Automated Quantification of Pneumonia Infected Volume in Lung CT Images: A Comparison with Subjective Assessment of Radiologists.

OBJECTIVE: To help improve radiologists' efficacy of disease diagnosis in reading computed tomography (CT) images, this study aims to investigate the feasibility of applying a modified deep learning (DL) method as a new strategy to automatically segment disease-infected regions and predict disease severity. METHODS: We employed a public dataset acquired from 20 COVID-19 patients, which includes manually annotated lung and infections masks, to train a new ensembled DL model that combines five customized residual attention U-Net models to segment disease infected regions followed by a Feature Pyramid Network model to predict disease severity stage. To test the potential clinical utility of the new DL model, we conducted an observer comparison study. First, we collected another set of CT images acquired from 80 COVID-19 patients and process images using the new DL model. Second, we asked two chest radiologists to read images of each CT scan and report the estimated percentage of the disease-infected lung volume and disease severity level. Third, we also asked radiologists to rate acceptance of DL model-generated segmentation results using a 5-scale rating method. RESULTS: Data analysis results show that agreement of disease severity classification between the DL model and radiologists is >90% in 45 testing cases. Furthermore, >73% of cases received a high rating score (≥4) from two radiologists. CONCLUSION: This study demonstrates the feasibility of developing a new DL model to automatically segment disease-infected regions and quantitatively predict disease severity, which may help avoid tedious effort and inter-reader variability in subjective assessment of disease severity in future clinical practice.

Pre-Clinical Development of a Potent Neutralizing Antibody MW3321 With Extensive SARS-CoV-2 Variants Coverage.

Since the outbreak of the coronavirus disease 2019 (COVID-19) pandemic, several variants of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have emerged and have consistently replaced the previous dominant variant. Therapeutics against variants of SARS-CoV-2 are urgently needed. Ideal SARS-CoV-2 therapeutic antibodies would have high potency in viral neutralization against several emerging variants. Neutralization antibodies targeting SARS-CoV-2 could provide immediate protection after SARS-CoV-2 infection, especially for the most vulnerable populations. In this work, we comprehensively characterize the breadth and efficacy of SARS-CoV-2 RBD-targeting fully human monoclonal antibody (mAb) MW3321. MW3321 retains full neutralization activity to all tested 12 variants that have arisen in the human population, which are assigned as VOC (Variants of Concern) and VOI (Variants of Interest) due to their impacts on public health. Escape mutation experiments using replicating SARS-CoV-2 pseudovirus show that escape mutants were not generated until passage 6 for MW3321, which is much more resistant to escape mutation compared with another clinical staged SARS-CoV-2 neutralizing mAb MW3311. MW3321 could effectively reduce viral burden in hACE2-transgenic mice challenged with either wild-type or Delta SARS-CoV-2 strains through viral neutralization and Fc-mediated effector functions. Moreover, MW3321 exhibits a typical hIgG1 pharmacokinetic and safety profile in cynomolgus monkeys. These data support the development of MW3321 as a monotherapy or cocktail against SARS-CoV-2-related diseases.

One microRNA has the potential to target whole viral mRNAs in a given human coronavirus

MicroRNAs (miRNAs) can repress viral replication by targeting viral messenger RNA (mRNA), which makes them potential antiviral agents. The antiviral effects of miRNAs on infectious viruses have been explored extensively;however, recent studies mainly considered the action modes of miRNAs, neglecting another key factor, the molecular biology of viruses, which may be particularly important in the study of miRNA actions against a given virus. In this paper, the action modes of miRNAs and the molecular biology of viruses are jointly considered for the first time and based on the reported roles of miRNAs on viruses and human coronaviruses (HCoVs) molecular biology, the general and specific interaction modes of miRNAs-HCoVs are systematically reviewed. It was found that HCoVs transcriptome is a nested set of subgenomic mRNAs, sharing the same 5′ leader, 3′ untranslated region (UTR) and open reading frame (ORF). For a given HCoV, one certain miRNA with a target site in the 5′ leader or 3’ UTR has the potential to target all viral mRNAs, indicating tremendous antiviral effects against HCoVs. However, for the shared ORFs, some parts are untranslatable attributed to the translation pattern of HCoVs mRNA, and it is unknown whether the base pairing between the untranslated ORFs and miRNAs plays a regulatory effect on the local mRNAs where the untranslated ORFs are located;therefore, the regulatory effects of miRNAs with targets within the shared ORFs are complicated and need to be confirmed. Collectively, miRNAs may bepromising antiviral agents against HCoVs due to their intrinsically nested set of mRNAs, and some gaps are waiting to be filled. In this review, insight is provided into the exploration of miRNAs that can interrupt HCoVs infection.

One microRNA has the potential to target whole viral mRNAs in a given human coronavirus.

