Tracking Live Virus by Targeting the Fusion Intermediate of Six-Helix Boundle Of SARS-CoV-2 (preprint)

Background: Molecular imaging specifically detecting SARS-CoV-2 in live subjects may aid theranostics for Coronavirus Disease 2019 (COVID-19). Herein, we developed novel molecular probes, Cy5-EK1 and [64 Cu]-NOTA-EK1, based on 36-mer EK1 peptide derived from the S2 subunit of spike (S) protein of SARS-CoV-2, an element of the six-helix bundle of S-protein for virus entry in vivoMethods: Enzyme-linked immunosorbent assay (ELISA) and immunostaining were performed to evaluate the potency of binding between these probes and recombinant full-length S-protein in vitro. HEK293 cells expressing S-protein of SARS-CoV-2 tumor-bearing mouse models were established to test the imaging target engagement in vivo.Findings: The potency of binding between NOTA-EK1 and S-protein was very strong, for which K d was 3.56 ± 0.38 nM and IC50 was 15.7 ± 0.6 nM. The uptake of [64Cu]-NOTA-EK1 in S-protein-positive tumors was greatly increased as early as 1 h post-injection and maintained at a high level until 24 h, while no signal was observed for S-protein-negative tumors. These differences were further confirmed by ex vivo imaging from both fluorescence and PET post-imaging studies. Immunofluorescent staining confirmed the colocalization of Cy5-EK1 with cell surface S-protein of SARS-CoV-2 in S-protein-positive HEK293 cells.Interpretation: Cy5-EK1 and [ 64Cu]-NOTA-EK1 could be used as specific molecular imaging probes for tracking SARS-CoV-2, which may have potential for the imaging and quantification of COVID-19 in a clinical context.Funding: This work was financially supported by the National Key R&D Program of China (2018YFC0910600).Declaration of Interest: None to declare. Ethical Approval: All animal experiments were carried out in accordance with the Institutional Ethical Guidelines for Animal Experiments of the Fifth Affiliated Hospital of Sun Yat-sen University(approval number: 00065).

Molecular Phenomics of Gut Ecosystem in COVID-19 Patients (preprint)

Background: Gut ecosystem has profound effects on host physiology and health. Gastrointestinal (GI) symptoms were frequently observed in patients with COVID-19. Compared with other organs, gut antiviral response can result in more complicated immune responses because of the interactions between the gut microbiota and host immunity. However, there are still large knowledge gaps in the impact of COVID-19 on gut molecular profiles and commensal microbiome, hindering our comprehensive understanding of the pathogenesis of SARS-CoV-2 and the treatment of COVID-19.Results: We performed longitudinal stool multi-omics profiling to systemically investigate the molecular phenomics alterations of gut ecosystem in COVID-19. Gut proteomes of COVID-19 were characterized by disturbed immune, proteolysis and redox homeostasis. The expression and glycosylation of proteins involved in neutrophil degranulation and migration were suppressed, while those of proteases were upregulated. The variable domains of Ig heavy chains were downregulated and the overall glycosylation of IgA heavy chain constant regions, IgGFc-binding protein, and J chain were suppressed with glycan-specific variations. There was a reduction of beneficial gut bacteria and an enrichment of bacteria derived deleterious metabolites potentially associated with multiple types of diseases (such as ethyl glucuronide). The reduction of Ig heave chain variable domains may contribute to the increase of some Bacteroidetes species. Many bacteria ceramide lipids with a C17-sphingoid based were downregulated in COVID-19. In many cases, the gut phenome did not restore two months after symptom onset.Conclusions: Our study indicates widely disturbed gut molecular profiles which may play a role in the development of symptoms in COVID-19. Our findings also emphasis the need for ongoing investigation of the long-term gut molecular and microbial alterations during COVID-19 recovery process. Considering the gut ecosystem as a potential target could offer a valuable approach in managing the disease.

