Bioinformatics analysis based on high-throughput sequencing data to identify hub genes related to different clinical types of COVID-19.

This article aims to explore hub genes related to different clinical types of cases with COVID-19 and predict the therapeutic drugs related to severe cases. The expression profile of GSE166424 was divided into four data sets according to different clinical types of COVID-19 and then calculated the differential expression genes (DEGs). The specific genes of four clinical types of COVID-19 were obtained by Venn diagram and conducted enrichment analysis, protein-protein interaction (PPI) networks analysis, screening hub genes, and ROC curve analysis. The hub genes related to severe cases were verified in GSE171110, their RNA-specific expression tissues were obtained from the HPA database, and potential therapeutic drugs were predicted through the DGIdb database. There were 536, 266, 944, and 506 specific genes related to asymptomatic infections, mild, moderate, and severe cases, respectively. The hub genes of severe specific genes were AURKB, BRCA1, BUB1, CCNB1, CCNB2, CDC20, CDC6, KIF11, TOP2A, UBE2C, and RPL11, and also differentially expressed in GSE171110 (P < 0.05), and their AUC values were greater than 0.955. The RNA tissue specificity of AURKB, CDC6, KIF11, UBE2C, CCNB2, CDC20, TOP2A, BUB1, and CCNB1 specifically enhanced on lymphoid tissue; CCNB2, CDC20, TOP2A, and BUB1 specifically expressed on the testis. Finally, 55 drugs related to severe COVID-19 were obtained from the DGIdb database. Summary, AURKB, BRCA1, BUB1, CCNB1, CCNB2, CDC20, CDC6, KIF11, TOP2A, UBE2C, and RPL11 may be potential diagnostic biomarkers for severe COVID-19, which may affect immune and male reproductive systems. 55 drugs may be potential therapeutic drugs for severe COVID-19.

The status of emotional labour and its influence on job burnout among village doctors during the COVID-19 pandemic in China: a cross-sectional study.

BACKGROUND: Village doctors in China are not only the gatekeepers of rural residents' health but also the net bottom of the medical security system. However, emotional labour is increasingly threatening the stability of the rural primary medical system. In addition, the ongoing coronavirus disease 2019 (COVID-19) pandemic has further exposed the vulnerability of human resources in China's rural health system. This study aims to evaluate the current situation of emotional labour among village doctors and explore the impact of emotional labour on job burnout during the COVID-19 pandemic in China. METHODS: A cross-sectional survey was conducted in December 2021 in Shandong Province. We used structured questionnaires to collect data, including sociodemographic characteristics, emotional labour, and job burnout. Data were analysed by t test, analysis of variance (ANOVA), Pearson correlation analysis, and hierarchical multiple linear regression. RESULTS: A total of 1,093 village doctors from Shandong Province participated in the study. More than half of the participants were male (62.40%) and were between 41 and 50 years old (53.43%). The total mean score of emotional labour was 3.17 ± 0.67, of which the surface acting (SA) score was 2.28 ± 0.90, and the deep acting (DA) score was 3.91 ± 0.93. There were significant differences in SA according to gender and work content (P < 0.05) and in DA according to gender, age, education level, and work content (P < 0.05). Pearson correlation analysis showed that SA was positively correlated with job burnout (P < 0.001), and DA was negatively correlated with job burnout (P < 0.001). Hierarchical multiple linear regression analysis revealed that 29% of the variance in job burnout is attributable to SA (ß = 0.530, P < 0.001) and DA (ß = -0.154, P < 0.001). CONCLUSION: Village doctors in Shandong Province performed moderate levels of emotional labour during the COVID-19 pandemic. SA had a significant positive effect on job burnout, while DA had a significant negative effect on job burnout among village doctors. Administrators should enhance training on emotional labour for village doctors to play a positive role in alleviating their job burnout.

Genomic monitoring of SARS-CoV-2 uncovers an Nsp1 deletion variant that modulates type I interferon response.

The SARS-CoV-2 virus, the causative agent of COVID-19, is undergoing constant mutation. Here, we utilized an integrative approach combining epidemiology, virus genome sequencing, clinical phenotyping, and experimental validation to locate mutations of clinical importance. We identified 35 recurrent variants, some of which are associated with clinical phenotypes related to severity. One variant, containing a deletion in the Nsp1-coding region (Δ500-532), was found in more than 20% of our sequenced samples and associates with higher RT-PCR cycle thresholds and lower serum IFN-ß levels of infected patients. Deletion variants in this locus were found in 37 countries worldwide, and viruses isolated from clinical samples or engineered by reverse genetics with related deletions in Nsp1 also induce lower IFN-ß responses in infected Calu-3 cells. Taken together, our virologic surveillance characterizes recurrent genetic diversity and identified mutations in Nsp1 of biological and clinical importance, which collectively may aid molecular diagnostics and drug design.