk factors in many diseases including respiratory infections.MethodsWe performed a multi-center study in the four largest hospitals designated for COVID-19 patients in Wuhan. There are totally 1547 patients diagnosed with COVID-19 enrolled in the study, alcohol consumption and CS history were evaluated among these patients. The epidemiology, laboratory findings and outcomes of patients contracted COVID-19 were further studied.ResultsOur findings indicated that COVID-19 patients with a history of CS tend to have more severe outcomes than non-smoking patients. However, alcohol consumption did not reveal significant effects on neither development of severe illness nor death rates in COVID-19 patients.ConclusionCS is a risk factor for developing severe illness and increasing mortality during the SARS-CoV-2 infection. We believe that our findings will provide a better understanding on the effects of alcohol intake and CS exposure in COVID-19 patients.

In China, the proportion of coal in the energy structure is high, and the utilization of coal will cause carbon emission and environmental pollution. Therefore, the adjustment of energy structure and the utilization of new energy has become the focus of China's efforts to comprehensively promote the green development of energy. At present, developing nuclear power has become a key way to break through the bottleneck of new energy power supply and realize economic and ecological benefits. Based on the current situation and existing problems of China's nuclear power industry, this paper puts forward the challenges and measures for the future development of nuclear power.

Dushan county, Guizhou province, is located in the southernmost tip of Guizhou province. It belongs to the temperate climate of the subtropical region and is one of the centers of the karst east Asia area. The total area of the county is 242220 hectares, of which 169142 hectares are rocky desertifi cation or endangered desertification state. At present, the problem of rocky desertification has seriously affected the ecological environment of the county, which is one of the important factors that restrict the local social living standard and economic development. Therefore, it is of great significance to promote the social and economic development of the county by investigating and analyzing the spatial differentiation rules, present situation and harm of rocky desertification in Dushan county.

As centralized state estimation algorithms for formation flying spacecraft would suffer from high computational burdens when the scale of the formation increases, it is necessary to develop decentralized algorithms. To the state of the art, most decentralized algorithms for formation flying are derived from centralized EKF by simplification and decoupling, rendering suboptimal estimations. In this paper, typical decentralized state estimation algorithms are reviewed, and a new scheme for decentralized algorithms is proposed. In the new solution, the system is modeled as a dynamic Bayesian network (DBN). A probabilistic graphical method named junction tree (JT) is used to analyze the hidden distributed structure of the DBNs. Inference on JT is a decentralized form of centralized Bayesian estimation (BE), which is a modularized three-step procedure of receiving messages, collecting evidences, and generating messages. As KF is a special case of BE, the new solution based on JT is equivalent in precision to centralized KF in theory. A cooperative navigation example of a three-satellite formation is used to test the decentralized algorithms. Simulation results indicate that JT has the best precision among all current decentralized algorithms.