SARS-CoV-2 Z-RNA activates the ZBP1-RIPK3 pathway to promote virus-induced inflammatory responses.

SARS-CoV-2 infection can trigger strong inflammatory responses and cause severe lung damage in COVID-19 patients with critical illness. However, the molecular mechanisms by which the infection induces excessive inflammatory responses are not fully understood. Here, we report that SARS-CoV-2 infection results in the formation of viral Z-RNA in the cytoplasm of infected cells and thereby activates the ZBP1-RIPK3 pathway. Pharmacological inhibition of RIPK3 by GSK872 or genetic deletion of MLKL reduced SARS-CoV-2-induced IL-1ß release. ZBP1 or RIPK3 deficiency leads to reduced production of both inflammatory cytokines and chemokines during SARS-CoV-2 infection both in vitro and in vivo. Furthermore, deletion of ZBP1 or RIPK3 alleviated SARS-CoV-2 infection-induced immune cell infiltration and lung damage in infected mouse models. These results suggest that the ZBP1-RIPK3 pathway plays a critical role in SARS-CoV-2-induced inflammatory responses and lung damage. Our study provides novel insights into how SARS-CoV-2 infection triggers inflammatory responses and lung pathology, and implicates the therapeutic potential of targeting ZBP1-RIPK3 axis in treating COVID-19.

An overview of COVID-19 aerosol box for preventing droplet and aerosol contaminations in healthcare providers performing airway intubation.

The COVID-19 is caused by the SARS-CoV-2, which is extremely infectious. Numerous virologist suggestions and guidelines advised using P2/N95 masks, gloves, goggles, face-shields, and frocks or gowns as routine specific protective tools during airway management to protect healthcare personnel from infection (PPE). However, numerous imitation research has indicated that conventional PPE cannot adequately protect healthcare personnel. Since then, numerous firms and healthcare professionals have created their personal reformed devices 'aerosol containment devices' (ACD). Their usage has expanded throughout the world without being properly evaluated for usefulness, efficacy, or safety. The practice of 'ACD' has been shown to make tracheal intubation (TI) more problematic in several simulated tests. Furthermore, the device should limit the transmission of droplets from a patient; however, it might put healthcare personnel at danger of being exposed to greater levels of viral aerosols. Consequently, the existing state of information suggests that 'ACD' deprived of a vacuum mechanism can simply protect healthcare personnel against viral transmission to a limited extent. We search various databases for the literature with keywords 'COVID-19,' 'aerosol box,' 'aerosol contaminations,' and 'droplet contaminations.' The current review focused on the aerosol box from various perspectives, including their mechanism, optimum time of use, the spread of aerosol control, current gaps, and future perspective for bridging those gaps.

ACE2-independent infection of T lymphocytes by SARS-CoV-2.

SARS-CoV-2 induced marked lymphopenia in severe patients with COVID-19. However, whether lymphocytes are targets of viral infection is yet to be determined, although SARS-CoV-2 RNA or antigen has been identified in T cells from patients. Here, we confirmed that SARS-CoV-2 viral antigen could be detected in patient peripheral blood cells (PBCs) or postmortem lung T cells, and the infectious virus could also be detected from viral antigen-positive PBCs. We next prove that SARS-CoV-2 infects T lymphocytes, preferably activated CD4 + T cells in vitro. Upon infection, viral RNA, subgenomic RNA, viral protein or viral particle can be detected in the T cells. Furthermore, we show that the infection is spike-ACE2/TMPRSS2-independent through using ACE2 knockdown or receptor blocking experiments. Next, we demonstrate that viral antigen-positive T cells from patient undergone pronounced apoptosis. In vitro infection of T cells induced cell death that is likely in mitochondria ROS-HIF-1a-dependent pathways. Finally, we demonstrated that LFA-1, the protein exclusively expresses in multiple leukocytes, is more likely the entry molecule that mediated SARS-CoV-2 infection in T cells, compared to a list of other known receptors. Collectively, this work confirmed a SARS-CoV-2 infection of T cells, in a spike-ACE2-independent manner, which shed novel insights into the underlying mechanisms of SARS-CoV-2-induced lymphopenia in COVID-19 patients.

Nursing ethics for prevention and control of major infectious disease outbreaks: Chinese expert consensus.

