A fast RT-qPCR system significantly shortens the time for SARS-CoV-2 nucleic acid test.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a serious threat to global development. Rapid and accurate diagnosis is critical for containing the pandemic and treating patients in time. As the gold standard for SARS-CoV-2 diagnosis, the qualitative reverse transcription-PCR (RT-qPCR) test has long been criticized for its long detection time. In this study, we optimized the primers and probes targeting SARS-CoV-2 ORF1ab and N gene designed by the Chinese Center for Disease Control and Preventions (CDC) to increase their Tm values to meet the optimal elongation temperature of Taq DNA polymerase, thus greatly shortened the elongation time. The higher elongation temperature in turn narrowed the temperature range of the reaction and saved more time. In addition, by shortening the distance between the fluorophore at the 5' end and the quencher in the middle we got a probe with higher signal-to-noise ratio. Finally, by using all these measures and optimized RT-qPCR program we successfully reduced the time (nucleic acid extraction step is not included) for nucleic acid test from 74 min to 26 min.

Quantitative determination of the electron beam radiation dose for SARS-CoV-2 inactivation to decontaminate frozen food packaging.

The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from cold-chain foods to frontline workers poses a serious public health threat during the current global pandemic. There is an urgent need to design concise approaches for effective virus inactivation under different physicochemical conditions to reduce the risk of contagion through viral contaminated surfaces of cold-chain foods. By employing a time course of electron beam exposure to a high titer of SARS-CoV-2 at cold-chain temperatures, a radiation dose of 2 â€‹kGy was demonstrated to reduce the viral titer from 104.5 to 0 median tissue culture infectious dose (TCID50)/mL. Next, using human coronavirus OC43 (HCoV-OC43) as a suitable SARS-CoV-2 surrogate, 3 â€‹kGy of high-energy electron radiation was defined as the inactivation dose for a titer reduction of more than 4 log units on tested packaging materials. Furthermore, quantitative reverse transcription PCR (RT-qPCR) was used to test three viral genes, namely, E, N, and ORF1ab. There was a strong correlation between TCID50 and RT-qPCR for SARS-CoV-2 detection. However, RT-qPCR could not differentiate between the infectivity of the radiation-inactivated and nonirradiated control viruses. As the defined radiation dose for effective viral inactivation fell far below the upper safe dose limit for food processing, our results provide a basis for designing radiation-based approaches for the decontamination of SARS-CoV-2 in frozen food products. We further demonstrate that cell-based virus assays are essential to evaluate the SARS-CoV-2 inactivation efficiency for the decontaminating strategies.

Food Security: 3D Dynamic Display and Early Warning Platform Construction and Security Strategy.

Since it affects a nation's economy and people's wellbeing, food security is a crucial national security requirement. In order to realize multi-angle grain data presentation and analysis and achieve the goal of deep mining, we propose a 3D dynamic visualization analysis method of multidimensional agricultural spatial-temporal data based on the self-organizing map. This method realizes the multi-angle display and analysis of grain data and achieves the purpose of deep mining. With the outbreak of COVID-19, the global food security situation is not optimistic, so it is necessary to use the food security early warning system to solve the food security issue. Machine learning has emerged widely in recent years and has been applied in various fields. Therefore, it is an excellent way to solve food security to apply the model in machine learning to construct a food security early warning system. Afterward, a food security early warning platform is developed with a support vector regression (SVR) model to ensure food security. Finally, we analyze China's medium and long-term food security policy in line with modernization objectives. The experimental results show that the food security early warning platform based on the SVR model from 2007 to 2016 is effective compared with the actual situation every year. Through analyses, we should improve the stability, reliability, and sustainability of food supply, firmly hold the food security initiative, and construct a national food security guarantee system matching the goal of modernization.

