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Background: The outbreak of COVID-19 in 2019 has rapidly swept the world, causing irreparable loss to human beings. The pandemic has shown that there is still a delay in the early response to disease outbreaks and needs a method for unknown disease outbreak detection. The study's objective is to establish a new medical knowledge representation and reasoning model, and use the model to explore the feasibility of unknown disease outbreak detection. Methods: The study defined abnormal values with diagnostic significances from clinical data as the Features, and defined the Features as the antecedents of inference rules to match with knowledge bases, achieved in detecting known or emerging infectious disease outbreaks. Meanwhile, the study built a syndromic surveillance base to capture the target cases' Features to improve the reliability and fault-tolerant ability of the system. Results: The study combined the method with Severe Acute Respiratory Syndrome (SARS), Middle East Respiratory Syndrome (MERS), and early COVID-19 outbreaks as empirical studies. The results showed that with suitable surveillance guidelines, the method proposed in this study was capable to detect outbreaks of SARS, MERS, and early COVID-19 pandemics. The quick matching accuracies of confirmed infection cases were 89.1, 26.3-98%, and 82%, and the syndromic surveillance base would capture the Features of the remaining cases to ensure the overall detection accuracies. Based on the early COVID-19 data in Wuhan, this study estimated that the median time of the early COVID-19 cases from illness onset to local authorities' responses could be reduced to 7.0-10.0 days. Conclusions: This study offers a new solution to transfer traditional medical knowledge into structured data and form diagnosis rules, enables the representation of doctors' logistic thinking and the knowledge transmission among different users. The results of empirical studies demonstrate that by constantly inputting medical knowledge into the system, the proposed method will be capable to detect unknown diseases from existing ones and perform an early response to the initial outbreaks., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Feng, Hu and Jiang.)

The outbreak of coronavirus disease 2019 (COVID-19) was first reported in Wuhan, China, in December 2019. To investigate the prevalence of COVID-19 in Wuhan, we conducted serologic tests on 35,326 individuals from four different communities to estimate cumulative incidence of infection. Our results showed that 1,332 individuals (3.77%) showed positive COVID-19 antibody (either IgM or IgG). Males had a lower positivity rate than females (3.02% versus 4.52%). The antibody positivity rates showed a clear trend of increase according to patients' ages and varied among different communities. The results indicate that public health interventions may play important roles in the control of COVID-19. IMPORTANCE Coronavirus disease 2019 (COVID-19) was first detected in December 2019 in Wuhan, China. Afterwards, a number of public health interventions were implemented, including lock-down, face mask ordinances, and social distancing. Studies that rely on viral RNA testing of symptomatic patients have shown that these multifaceted interventions contributed to the control of the COVID-19 outbreak in Wuhan and delayed the epidemic's progression. However, these estimates of confirmed cases may miss large numbers of asymptomatic patients and recovered symptomatic patients who were not tested. To investigate the prevalence of COVID-19 in Wuhan, we conducted serologic tests on 35,326 individuals to estimate the cumulative incidence of infection. The results suggest that public health interventions may play important roles in the control of COVID-19., (Copyright © 2021 Han et al.)

Background & Aims: The outbreak of coronavirus disease 2019 (COVID-19) has been declared a pandemic. Although COVID-19 is caused by infection in the respiratory tract, extrapulmonary manifestations including dysregulation of the immune system and hepatic injury have been observed. Given the high prevalence of hepatitis B virus (HBV) infection in China, we sought to study the impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and HBV coinfection in patients., Methods: Blood samples of 50 SARS-CoV-2 and HBV coinfected patients, 56 SARS-CoV-2 mono-infected patients, 57 HBeAg-negative chronic HBV patient controls and 57 healthy controls admitted to Renmin Hospital of Wuhan University were collected in this study. Complete blood count and serum biochemistry panels including markers indicative of liver functions were performed. Cytokines including IFN-γ, TNF-α, IL-2, IL-4, IL-6 and IL-10 were evaluated. T cell, B cell and NK cell counts were measured using flow cytometry., Results: SARS-CoV-2 and HBV coinfection did not significantly affect the outcome of the COVID-19. However, at the onset of COVID-19, SARS-CoV-2 and HBV coinfected patients showed more severe monocytopenia and thrombocytopenia as well as more disturbed hepatic function in albumin production and lipid metabolism. Most of the disarrangement could be reversed after recovery from COVID-19., Conclusions: While chronic HBV infection did not predispose COVID-19 patients to more severe outcomes, our data suggest SARS-CoV-2 and HBV coinfection poses a higher extent of dysregulation of host functions at the onset of COVID-19. Thus, caution needs to be taken with the management of SARS-CoV-2 and HBV coinfected patients., (© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

The coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was identified in December 2019 and has subsequently spread worldwide. Currently, there is no effective method to cure COVID-19. Mesenchymal stromal cells (MSCs) may be able to effectively treat COVID-19, especially for severe and critical patients. Menstrual blood-derived MSCs have recently received much attention due to their superior proliferation ability and their lack of ethical problems. Forty-four patients were enrolled from January to April 2020 in a multicenter, open-label, nonrandomized, parallel-controlled exploratory trial. Twenty-six patients received allogeneic, menstrual blood-derived MSC therapy, and concomitant medications (experimental group), and 18 patients received only concomitant medications (control group). The experimental group was treated with three infusions totaling 9 × 10 7 MSCs, one infusion every other day. Primary and secondary endpoints related to safety and efficacy were assessed at various time points during the 1-month period following MSC infusion. Safety was measured using the frequency of treatment-related adverse events (AEs). Patients in the MSC group showed significantly lower mortality (7.69% died in the experimental group vs 33.33% in the control group; P = .048). There was a significant improvement in dyspnea while undergoing MSC infusion on days 1, 3, and 5. Additionally, SpO 2 was significantly improved following MSC infusion, and chest imaging results were improved in the experimental group in the first month after MSC infusion. The incidence of most AEs did not differ between the groups. MSC-based therapy may serve as a promising alternative method for treating severe and critical COVID-19., (© 2021 The Authors. Clinical and Translational Medicine published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics.)