A COVID-19 antibody curbs SARS-CoV-2 nucleocapsid protein-induced complement hyperactivation (preprint)

Although human antibodies elicited by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleocapsid (N) protein are profoundly boosted upon infection, little is known about the function of N-reactive antibodies. Herein, we isolated and profiled a panel of 32 N protein-specific monoclonal antibodies (mAbs) from a quick recovery coronavirus disease-19 (COVID-19) convalescent patient who had dominant antibody responses to the SARS-CoV-2 N protein rather than to the SARS-CoV-2 spike (S) protein. The complex structure of the N protein RNA binding domain with the mAb with the highest binding affinity (nCoV396) revealed changes in the epitopes and antigen’s allosteric regulation. Functionally, a virus-free complement hyper-activation analysis demonstrated that nCoV396 specifically compromises the N protein-induced complement hyper-activation, which is a risk factor for the morbidity and mortality of COVID-19 patients, thus laying the foundation for the identification of functional anti-N protein mAbs.

A comparative survey of betacoronavirus strain molecular dynamics identifies key ACE2 binding sites (preprint)

Comparative functional analysis of the binding interactions between various betacoronavirus strains and their potential human target proteins, such as ACE1, ACE2 and CD26, is critical to our future understanding and combating of COVID-19. Here, employing large replicate sets of GPU accelerated molecular dynamics simulations, we statistically compare atom fluctuations of the known human target proteins in both the presence and absence of different strains of the viral receptor binding domain (RBD) of the S spike glycoprotein. We identify a common interaction site between the N-terminal helices of ACE2 and the viral RBD in all strains (hCoV-OC43, hCoV-HKU1, MERS-CoV, SARS-CoV1, and SARS-CoV-2) and a second more dynamically complex RBD interaction site involving the ACE2 amino acid sites K353, Q325, and a novel motif, AAQPFLL (386-392) in the more recent cross-species spillovers (i.e. absent in hCoV-OC43). We use computational mutagenesis to further confirm the functional relevance of these sites. We propose a "one touch/two touch" model of viral evolution potentially involved in functionally facilitating binding interactions in zoonotic spillovers. We also observe these two touch sites governing RBD binding activity in simulations on hybrid models of the suspected viral progenitor, batCoV-HKU4, interacting with both the human SARS target, ACE2, and the human MERS target, CD26. Lastly, we confirm that the presence of a common hypertension drug (lisinopril) within the target site of SARS-CoV-2 bound models of ACE1 and ACE2 acts to enhance the RBD interactions at the same key sites in our proposed model. In the near future, we recommend that our comparative computational analysis identifying these key viral RBD-ACE2 binding interactions be supplemented with comparative studies of site-directed mutagenesis in order to screen for current and future coronavirus strains at high risk of zoonotic transmission to humans. STATEMENT OF SIGNIFICANCEWe generated structural models of the spike glycoprotein receptor binding domain from recent and past betacoronavirus outbreak strains aligned to the angiotensin 1 converting enzyme 2 protein, the primary target protein of the SARS-CoV-2 virus causing COVID 19. We then statistically compared computer simulated molecular dynamics of viral bound and unbound versions of each model to identify locations where interactions with each viral strain have dampened the atom fluctuations during viral binding. We demonstrate that all known strains of betacoronavirus are strongly interactive with the N-terminal helix region of ACE2. We also identify a more complex viral interaction with three novel sites that associates with more recent and deadly SARS strains, and also a bat progenitor strain HKU4.

A COVID-19 antibody curbs SARS-CoV-2 nucleocapsid protein-induced complement hyper-activation (preprint)

Although human antibodies elicited by severe acute respiratory distress syndrome coronavirus-2 (SARS-CoV-2) nucleocapsid (N) protein are profoundly boosted upon infection, little is known about the function of N-directed antibodies. Herein, we isolated and profiled a panel of 32 N protein-specific monoclonal antibodies (mAb) from a quick recovery coronavirus disease-19 (COVID-19) convalescent, who had dominant antibody responses to SARS-CoV-2 N protein rather than to Spike protein. The complex structure of N protein RNA binding domain with the highest binding affinity mAb nCoV396 reveals the epitopes and antigens allosteric changes. Functionally, a virus-free complement hyper-activation analysis demonstrates that nCoV396 specifically compromises N protein-induced complement hyper-activation, a risk factor for morbidity and mortality in COVID-19, thus paving the way for functional anti-N mAbs identification. One Sentence SummaryB cell profiling, structural determination, and protease activity assays identify a functional antibody to N protein.