Epidemiological monitoring to ascertain if SARS-CoV-2 infects dogs and cats

2019 novel coronavirus (SARS-CoV-2) is a new strain of coronavirus that has never been found in humans. SARS-CoV-2 is a beta coronavirus. whereas the coronaviruses infecting pet dogs and cats arise mainly from a-coronaviruses. Whether SARS-CoV-2 infects cats, dogs and other pets is an important public-health issue during this time. In the present study, respiratory-tract symptoms in 20 pet cats and 4 pet dogs (especially with obvious fever and cough symptoms) in Beijing, China, were detected by fluorescence quantitative polymerase chain reaction (PCR) of SARS-CoV-2 and established diagnostic methods. Throat swabs were collected to detect the nucleic acids of SARS-CoV-2 using fluorescence quantitative PCR and to detect other pathogens. The nucleic acids of SARS-CoV-2 were not present in the 24 pets that we evaluated.

The Influence of Relational Capital on the Sustainability Risk: Findings from Chinese Non-State-Owned Manufacturing Enterprises

During the COVID-19 pandemic, the global economy fluctuated while the Chinese economy remained relatively stable-a distinction that has aroused people's curiosity about the unique operation of Chinese enterprises. Compared with the regularity and competitiveness of traditional market strategy theory, Chinese business management pays more attention to informal institutions and relational capital, which is one of the key features that distinguishes Chinese firms from their Western counterparts. Yet, theoretical research on relational capital against the Chinese cultural background remains scarce, and the particularity laws of the socialist market economy are still unclear. Based on the social capital theory, this paper redefines the concept of relational capital in the context of China and uses factor analysis to construct a relational capital measurement index. On this basis, non-state-owned manufacturing enterprises are then used as a sample to explore the interactive relationship between relational capital and sustainability risk. The empirical results show that relational capital can effectively reduce sustainability risk and ensure sustainable operation. In addition, enterprise growth, enterprise development, and marketization can strengthen the role of relational capital and positively regulate the relationship between relational capital and sustainability risk. This paper innovatively constructs the concept and index system of relational capital in the Chinese context, which is the perfection of relational capital theory. At the same time, it verifies the impact of relational capital on business sustainability, revises the correct cognition of relational capital, and supplements the deficiencies of the extant social socialist market economy research. Supported by both theoretical research and empirical conclusions, corresponding management suggestions are put forward for enterprises, governments, and managers to scientifically guide management practice and provide new ideas for future Chinese-style economic research.

Spatiotemporal evolution of NO2 diffusion in Beijing in response to COVID-19 lockdown using complex network.

The COVID-19 pandemic and the corresponding lockdown measures have been confirmed to reduce the air pollution in major megacities worldwide. Especially at some monitoring hotspots, NO2 has been verified to show a significant decrease. However, the diffusion pattern of these hotspots in responding to COVID-19 is not clearly understood at present stage. Hence, we selected Beijing, a typical megacity with the strictest lockdown measures during COVID-19 period, as the studied city and attempted to discover the NO2 diffusion process through complex network method. The improved metrics derived from the topological structure of the network were adopted to describe the performance of diffusion. Primarily, we found evidences that COVID-19 had significant effects on the spatial diffusion distribution due to combined effect of changed human activities and meteorological conditions. Besides, to further quantify the impacts of disturbance caused by different lockdown measures, we discussed the evolutionary diffusion patterns from lockdown period to recovery period. The results displayed that the difference between normal operation and pandemic operation firstly increased at the cutoff of lockdown measures but then declined after the implement of recovery measures. The source areas had greater vulnerability and lower resilience than receptors areas. Furthermore, based on the conclusion that the diffusion pattern changed during different periods, we explored the key stations on the path of diffusion process to further gain information. These findings could provide references for comprehending spatiotemporal pattern on city scale, which might be help for high-resolution air pollution mapping and prediction.

Structure-Based Primer Design Minimizes the Risk of PCR Failure Caused by SARS-CoV-2 Mutations.