OBJECTIVES: Major infectious disease has become a serious threat to people's health worldwide. As the world's largest healthcare workforce and the core forces fighting against the epidemic, nurses are on the frontline of this battle. A number of ethical issues have given rise to numerous concerns that have largely affected nurses in different ways as they respond to the epidemic. In addition, excessive expectations from people can exert undue pressure, which can easily lead to burnout in nurses. METHODS: In this consensus, the expert panel method was used to develop and reach a consensus. The members involved in the formation of the consensus included an expert discussion panel and a consensus writing expert group, a methodologist, and four secretaries. After 16 rounds of online expert consultation and two rounds of expert panel meetings, the writing team analyzed and reviewed the 78 amendments suggested by the experts to develop a consensus on nursing ethics for prevention and control of major infectious disease outbreaks based on the ethical vision of life care. RESULTS: This expert consensus focuses on five essential domains: the responsibilities and rights of nurses, the nurse-patient relationship, the doctor-nurse relationship, and the relationship between society and nurses throughout the epidemic. CONCLUSIONS: We hope this consensus can help nurses better understand and respond to the ethical issues and challenges in public health emergencies, and raise reasonable public expectations of the roles and responsibilities of nurses in these situations.

Antibody-Dependent Enhancement of SARS-CoV-2 Infection of Human Immune Cells: In Vitro Assessment Provides Insight in COVID-19 Pathogenesis.

Patients with COVID-19 generally raise antibodies against SARS-CoV-2 following infection, and the antibody level is positively correlated to the severity of disease. Whether the viral antibodies exacerbate COVID-19 through antibody-dependent enhancement (ADE) is still not fully understood. Here, we conducted in vitro assessment of whether convalescent serum enhanced SARS-CoV-2 infection or induced excessive immune responses in immune cells. Our data revealed that SARS-CoV-2 infection of primary B cells, macrophages and monocytes, which express variable levels of FcγR, could be enhanced by convalescent serum from COVID-19 patients. We also determined the factors associated with ADE, and found which showed a time-dependent but not viral-dose dependent manner. Furthermore, the ADE effect is not associated with the neutralizing titer or RBD antibody level when testing serum samples collected from different patients. However, it is higher in a medium level than low or high dilutions in a given sample that showed ADE effect, which is similar to dengue. Finally, we demonstrated more viral genes or dysregulated host immune gene expression under ADE conditions compared to the no-serum infection group. Collectively, our study provides insight into the understanding of an association of high viral antibody titer and severe lung pathology in severe patients with COVID-19.

Machine learning based on clinical characteristics and chest CT quantitative measurements for prediction of adverse clinical outcomes in hospitalized patients with COVID-19.

OBJECTIVES: To develop and validate a machine learning model for the prediction of adverse outcomes in hospitalized patients with COVID-19. METHODS: We included 424 patients with non-severe COVID-19 on admission from January 17, 2020, to February 17, 2020, in the primary cohort of this retrospective multicenter study. The extent of lung involvement was quantified on chest CT images by a deep learning-based framework. The composite endpoint was the occurrence of severe or critical COVID-19 or death during hospitalization. The optimal machine learning classifier and feature subset were selected for model construction. The performance was further tested in an external validation cohort consisting of 98 patients. RESULTS: There was no significant difference in the prevalence of adverse outcomes (8.7% vs. 8.2%, p = 0.858) between the primary and validation cohorts. The machine learning method extreme gradient boosting (XGBoost) and optimal feature subset including lactic dehydrogenase (LDH), presence of comorbidity, CT lesion ratio (lesion%), and hypersensitive cardiac troponin I (hs-cTnI) were selected for model construction. The XGBoost classifier based on the optimal feature subset performed well for the prediction of developing adverse outcomes in the primary and validation cohorts, with AUCs of 0.959 (95% confidence interval [CI]: 0.936-0.976) and 0.953 (95% CI: 0.891-0.986), respectively. Furthermore, the XGBoost classifier also showed clinical usefulness. CONCLUSIONS: We presented a machine learning model that could be effectively used as a predictor of adverse outcomes in hospitalized patients with COVID-19, opening up the possibility for patient stratification and treatment allocation. KEY POINTS: • Developing an individually prognostic model for COVID-19 has the potential to allow efficient allocation of medical resources. • We proposed a deep learning-based framework for accurate lung involvement quantification on chest CT images. • Machine learning based on clinical and CT variables can facilitate the prediction of adverse outcomes of COVID-19.

COVID-19 infection in patients with connective tissue disease: A multicity study in Hubei province, China.