MicroRNAs (miRNAs) can repress viral replication by targeting viral messenger RNA (mRNA), which makes them potential antiviral agents. The antiviral effects of miRNAs on infectious viruses have been explored extensively; however, recent studies mainly considered the action modes of miRNAs, neglecting another key factor, the molecular biology of viruses, which may be particularly important in the study of miRNA actions against a given virus. In this paper, the action modes of miRNAs and the molecular biology of viruses are jointly considered for the first time and based on the reported roles of miRNAs on viruses and human coronaviruses (HCoVs) molecular biology, the general and specific interaction modes of miRNAs-HCoVs are systematically reviewed. It was found that HCoVs transcriptome is a nested set of subgenomic mRNAs, sharing the same 5' leader, 3' untranslated region (UTR) and open reading frame (ORF). For a given HCoV, one certain miRNA with a target site in the 5' leader or 3' UTR has the potential to target all viral mRNAs, indicating tremendous antiviral effects against HCoVs. However, for the shared ORFs, some parts are untranslatable attributed to the translation pattern of HCoVs mRNA, and it is unknown whether the base pairing between the untranslated ORFs and miRNAs plays a regulatory effect on the local mRNAs where the untranslated ORFs are located; therefore, the regulatory effects of miRNAs with targets within the shared ORFs are complicated and need to be confirmed. Collectively, miRNAs may bepromising antiviral agents against HCoVs due to their intrinsically nested set of mRNAs, and some gaps are waiting to be filled. In this review, insight is provided into the exploration of miRNAs that can interrupt HCoVs infection.

Pre-Clinical Development of a Potent Neutralizing Antibody MW3321 With Extensive SARS-CoV-2 Variants Coverage

Since the outbreak of the coronavirus disease 2019 (COVID-19) pandemic, several variants of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have emerged and have consistently replaced the previous dominant variant. Therapeutics against variants of SARS-CoV-2 are urgently needed. Ideal SARS-CoV-2 therapeutic antibodies would have high potency in viral neutralization against several emerging variants. Neutralization antibodies targeting SARS-CoV-2 could provide immediate protection after SARS-CoV-2 infection, especially for the most vulnerable populations. In this work, we comprehensively characterize the breadth and efficacy of SARS-CoV-2 RBD-targeting fully human monoclonal antibody (mAb) MW3321. MW3321 retains full neutralization activity to all tested 12 variants that have arisen in the human population, which are assigned as VOC (Variants of Concern) and VOI (Variants of Interest) due to their impacts on public health. Escape mutation experiments using replicating SARS-CoV-2 pseudovirus show that escape mutants were not generated until passage 6 for MW3321, which is much more resistant to escape mutation compared with another clinical staged SARS-CoV-2 neutralizing mAb MW3311. MW3321 could effectively reduce viral burden in hACE2-transgenic mice challenged with either wild-type or Delta SARS-CoV-2 strains through viral neutralization and Fc-mediated effector functions. Moreover, MW3321 exhibits a typical hIgG1 pharmacokinetic and safety profile in cynomolgus monkeys. These data support the development of MW3321 as a monotherapy or cocktail against SARS-CoV-2-related diseases.

Force application of laparoscopic surgeons under the impact of heavy personal protective equipment during COVID-19 pandemic.

Objective: Surgeons are required to wear heavy personal protective equipment while delivering care to patients during the COVID-19 pandemic. We examined the impact of wearing double gloves on surgeons' performance in laparoscopic surgery. Methods: Eleven surgeons-in-training at the Surgical Simulation Research Lab of the University of Alberta were recruited to perform laparoscopic cutting tasks in simulation while wearing none, one pair, and two pairs of surgical gloves. Forces applied to laparoscopic instruments were measured. Results: Wearing gloves prolonged task times (one pair of gloves: 301.6 ± 61.7 s; two pairs of gloves: 295.8 ± 65.3 s) compared with no gloves (241.7 ± 46.9 s; p = 0.043). Wearing double gloves increased cutting errors (20.4 ± 5.1 mm2) compared with wearing one pair of gloves (16.9 ± 5.5 mm2) and no gloves (14.4 ± 4.6 mm2; p = 0.030). Wearing gloves reduced the peak force (one pair of gloves: 2.4 ± 0.7 N; two pairs of gloves: 2.7 ± 0.6 N; no gloves: 3.4 ± 1.4 N; p = 0.049), and the total force (one pair of gloves: 10.1 ± 2.8 N; two pairs of gloves: 10.3 ± 2.6 N; no glove: 12.6 ± 1.9 N; p = 0.048) delivered onto laparoscopic scissors compared with wearing no glove. Conclusion: The combined effects of wearing heavy gloves and using tools reduced the touching sensation, which limited the surgeons' confidence in performing surgical tasks. Increasing practice in simulation is suggested to allow surgeons to overcome difficulties brought by personal protective equipment.