The coronavirus disease 2019 (COVID-19) has caused and is still causing tremendous damage to the global economy and human health. Qualitative reverse transcription-PCR (RT-qPCR) is the golden standard for COVID-19 test. However, the SARS-CoV-2 variants may not only make vaccine less effective but also evade RT-qPCR test. Here we suggest an innovative primer design strategy for the RT-qPCR test of SARS-CoV-2. The principle is that the primers should be designed based on both the nucleic acid sequence and the structure of the protein encoded. The three nucleotides closest to the 3' end of the primer should be the codon which encodes the tryptophan in the structure core. Based on this principle, we designed a pair of primers targeting the nucleocapsid (N) gene. Since tryptophan is encoded by only one codon, any mutation that occurs at this position would change the amino acid residue, resulting in an unstable N protein. This means that this kind of SARS-CoV-2 variant could not survive. In addition, both our data and previous reports all indicate that the mutations occurring at other places in the primers do not significantly affect the RT-qPCR result. Consequently, no SARS-CoV-2 variant can escape detection by the RT-qPCR kit containing the primers designed based on our strategy.

Characterizing the interruption-recovery patterns of urban air pollution under the COVID-19 lockdown in China.

The COVID-19 pandemic provides an opportunity to study the effects of urban lockdown policies on the variation in pollutant concentrations and to characterize the recovery patterns of urban air pollution under the interruption of COVID-19 lockdown policies. In this paper, interruption-recovery models and regression discontinuity design were developed to characterize air pollution interruption-recovery patterns and analyze environmental impacts of the COVID-19 lockdown, using air pollution data from four Chinese metropolises (i.e., Shanghai, Wuhan, Tianjin, and Guangzhou). The results revealed the air pollutant interruption-recovery curve represented by the three lockdown response periods (Level I, Level II and Level III) during COVID-19. The curve decreased during Level I (A 25.3%-48.8% drop in the concentration of NO2 has been observed in the four metropolises compared with the same period in 2018-2019.), then recovered around reopening, but decreased again during Level III. Moreover, the interruption-recovery curve of the year-on-year air pollution difference suggests a process of first decreasing during Level I and gradually recovering to a new equilibrium during Level III (e.g., the unit cumulative difference of NO2 mass concentrations in Shanghai was 21.7, 22.5, 11.3 (µg/m3) during Level I, II, and III and other metropolises shared similar results). Our findings reveal general trends in the air quality externality of different lockdown policies, hence could provide valuable insights into air pollutant interruption-recovery patterns and clear scientific guides for policymakers to estimate the effect of different lockdown policies on urban air quality.

Three epitope-distinct human antibodies from RenMab mice neutralize SARS-CoV-2 and cooperatively minimize the escape of mutants.

Coronavirus disease 2019 (COVID-19), a pandemic disease caused by the newly emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused more than 3.8 million deaths to date. Neutralizing antibodies are effective therapeutic measures. However, many naturally occurring mutations at the receptor-binding domain (RBD) have emerged, and some of them can evade existing neutralizing antibodies. Here, we utilized RenMab, a novel mouse carrying the entire human antibody variable region, for neutralizing antibody discovery. We obtained several potent RBD-blocking antibodies and categorized them into four distinct groups by epitope mapping. We determined the involved residues of the epitope of three representative antibodies by cryo-electron microscopy (Cryo-EM) studies. Moreover, we performed neutralizing experiments with 50 variant strains with single or combined mutations and found that the mixing of three epitope-distinct antibodies almost eliminated the mutant escape. Our study provides a sound basis for the rational design of fully human antibody cocktails against SARS-CoV-2 and pre-emergent coronaviral threats.

Association between IL-6 and severe disease and mortality in COVID-19 disease: a systematic review and meta-analysis.