Systematic evaluation of SARS-CoV-2 spike protein derived peptides for diagnosis of COVID-19 patients (preprint)

Serological test plays an essential role in monitoring and combating COVID-19 pandemic. Recombinant spike protein (S protein), especially S1 protein is one of the major reagents for serological tests. However, the high cost in production of S protein, and the possible cross-reactivity with other human coronaviruses poses unneglectable challenges. Taking advantage of a peptide microarray of full spike protein coverage, we analyzed 2,434 sera from 858 COVID-19 patients, sera from 63 asymptomatic patients and 610 controls collected from multiple clinical centers. Based on the results of the peptide microarray, we identified several S protein derived 12-mer peptides that have high diagnosis performance. Particularly, for monitoring IgG response, one peptide (aa 1148-1159 or S2-78) has a comparable sensitivity (95.5%, 95% CI 93.7-96.9%) and specificity (96.7%, 95% CI 94.8-98.0%) to that of S1 protein for detection of both COVID-19 patients and asymptomatic infections. Furthermore, the performance of S2-78 IgG for diagnosis was successfully validated by ELISA with an independent sample cohort. By combining S2-78/ S1 with other peptides, a two-step strategy was proposed to ensure both the sensitivity and specificity of S protein based serological assay. The peptide/s identified in this study could be applied independently or in combination with S1 protein for accurate, affordable, and accessible COVID-19 diagnosis.

Establishment of a clinical nomogram model to predict the progression of COVID-19 to severe disease (preprint)

Background Coronavirus disease 2019 (COVID-19) is a worldwide public health pandemic with a high mortality rate, among severe cases. The disease is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. It is important to ensure early detection of the virus to curb disease progression to severe COVID-19. This study aimed to establish a clinical-nomogram model to predict the progression to severe COVID-19 in a timely, efficient manner.Methods This retrospective study included 202 patients with COVID-19 who were admitted to the Fifth Affiliated Hospital of Sun Yat-sen University and Shiyan Taihe Hospital from January 17 to April 30, 2020. The patients were randomly assigned to the training dataset (n = 163, with 43 progressing to severe COVID-19) or the validation dataset (n = 39, with 10 progressing to severe COVID-19) at a ratio of 8:2. The optimal subset algorithm was applied to filter for the clinical factors most relevant to the disease progression. Based on these factors, the logistic regression model was fit to distinguish severe (including severe and critical cases) from non-severe (including mild and moderate cases) COVID-19. Sensitivity, specificity, and area under the curve (AUC) were calculated using the R software package to evaluate prediction performance. A clinical nomogram was established and performance assessed with the discrimination curve.Results Risk factors, including demographics data, symptoms, laboratory and image findings were recorded for the 202 patients. Eight of the 52 variables that were entered into the selection process were selected via the best subset algorithm to establish the predictive model; they included gender, age, BMI, CRP, D-dimer, TP, ALB, and involved-lobe. Sensitivity, specificity and AUC were 0.91, 0.84 and 0.86 for the training dataset, and 0.87, 0.66, and 0.80 for the validation dataset.Conclusions We established an efficient and reliable clinical nomogram model which showed that gender, age, and initial indexes including BMI, CRP, D-dimer, involved-lobe, TP, and ALB could predict the risk of progression to severe COVID-19.

Impact of Coronavirus Disease 2019 on Pulmonary Function in Early Convalescence Phase (preprint)