"An integrated system, three separated responsibilities", a new fever clinic management model, in prevention and control of novel coronavirus pneumonia.

BACKGROUND: Since December 2019, there have been many new cases of coronavirus pneumonia in Wuhan, Hubei Province, which has gradually spread throughout the country. AIM: To explore our hospital's innovative management system to ensure the efficient operation of fever clinics during the epidemic, since controlling the spread of disease is an important way to prevent and control the epidemic. METHODS: In total, 200 outpatients with fever at our hospital between November 2019 and July 2020 were selected and allocated into two groups. RESULTS: The fever clinic in our hospital operated smoothly, and infection with the novel coronavirus disease (COVID-19) has not been reported in our hospital. Additionally, we did not have any cases of missed diagnosis. The awareness regarding COVID-19 infection sources, transmission routes, early symptoms, and preventive measures was significantly higher in our fever clinic than in those of the pre-management group. CONCLUSION: "An integrated system, three separate responsibilities" ensured the efficient functioning of our fever outpatient clinic and early screening of COVID-19 cases, which effectively curbed the transmission of COVID-19 and hence prevented COVID-19 pneumonia epidemic in our hospital, ultimately achieving the maximum effect of epidemic prevention and control.

N501Y mutation of spike protein in SARS-CoV-2 strengthens its binding to receptor ACE2.

SARS-CoV-2 has been spreading around the world for the past year. Recently, several variants such as B.1.1.7 (alpha), B.1.351 (beta), and P.1 (gamma), which share a key mutation N501Y on the receptor-binding domain (RBD), appear to be more infectious to humans. To understand the underlying mechanism, we used a cell surface-binding assay, a kinetics study, a single-molecule technique, and a computational method to investigate the interaction between these RBD (mutations) and ACE2. Remarkably, RBD with the N501Y mutation exhibited a considerably stronger interaction, with a faster association rate and a slower dissociation rate. Atomic force microscopy (AFM)-based single-molecule force microscopy (SMFS) consistently quantified the interaction strength of RBD with the mutation as having increased binding probability and requiring increased unbinding force. Molecular dynamics simulations of RBD-ACE2 complexes indicated that the N501Y mutation introduced additional π-π and π-cation interactions that could explain the changes observed by force microscopy. Taken together, these results suggest that the reinforced RBD-ACE2 interaction that results from the N501Y mutation in the RBD should play an essential role in the higher rate of transmission of SARS-CoV-2 variants, and that future mutations in the RBD of the virus should be under surveillance.

A proof of concept for neutralizing antibody-guided vaccine design against SARS-CoV-2.

Mutations and transient conformational movements of the receptor binding domain (RBD) that make neutralizing epitopes momentarily unavailable present immune escape routes for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To mitigate viral escape, we developed a cocktail of neutralizing antibodies (NAbs) targeting epitopes located on different domains of spike (S) protein. Screening of a library of monoclonal antibodies generated from peripheral blood mononuclear cells of COVID-19 convalescent patients yielded potent NAbs, targeting the N-terminal domain (NTD) and RBD domain of S, effective at nM concentrations. Remarkably, a combination of RBD-targeting NAbs and NTD-binding NAbs, FC05, enhanced the neutralization potency in cell-based assays and an animal model. Results of competitive surface plasmon resonance assays and cryo-electron microscopy (cryo-EM) structures of antigen-binding fragments bound to S unveil determinants of immunogenicity. Combinations of immunogens, identified in the NTD and RBD of S, when immunized in rabbits and macaques, elicited potent protective immune responses against SARS-CoV-2. More importantly, two immunizations of this combination of NTD and RBD immunogens provided complete protection in macaques against a SARS-CoV-2 challenge, without observable antibody-dependent enhancement of infection. These results provide a proof of concept for neutralization-based immunogen design targeting SARS-CoV-2 NTD and RBD.

Personal Protective Equipment in COVID-19: Impacts on Health Performance, Work-Related Injuries, and Measures for Prevention.

OBJECTIVE: To assess impact of personal protective equipment (PPE) on healthcare providers (HCPs) in caring for COVID-19 patients. METHODS: A cross-sectional survey was conducted over 50 hospitals in China. Descriptive analyses and Chi-square tests were performed on the collected data. RESULTS: All 104 frontline HCPs report negative impacts of PPE on their clinical performance, 97% of them experienced discomfort and injuries caused by wearing PPE for long hours. Frontline HCPs provided suggestions to alleviate the negative impacts and to enhance communication between healthcare staff and patients. Two hundred eighty two non-frontline HCPs also revealed similar problems; however, we recorded a few discrepancies between answers given by frontline and non-frontline HCPs. CONCLUSIONS: Wearing PPE for long hours degrades health performance. Measures were suggested to improve the design of PPE for protecting HCPs and enhancing their services to COVID patients.