BACKGROUND: So far, SARS-CoV-2 is the seventh coronavirus found to infect humans and cause disease with quite a strong infectivity. Patients diagnosed as severe or critical cases are prone to multiple organ dysfunction syndrome, acute respiratory distress syndrome and even death. Proinflammatory cytokine IL-6 has been reported to be associated with the severity of disease and mortality in patients with COVID-19. OBJECTIVE: This systematic review and meta-analysis were carried out to evaluate the association between IL-6 and severe disease and mortality in COVID-19 disease. METHODS: A systematic literature search using China National Knowledge Infrastructure, Wanfang databases, China Science and Technology Journal Database, Chinese Biomedical Literature, Embase, PubMed and Cochrane Central Register of Controlled Trials was performed from inception until 16 January 2021. RESULTS: 12 studies reported the value of IL-6 for predicting the severe disease in patients with COVID-19. The pooled area under the curve (AUC) was 0.85 (95% CI 0.821 to 0.931). 5 studies elaborated the predictive value of IL-6 on mortality. The pooled sensitivity, specificity and AUC were 0.15 (95% CI 0.13 to 0.17, I2=98.9%), 0.73 (95% CI 0.65 to 0.79, I2=91.8%) and 0.531 (95% CI 0.451 to 0.612), respectively. Meta-regression analysis showed that country, technique used, cut-off, sample, study design and detection time did not contribute to the heterogeneity of mortality. CONCLUSION: IL-6 is an adequate predictor of severe disease in patients infected with the COVID-19. The finding of current study may guide clinicians and healthcare providers in identifying potentially severe or critical patients with COVID-19 at the initial stage of the disease. Moreover, we found that only monitoring IL-6 levels does not seem to predict mortality and was not associated with COVID-19's mortality. PROSPERO REGISTRATION NUMBER: CRD42021233649.

Molecular basis of cross-species ACE2 interactions with SARS-CoV-2-like viruses of pangolin origin.

Pangolins have been suggested as potential reservoir of zoonotic viruses, including SARS-CoV-2 causing the global COVID-19 outbreak. Here, we study the binding of two SARS-CoV-2-like viruses isolated from pangolins, GX/P2V/2017 and GD/1/2019, to human angiotensin-converting enzyme 2 (hACE2), the receptor of SARS-CoV-2. We find that the spike protein receptor-binding domain (RBD) of pangolin CoVs binds to hACE2 as efficiently as the SARS-CoV-2 RBD in vitro. Furthermore, incorporation of pangolin CoV RBDs allows entry of pseudotyped VSV particles into hACE2-expressing cells. A screen for binding of pangolin CoV RBDs to ACE2 orthologs from various species suggests a broader host range than that of SARS-CoV-2. Additionally, cryo-EM structures of GX/P2V/2017 and GD/1/2019 RBDs in complex with hACE2 show their molecular binding in modes similar to SARS-CoV-2 RBD. Introducing the Q498H substitution found in pangolin CoVs into the SARS-CoV-2 RBD expands its binding capacity to ACE2 homologs of mouse, rat, and European hedgehog. These findings suggest that these two pangolin CoVs may infect humans, highlighting the necessity of further surveillance of pangolin CoVs.

Analysis of Risk Factors for Thromboembolic Events in 88 Patients with COVID-19 Pneumonia in Wuhan, China: A Retrospective Descriptive Report.