Novel Coronavirus disease 2019 (COVID-19) has spread rapidly around the world. Individuals with immune dysregulation and/or on immunosuppressive therapy, such as rheumatic patients, are considered at greater risk for infections. However, the risks of patients with each subcategory of rheumatic diseases have not been reported. Here, we identified 100 rheumatic patients from 18,786 COVID-19 patients hospitalized in 23 centers affiliated to Hubei COVID-19 Rheumatology Alliance between January 1 and April 1, 2020. Demographic information, medical history, length of hospital stay, classification of disease severity, symptoms and signs, laboratory tests, disease outcome, computed tomography, and treatments information were collected. Compared to gout and ankylosing spondylitis (AS) patients, patients with connective tissue disease (CTD) tend to be more severe after COVID-19 infection (p = 0.081). CTD patients also had lower lymphocyte counts, hemoglobin, and platelet counts (p values were 0.033, < 0.001, and 0.071, respectively). Hydroxychloroquine therapy and low- to medium-dose glucocorticoids before COVID-19 diagnosis reduced the progression of COVID-19 to severe/critical conditions (p = 0.001 for hydroxychloroquine; p = 0.006 for glucocorticoids). Our data suggests that COVID-19 in CTD patients may be more severe compared to patients with AS or gout.

Smart system of disease management for patient follow-up and medication refill during the COVID-19 epidemic period: a multicentre retrospective cohort study

Background An outbreak of coronavirus disease 2019 (COVID-19) started in December, 2019. The epicentre, Wuhan in Hubei Province, was in lockdown. From Jan 23, 2020, most hospitals in Wuhan only focused on patients with COVID-19, and patients with chronic diseases could not visit their physicians in clinic and had no access to prescriptions. Smart System of Disease Management (SSDM) is a series of mobile applications for chronic disease management that includes both patient and physician interfaces. After training in clinic, patients regularly do a disease activity assessment, and input data from lab tests as well as their medication. The data is then synchronised to the mobile of the responsible physician. The physician can then do an online consultation and renew prescriptions on the basis of real-time data from his or her patients. We aimed to establish the feasibility and effects of SSDM in maintaining effective interactions between patients and physicians in Hubei province during the COVID-19 epidemic period. Methods Based on the SSDM database, we did a multicentre retrospective cohort study of patients with rheumatic disease in Hubei province in China. SSDM had been widely used across China since 2015. To study the influence of interruption of routine care by the COVID-19 epidemic for patients with rheumatic disease, we included patients registered with SSDM from Hubei Province. Data on patient disease activities, online consultations, and prescription refilling, as well as surveys on satisfaction about the online service were extracted from Jan 23, 2020 to Feb 27, 2020, acting as the study group, and data from the same period during 2018 and 2019 were also extracted as a control. Inclusion criteria included a confirmed diagnosis of rheumatic disease and disease duration of at least 3 months. Patients were excluded from the study if they declined participation or discontinued before completion of the survey. For patients with rheumatoid arthritis, achieving a disease activity score with 28 joints (DAS28) of less than 3·2 was considered to be a treat-to-target (T2T) status. For patients with systemic lupus erythematosus, a disease activity index-2000 (SLESAI-2K) score of less than 4 was the main target of the lupus low disease-activity state (LLDAS). We compared the T2T and LLDAS prevalence during the epidemic period of 2020 with that of 2018 and 2019. All statistical analyses were done with Python version 3.7.4. We used descriptive and frequency statistics (percentage) to describe baseline demographic information and clinical information. Comparison of ratio variables between two groups was done with a χ2 test. Findings By Feb 27, 2020, a total of 173 560 adult patients (46 861 [27%] men and 126 699 [73%] women) with rheumatic disease from 860 hospitals across China registered and routinely used SSDM since 2015. Patients were encouraged to upload their data and do a disease activity self-assessment every 1–3 months. 10 441 (6%) of 173 560 patients (3237 [31%] with rheumatoid arthritis and 1566 [15%] with systemic lupus erythematosus) were managed by 176 rheumatologists from 42 hospitals in Hubei province. From Jan 23, 2020 to Feb 27, 2020, 69 rheumatologists from 28 hospitals provided 1451 patients with 1692 consultations and supplied 566 (39%) of them with continued medication, which included 55 commonly used therapeutic drugs for rheumatic diseases. 247 (8%) of 3237 patients with rheumatoid arthritis during the 2020 epidemic and 350 (9%) in same period during 2018 and 2019 did the DAS28 self-assessments, and T2T was 47% in 2020 compared with 50% in 2018 and 2019, (p=0·53). 293 (19%) of 1566 patients with systemic lupus erythematosus in 2020 and 210 (16%) in 2018 and 2019 did the SLESAI-2K self-assessments, and LLDAS was 60% in 2020 compared with 47% in 2018 and 2019 (p=0·03). Surveys showed that 100% of patients were satisfied with the interactions, which prevented the risk of cross-infection and discontinuation of medication. Interpretation Patients with rheumatism can maintain accessibility to good c re in the era of the COVID-19 epidemic by using SSDM for consultations and medication refills. The clinical outcomes, at least for both rheumatoid arthritis and systemic lupus erythematosus, are not compromised. Funding None.