Inhalable nanovaccine with biomimetic coronavirus structure to trigger mucosal immunity of respiratory tract against COVID-19.

The COVID-19 pandemic caused by SARS-CoV-2 seriously threatens global public health. It has previously been confirmed that SARS-CoV-2 is mainly transmitted between people through "respiratory droplets". Therefore, the respiratory tract mucosa is the first barrier to prevent virus invasion. It is very important to stimulate mucosal immunity to protect the body from respiratory virus infection. Inspired by this, we designed a bionic-virus nanovaccine, which can induce mucosal immunity by nasal delivery to prevent virus infection from respiratory tract. The nanovaccine that mimic virosome is composed of poly(I:C) mimicking viral genetic material as immune adjuvant, biomimetic pulmonary surfactant (bio-PS) liposomes as capsid structure of virus and the receptor binding domains (RBDs) of SARS-CoV-2 as "spike" to completely simulate the structure of the coronavirus. The nanovaccine can be administered by inhaling to imitate the process of SARS-CoV-2 infection through the respiratory tract. Our results demonstrated that the inhalable nanovaccine with bionic virus-like structure has a stronger mucosal protective effect than routine muscle and subcutaneous inoculation. In particular, high titer of secretory immunoglobulin A (sIgA) was detected in respiratory secretions, which effectively neutralize the virus and prevent it from entering the body through the respiratory tract. Through imitating the structure and route of infection, this inhalable nanovaccine strategy might inspire a new approach to the precaution of respiratory viruses.

Improving the performance of CNN to predict the likelihood of COVID-19 using chest X-ray images with preprocessing algorithms.

OBJECTIVE: This study aims to develop and test a new computer-aided diagnosis (CAD) scheme of chest X-ray images to detect coronavirus (COVID-19) infected pneumonia. METHOD: CAD scheme first applies two image preprocessing steps to remove the majority of diaphragm regions, process the original image using a histogram equalization algorithm, and a bilateral low-pass filter. Then, the original image and two filtered images are used to form a pseudo color image. This image is fed into three input channels of a transfer learning-based convolutional neural network (CNN) model to classify chest X-ray images into 3 classes of COVID-19 infected pneumonia, other community-acquired no-COVID-19 infected pneumonia, and normal (non-pneumonia) cases. To build and test the CNN model, a publicly available dataset involving 8474 chest X-ray images is used, which includes 415, 5179 and 2,880 cases in three classes, respectively. Dataset is randomly divided into 3 subsets namely, training, validation, and testing with respect to the same frequency of cases in each class to train and test the CNN model. RESULTS: The CNN-based CAD scheme yields an overall accuracy of 94.5 % (2404/2544) with a 95 % confidence interval of [0.93,0.96] in classifying 3 classes. CAD also yields 98.4 % sensitivity (124/126) and 98.0 % specificity (2371/2418) in classifying cases with and without COVID-19 infection. However, without using two preprocessing steps, CAD yields a lower classification accuracy of 88.0 % (2239/2544). CONCLUSION: This study demonstrates that adding two image preprocessing steps and generating a pseudo color image plays an important role in developing a deep learning CAD scheme of chest X-ray images to improve accuracy in detecting COVID-19 infected pneumonia.

China's practice to prevent and control COVID-19 in the context of large population movement.

BACKGROUND: The emerging infectious disease, coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), poses a serious threat in China and worldwide. Challenged by this serious situation, China has taken many measures to contain its transmission. This study aims to systematically review and record these special and effective practices, in hope of benefiting for fighting against the ongoing worldwide pandemic. METHODS: The measures taken by the governments was tracked and sorted on a daily basis from the websites of governmental authorities (e.g. National Health Commission of the People's Republic of China). And the measures were reviewed and summarized by categorizations, figures and tables, showing an ever-changing process of combating with an emerging infectious disease. The population shift levels, daily local new diagnosed cases, daily mortality and daily local new cured cases were used for measuring the effect of the measures. RESULTS: The practices could be categorized into active case surveillance, rapid case diagnosis and management, strict follow-up and quarantine of persons with close contacts, and issuance of guidance to help the public understand and adhere to control measures, plus prompt and effective high-level policy decision, complete activation of the public health system, and full involvement of the society. Along with the measures, the population shift levels, daily local new diagnosed cases, and mortality were decreased, and the daily local new cured cases were increased in China. CONCLUSIONS: China's practices are effective in controlling transmission of SARS-CoV-2. Considering newly occurred situations (e.g. imported cases, work resumption), the control measures may be adjusted.