3044 Cases reveal important prognosis signatures of COVID-19 patients.

Critical patients and intensive care unit (ICU) patients are the main population of COVID-19 deaths. Therefore, establishing a reliable method is necessary for COVID-19 patients to distinguish patients who may have critical symptoms from other patients. In this retrospective study, we firstly evaluated the effects of 54 laboratory indicators on critical illness and death in 3044 COVID-19 patients from the Huoshenshan hospital in Wuhan, China. Secondly, we identify the eight most important prognostic indicators (neutrophil percentage, procalcitonin, neutrophil absolute value, C-reactive protein, albumin, interleukin-6, lymphocyte absolute value and myoglobin) by using the random forest algorithm, and find that dynamic changes of the eight prognostic indicators present significantly distinct within differently clinical severities. Thirdly, our study reveals that a model containing age and these eight prognostic indicators can accurately predict which patients may develop serious illness or death. Fourthly, our results demonstrate that different genders have different critical illness rates compared with different ages, in particular the mortality is more likely to be attributed to some key genes (e.g. ACE2, TMPRSS2 and FURIN) by combining the analysis of public lung single cells and bulk transcriptome data. Taken together, we urge that the prognostic model and first-hand clinical trial data generated in this study have important clinical practical significance for predicting and exploring the disease progression of COVID-19 patients.

Care patterns and Traditional Chinese Medicine constitution as factors of depression and anxiety in patients with systemic sclerosis: A cross-sectional study during the COVID-19 pandemic.

Objective: Care patterns and Traditional Chinese Medicine (TCM) constitution affects the emotion and health of patients with systemic sclerosis (SSc) while the prevalence of COVID-19 may aggravate such patients' emotion and health. We investigated the depression and anxiety levels of patients with SSc during the pandemic to identify the correlation between care patterns, TCM constitution, and patients' emotion. Materials and methods: This was a cross-sectional study. Patients with SSc and healthy individuals were surveyed using the patient health questionnaire-9, generalized anxiety disorder-7, and constitution in Chinese medicine questionnaire and a modified care pattern questionnaire. Factors correlated with depression and anxiety were screened using univariate and multivariate logistic regression analyses. Results: A total of 273 patients with SSc and 111 healthy individuals were included in the analysis. The proportion of patients with SSc who were depressed was 74.36%, who had anxiety was 51.65%, and who experienced disease progression during the pandemic was 36.99%. The proportion of income reduction in the online group (56.19%) was higher than that in the hospital group (33.33%) (P = 0.001). Qi-deficiency [adjusted odds ratio (OR) = 2.250] and Qi-stagnation (adjusted OR = 3.824) constitutions were significantly associated with depression. Remote work during the outbreak (adjusted OR = 1.920), decrease in income (adjusted OR = 3.556), and disease progression (P = 0.030) were associated with the occurrence of depression. Conclusion: Chinese patients with SSc have a high prevalence of depression and anxiety. The COVID-19 pandemic has changed the care patterns of Chinese patients with SSc, and work, income, disease progression, and change of medications were correlates of depression or anxiety in patients with SSc. Qi-stagnation and Qi-deficiency constitutions were associated with depression, and Qi-stagnation constitution was associated with anxiety in patients with SSc. Trial registration: http://www.chictr.org.cn/showproj.aspx?proj=62301, identifier ChiCTR2000038796.

Construction and application of COVID-19 infectors activity information knowledge graph.

During COVID-19 prevention and control, people need to be aware of the outbreak situation in their area to avoid being inconvenienced by the outbreak and even becoming infected. Thus, this project constructs a knowledge graph with COVID-19 infector activity information, by using the official flow information of the infected people from the provincial and municipal websites. This knowledge graph is the basis of the COVID-19 applications for tracing, visualization and reporting proposes. In the implementation process, we (1) collect a dataset with the information on COVID-19 cases from the prevention and control centers, (2) extract the entity elements with a Bert + BILSTM + CRF-based model, and (3) pre-process the dataset and construct a knowledge graph with manual annotation and human-based review. Finally, we use the knowledge graph to develop a web-based application to implement the question and answer, query, transmission path tracking and the "No.0" tracing infector functions.

Biopsy channel of the endoscope as a potential source of infectious droplets during GI endoscopy.