Objective: This study investigated the influence of Coronavirus Disease 2019 (COVID-19) on lung function in early convalescence phase. Methods: A prospective retrospective study of COVID-19 patients at the Fifth Affiliated Hospital of Sun Yat-sen University were conducted, with serial assessments including lung volumes (TLC), spirometry (FVC, FEV1), lung diffusing capacity for carbon monoxide (DLCO),respiratory muscle strength, 6-minute walking distance (6MWD) and high resolution CT being collected at 30 days after discharged. Results: 57 patients completed the serial assessments. There were 40 non-severe cases and 17 severe cases. Thirty-one patients (54.3%) had abnormal CT findings. Abnormalities were detected in the pulmonary function tests in 43 (75.4%) of the patients. Six (10.5%), 5(8.7%), 25(43.8%) 7(12.3%), and 30 (52.6%) patients had FVC, FEV1, FEV1/FVC ratio, TLC, and DLCO values less than 80% of predicted values, respectively. 28 (49.1%) and 13 (22.8%) patients had PImax and PEmax values less than 80% of the corresponding predicted values. Compared with non-severe cases, severe patients showed higher incidence of DLCO impairment (75.6%vs42.5%, p=0.019), higher lung total severity score（TSS）and R20, and significantly lower percentage of predicted TLC and 6MWD. No significant correlation between TSS and pulmonary function parameters was found during follow-up visit. Conclusion: Impaired diffusing-capacityDeclining DLCO, lower respiratory muscle strength, and lung imaging abnormalities were detected in more than half of the COVID-19 patients in early convalescence phase. Compared with non-severe cases, severe patients had a higher incidence of DLCO impairment and encountered more TLC decrease and 6MWD decline.

What is the Role of Chest CT Scan for Pediatric Patient Diagnosis of COVID-19? (preprint)

Objectives To retrospectively analyze the CT imaging features and patterns at baseline and as they evolve with time as the disease progresses or resolves in a cohort of pediatric patients affected with 2019 corona virus disease (COVID-19) pneumonia from three different cities in China.Methods We evaluated 29 pediatric patients with COVID-19 in the authors’ institution from Jan 1 to Feb 20, 2020. Cases were confirmed by laboratory test and were analyzed for epidemiological, demographic, clinical, radiological features and patterns.Results 29 initial scans and 23 follow-up scans were obtained from 29 patients. 15(52%) patients had been to Hubei Province and 26 (90%) of them had close contact with the COVID-19 positive patients in 14 days prior to the illness onset. The peak severity time was 5-8 days after symptom onset. A significant difference between the number of involved segments at different time points was indicated (p=0.019). Half (52%) of the laboratory confirmed patients had no CT positive findings. Nine (31%) of the laboratory confirmed patients had no symptoms. Six (21%) had no CT positive findings nor symptoms. All the patients of one center(n=6) whose fecal samples remained positive after the respiratory samples became negative.Conclusion The common positive CT findings included ground-glass opacities (50%), ground-glass opacities mixed with consolidation (36%), peribronchial thickening (21%), and consolidations (14%). We recommend for pediatric patients CT should not be used as a first-line test to diagnose COVID-19.

Preliminary evidence from a multicenter prospective observational study of the safety and efficacy of chloroquine for the treatment of COVID-19 (preprint)

Background Effective therapies are urgently needed for the SARS-CoV-2 pandemic. Chloroquine has been proved to have antiviral effect against coronavirus in vitro. In this study, we aimed to assess the efficacy and safety of chloroquine with different doses in COVID-19. Method In this multicenter prospective observational study, we enrolled patients older than 18 years old with confirmed SARS-CoV-2 infection excluding critical cases from 12 hospitals in Guangdong and Hubei Provinces. Eligible patients received chloroquine phosphate 500mg, orally, once (half dose) or twice (full dose) daily. Patients treated with non-chloroquine therapy were included as historical controls. The primary endpoint is the time to undetectable viral RNA. Secondary outcomes include the proportion of patients with undetectable viral RNA by day 10 and 14, hospitalization time, duration of fever, and adverse events. Results A total of 197 patients completed chloroquine treatment, and 176 patients were included as historical controls. The median time to achieve an undetectable viral RNA was shorter in chloroquine than in non-chloroquine (absolute difference in medians -6.0 days; 95% CI -6.0 to -4.0). The duration of fever is shorter in chloroquine (geometric mean ratio 0.6; 95% CI 0.5 to 0.8). No serious adverse events were observed in the chloroquine group. Patients treated with half dose experienced lower rate of adverse events than with full dose. Conclusions Although randomised trials are needed for further evaluation, this study provides evidence for safety and efficacy of chloroquine in COVID-19 and suggests that chloroquine can be a cost-effective therapy for combating the COVID-19 pandemic.