SARS-CoV-2 triggers inflammatory responses and cell death through caspase-8 activation.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can lead to respiratory illness and multi-organ failure in critically ill patients. Although the virus-induced lung damage and inflammatory cytokine storm are believed to be directly associated with coronavirus disease 2019 (COVID-19) clinical manifestations, the underlying mechanisms of virus-triggered inflammatory responses are currently unknown. Here we report that SARS-CoV-2 infection activates caspase-8 to trigger cell apoptosis and inflammatory cytokine processing in the lung epithelial cells. The processed inflammatory cytokines are released through the virus-induced necroptosis pathway. Virus-induced apoptosis, necroptosis, and inflammation activation were also observed in the lung sections of SARS-CoV-2-infected HFH4-hACE2 transgenic mouse model, a valid model for studying SARS-CoV-2 pathogenesis. Furthermore, analysis of the postmortem lung sections of fatal COVID-19 patients revealed not only apoptosis and necroptosis but also massive inflammatory cell infiltration, necrotic cell debris, and pulmonary interstitial fibrosis, typical of immune pathogenesis in the lung. The SARS-CoV-2 infection triggered a dual mode of cell death pathways and caspase-8-dependent inflammatory responses may lead to the lung damage in the COVID-19 patients. These discoveries might assist the development of therapeutic strategies to treat COVID-19.

Clinical Factors Associated with Progression and Prolonged Viral Shedding in COVID-19 Patients: A Multicenter Study.

Coronavirus disease 2019 (COVID-19) is a global pandemic associated with a high mortality. Our study aimed to determine the clinical risk factors associated with disease progression and prolonged viral shedding in patients with COVID-19. Consecutive 564 hospitalized patients with confirmed COVID-19 between January 17, 2020 and February 28, 2020 were included in this multicenter, retrospective study. The effects of clinical factors on disease progression and prolonged viral shedding were analyzed using logistic regression and Cox regression analyses. 69 patients (12.2%) developed severe or critical pneumonia, with a higher incidence in the elderly and in individuals with underlying comorbidities, fever, dyspnea, and laboratory and imaging abnormalities at admission. Multivariate logistic regression analysis indicated that older age (odds ratio [OR], 1.04; 95% confidence interval [CI], 1.02-1.06), hypertension without receiving angiotensinogen converting enzyme inhibitors or angiotensin receptor blockers (ACEI/ARB) therapy (OR, 2.29; 95% CI, 1.14-4.59), and chronic obstructive pulmonary disease (OR, 7.55; 95% CI, 2.44-23.39) were independent risk factors for progression to severe or critical pneumonia. Hypertensive patients without receiving ACEI/ARB therapy showed higher lactate dehydrogenase levels and computed tomography (CT) lung scores at about 3 days after admission than those on ACEI/ARB therapy. Multivariate Cox regression analysis revealed that male gender (hazard ratio [HR], 1.22; 95% CI, 1.02-1.46), receiving lopinavir/ritonavir treatment within 7 days from illness onset (HR, 0.75; 95% CI, 0.63-0.90), and receiving systemic glucocorticoid therapy (HR, 1.79; 95% CI, 1.46-2.21) were independent factors associated with prolonged viral shedding. Our findings presented several potential clinical factors associated with developing severe or critical pneumonia and prolonged viral shedding, which may provide a rationale for clinicians in medical resource allocation and early intervention.

Characteristic of 523 COVID-19 in Henan Province and a Death Prediction Model.

