The objective of this study was to detect the Epstein–Barr virus (EBV) coinfection in coronavirus disease 2019 (COVID-19). In this retrospective single-center study, we included 67 COVID-19 patients with onset time within 2 weeks in Renmin Hospital of Wuhan University from January 9 to February 29, 2020. Patients were divided into EBV/SARS-CoV-2 coinfection group and SARS-CoV-2 infection alone group according to the serological results of EBV, and the characteristics differences between the two groups were compared. The median age was 37 years, with 35 (52.2%) females. Among these COVID-19 patients, thirty-seven (55.2%) patients were seropositive for EBV viral capsid antigen (VCA) IgM antibody. EBV/SARS-CoV-2 coinfection patients had a 3.09-fold risk of having a fever symptom than SARS-CoV-2 infection alone patients (95% CI 1.11–8.56; P = 0.03). C-reactive protein (CRP) (P = 0.02) and the aspartate aminotransferase (AST) (P = 0.04) in EBV/SARS-CoV-2 coinfection patients were higher than that in SARS-CoV-2 infection alone patients. EBV/SARS-CoV-2 coinfection patients had a higher portion of corticosteroid use than the SARS-CoV-2 infection alone patients (P = 0.03). We find a high incidence of EBV coinfection in COVID-19 patients. EBV/SARS-CoV-2 coinfection was associated with fever and increased inflammation. EBV reactivation may associated with the severity of COVID-19.

With the emergence of unmanned plane, autonomous vehicles, face recognition, and language processing, the artificial intelligence (AI) has remarkably revolutionized our lifestyle. Recent studies indicate that AI has astounding potential to perform much better than human beings in some tasks, especially in the image recognition field. As the amount of image data in imaging center of ophthalmology is increasing dramatically, analyzing and processing these data is in urgent need. AI has been tried to apply to decipher medical data and has made extraordinary progress in intelligent diagnosis. In this paper, we presented the basic workflow for building an AI model and systematically reviewed applications of AI in the diagnosis of eye diseases. Future work should focus on setting up systematic AI platforms to diagnose general eye diseases based on multimodal data in the real world.

Background: The emerging 2019 novel coronavirus (2019-nCoV) has pushed several countries into state of emergency all over the world. The possible transmission of 2019-nCoV by conjunctiva is controversial and has substantial public health implications. Methods: A retrospective cohort study was initiated to investigate the possible transmission of 2019-nCoV through aerosol contact with conjunctiva. We enrolled 67 cases of confirmed or suspected cases of novel coronavirus pneumonia (NCP) during 17–28 Jan 2020. Nasopharyngeal and conjunctival swabs were collected for real time RT-PCR analysis to detect 2019-nCoV. Results: 63 patients were identified as laboratory-confirmed NCP and the remaining four were suspected NCP. Conjunctival swab samples from one NCP patient yielded positive PCR results and two NCP patients yielded probable positive PCR results. None of the three patients had ocular symptoms. The only one NCP patient with conjunctivitis as the first symptom had negative conjunctival sac 2019-nCoV test. Conjunctival swab samples from the four suspected cases of NCIP were negative. Conclusion: 2019-nCoV can be detected in the conjunctival sac of patients with NCP. Through clinical analysis, viral transmission via the conjunctival route was not supported by the data. Good clinical protection can effectively cut off the transmission path.

Background: Dietary fiber is a functional substance with strong antioxidant activity that plays an important role in human health. Dietary fiber has been shown to reduce the risks of many types of cancers, but whether it can reduce the risk of death in cancer survivors remains undetermined. Methods: This study included the dietary data of cancer survivors who participated in the National Health and Nutrition Examination Surveys from 2001 to 2018. Firstly, the relationship between fiber intake and composite dietary antioxidant index (CDAI) was explored by weighted multiple regression and smooth curve. Subsequently, multivariable Cox proportional hazards regression models were used to explore the effects of dietary fiber intake and CDAI level on the risks of all-cause, tumor, and cardiovascular death among cancer survivors. Results: A total of 2077 participants were included in the study, representing approximately 11,854,509 cancer survivors in the United States. The dietary fiber intake of tumor survivors had a nonlinear positive relationship with CDAI levels (β = 0.24, 95% CI: 0.08–0.40, p = 0.004). Multivariable Cox proportional hazards regression models showed that high dietary fiber intake and CDAI levels were associated with reduced risks of all-cause and tumor death in tumor survivors, but were not associated with the risk of cardiovascular death. Conclusion: An increased dietary fiber intake can enhance the body’s antioxidant capacity. A higher dietary fiber intake and CDAI level may reduce the risk of all-cause and tumor death in tumor survivors.