Artificial intelligence for rapid identification of the coronavirus disease 2019 (COVID-19) (preprint)

For diagnosis of COVID-19, a SARS-CoV-2 virus-specific reverse transcriptase polymerase chain reaction (RT-PCR) test is routinely used. However, this test can take up to two days to complete, serial testing may be required to rule out the possibility of false negative results, and there is currently a shortage of RT-PCR test kits, underscoring the urgent need for alternative methods for rapid and accurate diagnosis of COVID-19 patients. Chest computed tomography (CT) is a valuable component in the evaluation of patients with suspected SARS-CoV-2 infection. Nevertheless, CT alone may have limited negative predictive value for ruling out SARS-CoV-2 infection, as some patients may have normal radiologic findings at early stages of the disease. In this study, we used artificial intelligence (AI) algorithms to integrate chest CT findings with clinical symptoms, exposure history, and laboratory testing to rapidly diagnose COVID-19 positive patients. Among a total of 905 patients tested by real-time RT-PCR assay and next-generation sequencing RT-PCR, 419 (46.3%) tested positive for SARS-CoV-2. In a test set of 279 patients, the AI system achieved an AUC of 0.92 and had equal sensitivity as compared to a senior thoracic radiologist. The AI system also improved the detection of RT-PCR positive COVID-19 patients who presented with normal CT scans, correctly identifying 17 of 25 (68%) patients, whereas radiologists classified all of these patients as COVID-19 negative. When CT scans and associated clinical history are available, the proposed AI system can help to rapidly diagnose COVID-19 patients.

Key to successful treatment of COVID-19: accurate identification of severe risks and early intervention of disease progression (preprint)

Abstract Background COVID-19 is a new and highly contagious respiratory disease that has caused global spread, high case fatality rate in severe patients, and a huge medical burden due to invasive mechanical ventilation. The current diagnosis and treatment guidelines are still need to be improved, and more excellent clinical experience is needed to provide reference. Methods We analyzed and summarized clinical data of 97 confirmed COVID-19 adult patients (including 26 severe cases) admitted to the Fifth Affiliated Hospital of Sun Yat-sen University from January 17, 2020 to March 10, 2020,included laboratory examination results, imaging findings, treatment effect, prognosis , etc, in order to put forward prediction index of severe COVID-19 patients, principles of early intervention and methylprednisolone usages in COVID-19 patients. Results 1.Hypoxemia, hyperlactic acid, hypoproteinemia, and hypokalemia were prevalent in COVID-19 patients.The significant low lymphocyte count, hypoproteinemia, hypokalemia, the persistent or worsen high CRP, high D-dimer, and high BNP, and the occurrence of hemoptysis and novel coronavirus (SARS-CoV-2) viremia were important indicators for early diagnosis and prediction of severe disease progression. 2.Characteristic images of lung CT had a clear change in COVID - 19, Ground-glass opacity (GGO) and high-density linear combinations may indicate different pathological changes. Rapid lobular progression of GGO suggests the possibility of severe disease. 3.Basic principles of early intervention treatment of COVID-19: on the premise of no effective antiviral drugs, treatment is based on supportive and symptomatic therapy (albumin supplementation, supplement of potassium, supplement blood plasma, etc.) in order to maintain the stability of the intracellular environment and adequately reactivate body immunity to clean up SARS-CoV-2 . 4. According to severity, oxygenation index, body weight, age, underlying diseases, appropriate amount methylprednisolone application on severe/critical COVID-19 patients on demand, improved blood oxygen and reduced the utilization rate of invasive mechanical ventilation, case fatality rate and medical burden significantly. The most common indications for invasive mechanical ventilation should be strictly control in critical COVID-19 patients. Conclusions: 1.Accurate and timely identification of clinical features in severe risks, and early and appropriate intervention can block disease progression. 2.Appropriate dose of methylprednisolone can effectively avoid invasive mechanical ventilation and reduce case fatality rate in critical COVID-19 patients.

