An outbreak of coronavirus disease in Wuhan, China caused by SARS-CoV-2 has led to a serious epidemic in China and other countries, resulting in worldwide concern. With active efforts of prevention and control, more and more patients are being discharged. However, how to manage these patients normatively is still challenging. This paper reports an asymptomatic discharged patient with COVID-19 who retested positive for SARS-CoV-2, which arouses concern regarding the present discharge standards of COVID-19.

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Background: The association between metabolic syndrome (MS), both in terms of its components and as a whole, and the risk of hepatocellular carcinoma (HCC) in subjects with hepatitis B virus (HBV) infection remains unclear, especially in mainland China. Methods: We prospectively included 6,564 individuals with HBV infection from an initial cohort of 105,397 civil servants. The multivariate-adjusted HR and 95% confidence interval (95% CI) were evaluated using Cox proportional hazards models to explore the potential connection between HCC risk and MS. Cumulative incidences were plotted using Kaplan-Meier curves. Results: After a 45,668.0 person-year follow-up (76.0 AE 30.8 months) of 6,564 subjects who were seropositive for hepatitis B surface antigen, 89 incident HCC cases were identified. MS as a whole was independently associated with a 2-fold increased HCC risk (HR, 2.25; 95% CI, 1.41-3.60) after adjusting for age (in 1-year increments), gender, cigarette smoking, alcohol consumption, liver cirrhosis, and elevated aspartate aminotransferase levels (!40 U/L). Subjects with three or more factors and those with one or two factors had adjusted increased HCC risks of 2.12-fold (95% CI, 1.16-3.89) and 1.28-fold (95% CI, 0.74-2.22), respectively, in comparison with those without any metabolic factors. Central obesity and type 2 diabetes were associated with significantly increased HCC risk, whereas this association was not observed in obese subjects (body mass index !30 kg/m 2 ; 95% CI, 0.73-3.44). Conclusions: MS as a whole, central obesity, and type 2 diabetes were independently associated with increased HCC risk in a population with HBV infection in mainland China. Impact: MS may be a risk factor for HCC.

Abstract. Image fusion combines several images of the same scene into a fused image, which contains all important information. Multiscale transform and sparse representation can solve this problem effectively. However, due to the limited number of dictionary atoms, it is difficult to provide an accurate description for image details in the sparse representation-based image fusion method, and it needs a great deal of calculations. In addition, for the multiscale transform-based method, the low-pass subband coefficients are so hard to represent sparsely that they cannot extract significant features from images. In this paper, a nonsubsampled contourlet transform (NSCT) and sparse representation-based image fusion method (NSCTSR) is proposed. NSCT is used to perform a multiscale decomposition of source images to express the details of images, and we present a dictionary learning scheme in NSCT domain, based on which we can represent low-frequency information of the image sparsely in order to extract the salient features of images. Furthermore, it can reduce the calculation cost of the fusion algorithm with sparse representation by the way of nonoverlapping blocking. The experimental results show that the proposed method outperforms both the fusion method based on single sparse representation and multiscale decompositon. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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