Certain high-risk factors related to the death of COVID-19 have been reported, however, there were few studies on a death prediction model. This study was conducted to delineate the clinical characteristics of patients with coronavirus disease 2019 (covid-19) of different degree and establish a death prediction model. In this multi-centered, retrospective, observational study, we enrolled 523 COVID-19 cases discharged before February 20, 2020 in Henan Province, China, compared clinical data, screened for high-risk fatal factors, built a death prediction model and validated the model in 429 mild cases, six fatal cases discharged after February 16, 2020 from Henan and 14 cases from Wuhan. Out of the 523 cases, 429 were mild, 78 severe survivors, 16 non-survivors. The non-survivors with median age 71 were older and had more comorbidities than the mild and severe survivors. Non-survivors had a relatively delay in hospitalization, with higher white blood cell count, neutrophil percentage, D-dimer, LDH, BNP, and PCT levels and lower proportion of eosinophils, lymphocytes and albumin. Discriminative models were constructed by using random forest with 16 non-survivors and 78 severe survivors. Age was the leading risk factors for poor prognosis, with AUC of 0.907 (95% CI 0.831-0.983). Mixed model constructed with combination of age, demographics, symptoms, and laboratory findings at admission had better performance (p = 0.021) with a generalized AUC of 0.9852 (95% CI 0.961-1). We chose 0.441 as death prediction threshold (with 0.85 sensitivity and 0.987 specificity) and validated the model in 429 mild cases, six fatal cases discharged after February 16, 2020 from Henan and 14 cases from Wuhan successfully. Mixed model can accurately predict clinical outcomes of COVID-19 patients.

Early prediction of disease progression in COVID-19 pneumonia patients with chest CT and clinical characteristics.

The outbreak of coronavirus disease 2019 (COVID-19) has rapidly spread to become a worldwide emergency. Early identification of patients at risk of progression may facilitate more individually aligned treatment plans and optimized utilization of medical resource. Here we conducted a multicenter retrospective study involving patients with moderate COVID-19 pneumonia to investigate the utility of chest computed tomography (CT) and clinical characteristics to risk-stratify the patients. Our results show that CT severity score is associated with inflammatory levels and that older age, higher neutrophil-to-lymphocyte ratio (NLR), and CT severity score on admission are independent risk factors for short-term progression. The nomogram based on these risk factors shows good calibration and discrimination in the derivation and validation cohorts. These findings have implications for predicting the progression risk of COVID-19 pneumonia patients at the time of admission. CT examination may help risk-stratification and guide the timing of admission.

Real-time Screening of Specimen Pools for Coronavirus Disease 2019 (COVID-19) Infection at Sanya Airport, Hainan Island, China.

A 10:1 pooled test strategy on-site at an airport of China was pursued, resulting in increased test throughput, limited use of reagents, and increased testing efficiency without loss of sensitivity. This testing approach has the potential to reduce the need for contact tracing when the results are delivered first time.

COVID-19 in patients with rheumatic disease in Hubei province, China: a multicentre retrospective observational study.

BACKGROUND: In the ongoing COVID-19 pandemic, the susceptibility of patients with rheumatic diseases to COVID-19 remains unclear. We aimed to investigate susceptibility to COVID-19 in patients with autoimmune rheumatic diseases during the ongoing COVID-19 pandemic. METHODS: We did a multicentre retrospective study of patients with autoimmune rheumatic diseases in Hubei province, the epicentre of the COVID-19 outbreak in China. Patients with rheumatic diseases were contacted through an automated telephone-based survey to investigate their susceptibility to COVID-19. Data about COVID-19 exposure or diagnosis were collected. Families with a documented history of COVID-19 exposure, as defined by having at least one family member diagnosed with COVID-19, were followed up by medical professionals to obtain detailed information, including sex, age, smoking history, past medical history, use of medications, and information related to COVID-19. FINDINGS: Between March 20 and March 30, 2020, 6228 patients with autoimmune rheumatic diseases were included in the study. The overall rate of COVID-19 in patients with an autoimmune rheumatic disease in our study population was 0·43% (27 of 6228 patients). We identified 42 families in which COVID-19 was diagnosed between Dec 20, 2019, and March 20, 2020, in either patients with a rheumatic disease or in a family member residing at the same physical address during the outbreak. Within these 42 families, COVID-19 was diagnosed in 27 (63%) of 43 patients with a rheumatic disease and in 28 (34%) of 83 of their family members with no rheumatic disease (adjusted odds ratio [OR] 2·68 [95% CI 1·14-6·27]; p=0·023). Patients with rheumatic disease who were taking hydroxychloroquine had a lower risk of COVID-19 infection than patients taking other disease-modifying anti-rheumatic drugs (OR 0·09 [95% CI 0·01-0·94]; p=0·044). Additionally, the risk of COVID-19 was increased with age (adjusted OR 1·04 [95%CI 1·01-1·06]; p=0·0081). INTERPRETATION: Patients with autoimmune rheumatic disease might be more susceptible to COVID-19 infection than the general population. FUNDING: National Natural Science Foundation of China and the Tongji Hospital Clinical Research Flagship Program.