Diagnosis challenge of suspected COVID-19 pneumonia in cancer patients with radiation-induced pneumonitis (preprint)

Background During the outbreak period of COVID-19 pneumonia, cancer patients have been neglected and in greater danger. Furthermore, the differential diagnosis between COVID-19 pneumonia and radiation pneumonitis in caner patients remains a challenge. The study aimed to determine their clinical presentations and radiological features to familiarize radiologists and clinical teams with them in order to early diagnosis and prompt early patient isolation.Methods From January 21, 2019 to February 18, 2020, the patients selected consecutively met the following criteria: (i) presumed COVID-19 pneumonia; (ii) patients with a history of malignancy and lung exposure to ionizing radiation. A retrospective analysis including all patients’ presenting was performed.Results 4 patients from 112 suspected individals were selected, including 2 males and 2 females with a median age of 54 years (39–64 years). After repeated pharyngeal swab nucleic acid tests, 1 case was confirmed and 3 cases were excluded from COVID-19 pneumonia.Conclusions Despite the comparable morphologic characteristics of lung CT imaging, the location, extent, and distribution of lung lesions between COVID-19 pneumonia and radiation pneumonitis differ significantly, further combined with clinical and laboratory findings that could facilitate early diagnosis and appropriate management.

A high-efficiency hospital emergency-response mode is key to successful treatment of COVID-19 patients in Zhuhai (preprint)

Background: In December 2019, coronavirus disease 2019 (COVID-19) emerged in Wuhan and has since rapidly spread throughout China. The mortality rates of novel coronavirus pneumonia (NCP) in severe and critical cases are very high. In this public-health emergency, a high-efficiency administrative emergency-response mode in designated hospitals is needed. Method: As an affiliated hospital of Sun Yat-sen University, ours, the Fifth Affiliated Hospital, is the only one designated for the diagnosis and treatment of COVID-19 in Zhuhai, a mid-sized city. The NCP department, for which the president of the hospital is also the direct administrative lead, was established at an early stage of the epidemic at our hospital. This department includes core members of the pulmonary and critical-care medicine (PCCM) specialist and multidisciplinary team. Rather than adhering to national guidelines on NCP, we have focused on individualized treatment, timely adjustment thereof and management strategies in working with COVID-19 patients based on the professional opinions of a professor of respiratory medicine and an expert group. Results: (1) High working efficiency: As of March 2, 2020, we have completed 2974 citywide consultations and treatment of 366 inpatients, including 101 who were diagnosed with COVID-19. (2) Excellent therapeutic effect: Of the 101 patients hospitalized with confirmed COVID-19, only 1 has died, and the rest were all cured and discharged. No secondary hospital infection, pipeline infection or pressure sores were found in any patient. (3) Finding and confirming person-to-person transmission characteristic of COVID-19 prior to the official press conference: Strengthened protection is key to zero infection among the healthcare providers and medical faculty, as well as to a lower rate of second-generation infectious patients. (4) Timely adjustment of management and treatment strategy prior to guideline updates: The first evidence of digestive-tract involvement in COVID-19 has been found, and the earliest clinical trial of chloroquine in the treatment of the disease was carried out at our hospital. Conclusions: At our hospital, establishment of an NCP department, which is directly administered by the hospital president and specialized operation guided by a professor of respiratory medicine, has been key to our success in managing and treating COVID-19 patients. Our hospital’s emergency-response mode could provide a reference for other hospitals and cities in this epidemic situation.

A high efficient hospital emergency responsive mode is the key of successful treatment of 100 COVID-19 patients in Zhuhai (preprint)

Background: Since December 2019, Coronavirus Disease 2019 (COVID-19) emerged in Wuhan city and rapidly spread throughout China. The mortality of novel coronavirus pneumonia (NCP) in severe and critical cases is very high. Facing this kind of public health emergency, high efficient administrative emergency responsive mode in designated hospital is needed. Method: As an affiliated hospital of Sun Yat-sen University, our hospital is the only designated one for diagnosis and treatment of COVID-19 in Zhuhai, a medium-sized city. Novel coronavirus pneumonia department, which is administrative led by the president of hospital directly, has been established at early stage of epidemic crisis in my hospital. In NCP department, there are core members of Pulmonary and Critical Care Medicine (PCCM) specialist and multidisciplinary team. Don't stick to national guidelines of NCP, based on professional opinion by respiratory professor and expert group, we focused on individualized treatment and timely adjustment of treatment and management strategies in working about COVID-19 patients. Results: 1. High working efficiency: By Mar 02, 2020, we have completed 2974 citywide consultations and treatment of 366 inpatients, including 101 patients diagnosed with COVID-19. 2. Excellent therapeutic effectAmong 101 hospitalized patients with confirmed COVID-19, all were cured and discharged, except for one death. No secondary hospital infection, no pipeline infection and no pressure sore were found in all patients. 3. Finding and confirming person-to-person transmission characteristic of COVID-19 prior to official release conference: Strengthened protection is key point to zero infection in healthcare group and medical faculty and lower rate of second generation infectious patients. 4. Timely adjustment management and treatment strategy prior to guideline update: The first evidence of digestive tract involvement in COVID-19 has been found, and the earliest clinical trial of chloroquine in the treatment of COVID-19 has been carried out in our hospital. Conclusions: In our hospital, establishment of NCP department, which is administratively led by the president of hospital directly and specialized conduct by respiratory professor, is the key to success in management and treatment of COVID-19 patients. This hospital emergency responsive mode could provide reference for other hospitals and cities in epidemic situation.