BACKGROUND AND AIMS: During endoscopy, droplets with the potential to transmit infectious diseases are known to emanate from a patient's mouth and anus, but they may also be expelled from the biopsy channel of the endoscope. The main goal of our study was to quantify droplets emerging from the biopsy channel during clinical endoscopy. METHODS: A novel light-scattering device was used to measure droplets emanating from the biopsy channel. An endoscopy model was created, and in vitro measurements were carried out during air insufflation, air and water suctioning, and the performance of biopsy sampling. Similar measurements were then made on patients undergoing endoscopy, with all measurements taking place over 2 days to minimize variation. RESULTS: During in vitro testing, no droplets were observed at the biopsy channel during air insufflation or air and water suctioning. In 3 of 5 cases, droplets were observed during biopsy sampling, mostly when the forceps were being removed from the endoscope. In the 22 patients undergoing routine endoscopy, no droplets were observed during air insufflation and water suctioning. Droplets were detected in 1 of 11 patients during air suctioning. In 9 of 18 patients undergoing biopsy sampling and 5 of 6 patients undergoing snare polypectomies, droplets were observed at the biopsy channel, mostly when instruments were being removed from the endoscope. CONCLUSIONS: We found that the biopsy channel may be a source of infectious droplets, especially during the removal of instruments from the biopsy channel. When compared with droplets reported from the mouth and anus, these droplets were larger in size and therefore potentially more infectious.

Mechanistic insights into SARS-CoV-2 epidemic via revealing the features of SARS-CoV-2 coding proteins and host responses upon its infection.

SUMMARY: There are seven known coronaviruses that infect humans: four mild coronaviruses, including HCoV-229E, HCoV-OC43, HCoV-NL63 and HCoV-HKU1, only cause mild respiratory diseases, and three severe coronaviruses, including SARS-CoV, MERS-CoV and SARS-CoV-2, can cause severe respiratory diseases even death of infected patients. Both infection and death caused by SARS-CoV-2 are still rapidly increasing worldwide. In this study, we demonstrate that viral coding proteins of SARS-CoV-2 have distinct features and are most, medium and least conserved with SARS-CoV, MERS-CoV and the rest four mild coronaviruses (HCoV-229E, HCoV-OC43, HCoV-NL63 and HCoV-HKU1), respectively. Moreover, expression of host responsive genes (HRG), HRG-enriched biological processes and HRG-enriched KEGG pathways upon infection of SARS-CoV-2 shows slightly overlapping with SARS-CoV and MERS-CoV but distinctive to the four mild coronaviruses. Interestingly, enrichment of overactivation of neutrophil by HRGs is only and commonly found in infections of severe SARS-CoV-2, SARS-CoV and MERS-CoV but not in the other four mild coronaviruses, and the related gene networks show different patterns. Clinical data support that overactivation of neutrophil for severe patients can be one major factor for the similar clinical symptoms observed in SARS-CoV-2 infection compared to infections of the other two severe coronavirus (SARS-CoV and MERS-CoV). Taken together, our study provides a mechanistic insight into SARS-CoV-2 epidemic via revealing the conserved and distinct features of SARS-CoV-2, raising the critical role of dysregulation of neutrophil for SARS-CoV-2 infection. AVAILABILITY AND IMPLEMENTATION: All data sources and analysis methods related to this manuscript are available in the methods, supplementary materials and GEO database (https://www.ncbi.nlm.nih.gov/geo/). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A metagenomic-based method to study hospital air dust resistome.

As a symbol of the defense mechanisms that bacteria have evolved over time, the genes that make bacteria resist antibiotics are overwhelmingly present in the environment. Currently, bacterial antibiotic resistance genes (ARGs) in the air are a serious concern. Previous studies have identified bacterial communities and summarized putative routes of transmissions for some dominant hospital-associated pathogens from hospital indoor samples. However, little is known about the possible indoor air ARG transportation. In this study, we mainly surveyed air-conditioner air dust samples under different airflow conditions and analyzed these samples using a metagenomic-based method. The results show air dust samples exhibited a complex resistome, and the average concentration is 0.00042 copies/16S rRNA gene, which is comparable to some other environments. The hospital air-conditioners can form resistome over time and accumulate pathogens. In addition, our results indicate that the Outpatient hall is one of the main ARG transmission sources, which can distribute ARGs to other departments (explains >80% resistome). We believe that the management should focus on ARG carrier genera such as Staphylococcus, Micrococcus, Streptococcus, and Enterococcus in this hospital and our novel evidence-based network strategy proves that plasmid-mediated ARG transfer can occur frequently. Overall, these results provide insights into the characteristics of air dust resistome and possible route for how ARGs are spread in air.