BACKGROUND Since the outbreak of COVID-19 in December 2019, there have been 96 623 laboratory-confirmed cases and 4784 deaths by December 29 in China. We aimed to analyze the risk factors and the incidence of thrombosis from patients with confirmed COVID-19 pneumonia. MATERIAL AND METHODS Eighty-eight inpatients with confirmed COVID-19 pneumonia were reported (31 critical cases, 33 severe cases, and 24 common cases). The thrombosis risk factor assessment, laboratory results, ultrasonographic findings, and prognoses of these patients were analyzed, and compared among groups with different severity. RESULTS Nineteen of the 88 cases developed DVT (12 critical cases, 7 severe cases, and no common cases). In addition, among the 18 patients who died, 5 were diagnosed with DVT. Positive correlations were observed between the increase in D-dimer level (≥5 µg/mL) and the severity of COVID-19 pneumonia (r=0.679, P<0.01), and between the high Padua score (≥4) and the severity (r=0.799, P<0.01). In addition, the CRP and LDH levels on admission had positive correlations with the severity of illness (CRP: r=0.522, P<0.01; LDH: r=0.600, P<0.01). A negative correlation was observed between the lymphocyte count on admission and the severity of illness (r=-0.523, P<0.01). There was also a negative correlation between the lymphocyte count on admission and mortality in critical patients (r=-0.499, P<0.01). Univariable logistic regression analysis showed that the occurrence of DVT was positively correlated with disease severity (crude odds ratio: 3.643, 95% CI: 1.218-10.896, P<0.05). CONCLUSIONS Our report illustrates that critically or severely ill patients have an associated high D-dimer value and high Padua score, and illustrates that a low threshold to screen for DVT may help improve detection of thromboembolism in these groups of patients, especially in asymptomatic patients. Our results suggest that early administration of prophylactic anticoagulant would benefit the prognosis of critical patients with COVID-19 pneumonia and would likely reduce thromboembolic rates.

Structural basis for bivalent binding and inhibition of SARS-CoV-2 infection by human potent neutralizing antibodies.

Neutralizing monoclonal antibodies (nAbs) to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) represent promising candidates for clinical intervention against coronavirus disease 2019 (COVID-19). We isolated a large number of nAbs from SARS-CoV-2-infected individuals capable of disrupting proper interaction between the receptor binding domain (RBD) of the viral spike (S) protein and the receptor angiotensin converting enzyme 2 (ACE2). However, the structural basis for their potent neutralizing activity remains unclear. Here, we report cryo-EM structures of the ten most potent nAbs in their native full-length IgG-form or in both IgG-form and Fab-form bound to the trimeric S protein of SARS-CoV-2. The bivalent binding of the full-length IgG is found to associate with more RBDs in the "up" conformation than the monovalent binding of Fab, perhaps contributing to the enhanced neutralizing activity of IgG and triggering more shedding of the S1 subunit from the S protein. Comparison of a large number of nAbs identified common and unique structural features associated with their potent neutralizing activities. This work provides a structural basis for further understanding the mechanism of nAbs, especially through revealing the bivalent binding and its correlation with more potent neutralization and the shedding of S1 subunit.

Impact of the COVID-19 lockdown on roadside traffic-related air pollution in Shanghai, China.

The outbreak of COVID-19 has significantly inhibited global economic growth and impacted the environment. Some evidence suggests that lockdown strategies have significantly reduced traffic-related air pollution (TRAP) in regions across the world. However, the impact of COVID-19 on TRAP on roadside is still not clearly understood. In this study, we assessed the influence of the COVID-19 lockdown on the levels of traffic-related air pollutants in Shanghai. The pollution data from two types of monitoring stations-roadside stations and non-roadside stations were compared and evaluated. The results show that NO2, PM2.5, PM10, and SO2 had reduced by ~30-40% at each station during the COVID-19 pandemic in contrast to 2018-2019. CO showed a moderate decline of 28.8% at roadside stations and 16.4% at non-roadside stations. In contrast, O3 concentrations increased by 30.2% at roadside stations and 5.7% at non-roadside stations. This result could be resulted from the declined NOx emissions from vehicles, which lowered O3 titration. Full lockdown measures resulted in the highest reduction of primary pollutants by 34-48% in roadside stations and 18-50% in non-roadside stations. The increase in O3 levels was also the most significant during full lockdown by 64% in roadside stations and 33% in non-roadside stations due to the largest decrease in NO2 precursors, which promote O3 formation. Additionally, Spearman's rank correlation coefficients between NO2 and other pollutants significantly decreased, while the values between NO2 and O3 increased at roadside stations.

Cross-species recognition of SARS-CoV-2 to bat ACE2.