Establishment of a clinical nomogram model to predict the progress to severe COVID-19 (preprint)

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is the leading cause of a public health emergency in the world, accompanying with high mortality in severe corona virus disease 2019(COVID-19 ), thereby early detection and stopping the progress to severe COVID-19 is important. Our aim is to establish a clinical nomogram model to calculate and predict the progress to severe COVID-19 timely and efficiently.Methods: In this study, 65 patients with COVID-19 had been included retrospectively in the Fifth Affiliated Hospital of Sun Yat-sen University from January 17, to February 11, 2020. Patients were randomly assigned to train dataset (n=51 with 15 progressing to severe COVID-19) and test dataset (n=14 with 4 progressing to severe COVID-19). Lasso algorithm was applied to filter the most classification relevant clinical factors. Based on selected factors, logistic regression model was fit to predict the severe from mild/common. Meanwhile in nomogram sensitivity, specificity, AUC (Area under Curve), and calibration curve were depicted and calculated by R language, to evaluate the prediction performance to severe COVID-19.Results:High ratio of sever COVID-19 patients (26.5%) had been found in our retrospective study, and 84% of these cases progress to severe or critical after 5 days from their first clinical examination. In these 65 patients with COVID-19, 77 clinical characteristics in first examination were collected and analyzed, and 37 ones had been found different between non-severe and severe COVID-19. But when all these factors were analyzed in establishment of prediction model, six factors are crucial for predicting progress of severe COVID-19 via Lasso algorithm. Based on these six factors, including increased fibrinogen, hyponatremia, decreased PaO2,multiple lung lobes involved, down-regulated CD3（+）T-lymphocyte and fever, a logistic regression model was fit to discriminate severe and common COVID-19 patients. The sensitivity, specificity and AUC were 0.93, 0.86, 0.96 in the train dataset and 0.9, 1.0, 1.0 in test dataset respectively. Nomogram-predicted probability was more consistent with actual probability by R language.Conclusions:In summary, an efficient and reliable clinical nomogram model had been established, which indicate increased fibrinogen, hyponatremia, decreased PaO2, multiple lung lobes involved, down-regulated CD3（+）T-lymphocyte and fever at the first clinical examination, could predict progress of patients to severe COVID-19.

Crystal structure of SARS-CoV-2 nucleocapsid protein RNA binding domain reveals potential unique drug targeting sites (preprint)

The outbreak of coronavirus disease (COVID-19) in China caused by SARS-CoV-2 virus continually lead to worldwide human infections and deaths. It is currently no specific viral protein targeted therapeutics yet. Viral nucleocapsid protein is a potential antiviral drug target, serving multiple critical functions during the viral life cycle. However, the structural information of SARS-CoV-2 nucleocapsid protein is yet to be clear. Herein, we have determined the 2.7 [A] crystal structure of the N-terminal RNA binding domain of SARS-CoV-2 nucleocapsid protein. Although overall structure is similar with other reported coronavirus nucleocapsid protein N-terminal domain, the surface electrostatic potential characteristics between them are distinct. Further comparison with mild virus type HCoV-OC43 equivalent domain demonstrates a unique potential RNA binding pocket alongside the {beta}-sheet core. Complemented by in vitro binding studies, our data provide several atomic resolution features of SARS-CoV-2 nucleocapsid protein N-terminal domain, guiding the design of novel antiviral agents specific targeting to SARS-CoV-2.