Verification of SARS-CoV-2-Encoded small RNAs and contribution to Infection-Associated lung inflammation (preprint)

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the virus that causes coronavirus disease 2019 (COVID-19), the respiratory illness responsible for the COVID-19 pandemic. SARS-CoV-2 is a positive-stranded RNA virus belongs to Coronaviridae family. The viral genome of SARS-CoV-2 contains around 29.8 kilobase with a 5'-cap structure and 3'-poly-A tail, and shows 79.2% nucleotide identity with human SARS-CoV-1, which caused the 2002-2004 SARS outbreak. As the successor to SARS-CoV-1, SARS-CoV-2 now has circulated across the globe. There is a growing understanding of SARS-CoV-2 in virology, epidemiology, and clinical management strategies. In this study, we verified the existence of two 18-22 nt small viral RNAs (svRNAs) derived from the same precursor in human specimens infected with SARS-CoV-2, including nasopharyngeal swabs and formalin-fixed paraffin-embedded (FFPE) explanted lungs from lung transplantation of COVID-19 patients. We then simulated and confirmed the formation of these two SARS-CoV-2-Encoded small RNAs in human lung epithelial cells. And the potential pro-inflammatory effects of the splicing and maturation process of these two svRNAs in human lung epithelial cells were also explored. By screening cytokine storm genes and the characteristic expression profiling of COVID-19 in the explanted lung tissues and the svRNAs precursor transfected human lung epithelial cells, we found that the maturation of these two small viral RNAs contributed significantly to the infection associated lung inflammation, mainly via the activation of the CXCL8, CXCL11 and type I interferon signaling pathway. Taken together, we discovered two SARS-CoV-2-Encoded small RNAs and investigated the pro-inflammatory effects during their maturation in human lung epithelial cells, which might provide new insight into the pathogenesis and possible treatment options for COVID-19.

Strong policies control the spread of COVID-19 in China.

The coronavirus disease 2019 (COVID-19) outbroke in Wuhan, Hubei Province, China, affecting more than 200 countries and regions. This study aimed to predict the development of the epidemic with specific interventional policies applied in China and evaluate their effectiveness. COVID-19 data of Hubei Province and the next five most affected provinces were collected from daily case reports of COVID-19 on the Health Committee official website of these provinces. The number of current cases, defined as the number of confirmed cases minus the number of cured cases and those who have died, were examined in this study. A modified susceptible-exposed-infectious-removed (SEIR) model was used to assess the effects of interventional policies on the epidemic. In this study, 28 January was day 0 of the model. The results of the modified SEIR model showed that the number of current cases in Hubei and Zhejiang provinces tended to be stabilized after 70 days and after 60 days in the four other provinces. The predicted number of current cases without policy intervention was shown to far exceed that with policy intervention. The estimated number of COVID-19 cases in Hubei Province with policy intervention was predicted to peak at 51 222, whereas that without policy intervention was predicted to reach 157 721. Based on the results of the model, strong interventional policies were found to be vital components of epidemic control. Applying such policies is likely to shorten the duration of the epidemic and reduce the number of new cases.

Flipped classroom improves nursing students' theoretical learning in China: A meta-analysis.

OBJECTIVE: At present, current didactic teaching delivery method help nursing students apply theory to clinical situations in an inefficient way. The flipped classroom (FC), a novel teaching mode emphasizing self-study and critical thinking, has generated interest in nursing education in China. However, there are a gap in the literature and no consistent outcomes of current studies which compared FC and lecture-based learning (LBL), and no systematic review has comprehensively compared theoretical scores as an affected outcome in FC versus LBL modes. METHODS: In this review, we analyze flipped-learning nursing students' scores, and aim to assess the efficacy and provide a deeper understanding of the FC in nursing education. Following the inclusion criteria, articles were obtained by searching PubMed, Embase and Chinese data, including the China National Knowledge Infrastructure, Wanfang Data, and VIP database until 3 January 2020. Data were extracted from eligible articles and quality was assessed. A meta-analysis was then performed using a random effects model with a standardized mean value (SMD) and a 95% confidence interval (CI).32 studies were included after reviewing 2,439 citations. All studies were randomized controlled trials (RCTs). The FC theoretical knowledge scores in FC were significantly positively affected compared to those of the traditional classroom (SMD = 1.33, 95% CI: 1.02-1.64; P < 0.001). In addition, 23 studies reported skill scores, indicating significant difference between the FC mode and LBL mode (SMD = 1.58, 95%CI: 1.23-1.93; P < 0.001). CONCLUSIONS: The results of this meta-analysis suggest that compared to the LBL teaching method, the FC mode dose significantly improve Chinese nursing students' theoretical scores. However, the problems of heterogeneity and publication bias in this study need to be remedied high-quality future studies.