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has emerged as a major threat to global health. Although varied SARS-CoV-2-related coronaviruses have been isolated from bats and SARS-CoV-2 may infect bat, the structural basis for SARS-CoV-2 to utilize the human receptor counterpart bat angiotensin-converting enzyme 2 (bACE2) for virus infection remains less understood. Here, we report that the SARS-CoV-2 spike protein receptor binding domain (RBD) could bind to bACE2 from Rhinolophus macrotis (bACE2-Rm) with substantially lower affinity compared with that to the human ACE2 (hACE2), and its infectivity to host cells expressing bACE2-Rm was confirmed with pseudotyped SARS-CoV-2 virus and SARS-CoV-2 wild virus. The structure of the SARS-CoV-2 RBD with the bACE2-Rm complex was determined, revealing a binding mode similar to that of hACE2. The analysis of binding details between SARS-CoV-2 RBD and bACE2-Rm revealed that the interacting network involving Y41 and E42 of bACE2-Rm showed substantial differences with that to hACE2. Bats have extensive species diversity and the residues for RBD binding in bACE2 receptor varied substantially among different bat species. Notably, the Y41H mutant, which exists in many bats, attenuates the binding capacity of bACE2-Rm, indicating the central roles of Y41 in the interaction network. These findings would benefit our understanding of the potential infection of SARS-CoV-2 in varied species of bats.

Factors that determine a Patient's willingness to physician selection in online healthcare communities: A trust theory perspective.

Health care users and patients are increasingly using online health communities to seek medical service, especially during the COVID-19 epidemic. The factors that determine the online trust between physicians and patients perplex the stakeholders for a long time. Based on the trust theory, this study explored the influence of physicians' personal quality and online reputation on patients' selection. A longitudinal panel data collection exercise, covering 11905 physicians on haodf. com, was conducted on May 20, 2018, May 22, 2019 and May 25, 2020. The random effect models are used to test our hypothesis. Results show that physicians' quality (competence, benevolence, and integrity) and online reputation (online reviews and online rating) can significantly affect patients' selection. Moreover, the physician's gender can enhance the influence of online reputation on patients' selection. As online healthcare community becomes an increasingly appealing channel for health, the frequency of the physician's quality information updating and the quality of online service are equally important to online physician-patient trust.

Prediction of the Severity of the Coronavirus Disease and Its Adverse Clinical Outcomes.

This study aims to investigate blood and biochemical laboratory findings in patients with severe coronavirus disease 2019 (COVID-19) and to develop a joint predictor for predicting the likelihood of severe COVID-19 and its adverse clinical outcomes and to provide more information for treatment. We collected the data of 88 patients with laboratory-confirmed COVID-19. Further, the patients were divided into a non-severe group and a critical group (including critically ill cases). Univariate analysis showed that the absolute lymphocyte count, albumin level, albumin/globulin ratio, lactate dehydrogenase level, interleukin-6 (IL-6) level, erythrocyte count, globulin level, blood glucose level, and age were significantly correlated with the severity of COVID-19. The multivariate binary logistic regression model revealed that age, absolute lymphocyte count, and IL-6 level were independent risk factors in patients with COVID-19. The receiver operating characteristic curve revealed that the combination of IL-6 level, absolute lymphocyte count, and age is superior to a single factor as predictors for severe COVID-19, regardless of whether it is in terms of the area under the curve or the prediction sensitivity and specificity. Early application is beneficial to early identification of critically ill patients and timing individual treatments to reduce mortality.

Broad host range of SARS-CoV-2 and the molecular basis for SARS-CoV-2 binding to cat ACE2.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of the recent pandemic COVID-19, is reported to have originated from bats, with its intermediate host unknown to date. Here, we screened 26 animal counterparts of the human ACE2 (hACE2), the receptor for SARS-CoV-2 and SARS-CoV, and found that the ACE2s from various species, including pets, domestic animals and multiple wild animals, could bind to SARS-CoV-2 receptor binding domain (RBD) and facilitate the transduction of SARS-CoV-2 pseudovirus. Comparing to SARS-CoV-2, SARS-CoV seems to have a slightly wider range in choosing its receptor. We further resolved the cryo-electron microscopy (cryo-EM) structure of the cat ACE2 (cACE2) in complex with the SARS-CoV-2 RBD at a resolution of 3 Å, revealing similar binding mode as hACE2 to the SARS-CoV-2 RBD. These results shed light on pursuing the intermediate host of SARS-CoV-2 and highlight the necessity of monitoring susceptible hosts to prevent further outbreaks.

Prediction of adverse clinical outcomes in patients with coronavirus disease 2019.

OBJECTIVE: This study aims to investigate blood and biochemical laboratory findings in patients with coronavirus disease (COVID-19) and analyze the potential predictors of poor outcome in patients with COVID-19. METHODS: The clinical, laboratory, and outcome data of 87 patients with COVID-19 were collected and retrospectively analyzed. Only data collected at the time of admission were used in the analysis for predictors of poor outcome. These patients were divided into two groups: the adverse prognosis group (36 patients) and the non-adverse prognosis group (51 patients). The adverse prognosis of COVID-19 patients was defined as admission to the intensive care unit or death. RESULTS: On the univariate analysis, age, white blood cell (WBC) count, neutrophil counts, lymphocytes count, neutrophils-to-lymphocytes ratio (NLR), interleukin-6, albumin-to-globulin ratio (AGR), albumin, lactate dehydrogenase, glutamyl transpeptidase, and blood glucose were found to be the significant predictors. On the multivariate analysis, the predictors of poor outcome of patients with COVID-19 were NLR (OR = 2.741, [95% CI = 1.02 ~ 7.35], P = .045) and IL-6 (OR = 1.405, [95% CI = 1.04 ~ 1.89, P = .025]). The receiver operating characteristic (ROC) curve revealed that the AUC of NLR, interleukin-6, pneumonia severity index (PSI) score, and Confusion-Urea-Respiratory Rate-Blood pressure-65 (CURB-65) score were 0.883, 0.852, 0.824, and 0.782, respectively. CONCLUSION: High interleukin-6 (6 pg/mL, cuff value) and NLR (4.48, cuff value) can be used to predict poor outcomes in patients with COVID-19 on admission, thus can serve as a beneficial tool for timely identifying COVID-19 patients prone to poor outcome and reduce patient mortality through early intervention.

Clinical and pathological investigation of severe COVID-19 patients

BACKGROUND: Severe acute respiratory coronavirus 2 (SARS-CoV-2) caused coronavirus disease 2019 (COVID-19) has become a pandemic. This study addressed the clinical and immunopathological characteristics of severe COVID-19. METHODS: Sixty-nine COVID-19 patients were classified into as severe and non-severe groups to analyze their clinical and laboratory characteristics. A panel of blood cytokines was quantified over time. Biopsy specimens from two deceased cases were obtained for immunopathological, ultrastructural, and in situ hybridization examinations. RESULTS: Circulating cytokines, including IL8, IL6, TNFα, IP10, MCP1, and RANTES, were significantly elevated in severe COVID-19 patients. Dynamic IL6 and IL8 were associated with disease progression. SARS-CoV-2 was demonstrated to infect type II, type I pneumocytes and endothelial cells, leading to severe lung damage through cell pyroptosis and apoptosis. In severe cases, lymphopenia, neutrophilia, depletion of CD4+ and CD8+ T lymphocytes, and massive macrophage and neutrophil infiltrates were observed in both blood and lung tissues. CONCLUSIONS: A panel of circulating cytokines could be used to predict disease deterioration and inform clinical interventions. Severe pulmonary damage was predominantly attributed to both SARS-CoV-2 caused cytopathy and immunopathologic damage. Strategies that encourage pulmonary recruitment and overactivation of inflammatory cells by suppressing cytokine storm might improve the outcomes of severe COVID-19 patients.