Spaceborne InSAR for Monitoring and Health Assessment of Historical Architectures: The Tianjin Case Study (preprint)

Recently, interferometry synthetic aperture radar (InSAR) technology has shown its capabilities to monitor the displacement of natural processes with millimeter accuracy. Nevertheless, there is limited InSAR research on the health assessment of historical architectures. In this paper, we firstly proposed a possible methodology aiming at health assessment of historical architectures using space-borne SAR data. The proposed strategy consists of extracting building deformation from Persistent Scatterer Interferometry (PSI)results with spatial analysis between a geographical database and geocoded Persistent Scatterer (PS) and Inverse Distance Weighted (IDW) interpolation, deriving assessment parameters of both angular angle () and unequal subsidence velocity (), finally comparing them with alarm value for health assessment. This method has been applied to the Heping District of Tianjin (China), which contains many historical architectures, and two important examples (the Bohai Building and the China Theater) in the region were selected for detailed analysis, through the use of a high-resolution satellite dataset. For these two buildings, after extracting and analyzing deformation, both of the assessment parameters (and ) were acquired, and the good health conclusions were acquired in the case of values smaller than the alarm thresholds, which were validated by the similar conclusion from in situ leveling records. Finally, both the deformation mechanism of two architectures and health assessment ability with InSAR were analyzed in detail for further application.

Structural Requirements and Plasticity of Receptor-Binding Domain in Human Coronavirus Spike

The most recent human coronaviruses including severe acute respiratory syndrome coronavirus-2 causing severe respiratory tract infection and high pathogenicity bring significant global public health concerns. Infections are initiated by recognizing host cell receptors by coronavirus spike protein S1 subunit, and then S2 mediates membrane fusion. However, human coronavirus spikes undergo frequent mutation, which may result in diverse pathogenesis and infectivity. In this review, we summarize some of these recent structural and mutational characteristics of RBD of human coronavirus spike protein and their interaction with specific human cell receptors and analyze the structural requirements and plasticity of RBD. Stability of spike protein, affinity toward receptor, virus fitness, and infectivity are the factors controlling the viral tropisms. Thus, understanding the molecular details of RBDs and their mutations is critical in deciphering virus evolution. Structural information of spike and receptors of human coronaviruses not only reveals the molecular mechanism of host–microbe interaction and pathogenesis but also helps develop effective drug to control these infectious pathogens and cope with the future emerging coronavirus outbreaks.

McAN: an ultrafast haplotype network construction algorithm (preprint)

Haplotype network is becoming popular due to its increasing use in analyzing genealogical relationships of closely related genomes. We newly proposed McAN, a minimum-cost arborescence based haplotype network con-struction algorithm, by considering mutation spectrum history (mutations in ancestry haplotype should be contained in descendant haplotype), node size (corresponding to sample count for a given node) and sampling time. McAN is two orders of magnitude faster than the state-of-the-art algorithms, making it suitable for analyzation of massive se-quences. Availability: Source code is written in C/C++ and available at https://github.com/Theory-Lun/McAN and https://ngdc.cncb.ac.cn/biocode/tools/BT007301 under the MIT license. The online web service of McAN is available at https://ngdc.cncb.ac.cn/ncov/online/tool/haplotype. SARS-CoV-2 dataset are available at https://ngdc.cncb.ac.cn/ncov/.

Preclinical Immunological Evaluation of an Intradermally Administered Heterologous Vaccine Against SARS-CoV-2 Variants (preprint)

The recent emergence of new variants in the COVID-19 pandemic has led to new requirements for vaccines, with a focus on the capacity of vaccines to elicit high levels of neutralizing antibodies with specific recognition of S antigen variants based on the characterized vaccines licensed for use. A new strategy involving a heterologous vaccine composed of one or two doses of inactivated vaccine and a boost with the S1 protein with mutations (K-S) administered via the intradermal route was designed in this work and was found to improve immune efficacy by increasing neutralizing antibody titers and promoting specific T cell responses against 5 variants of the RBD peptide. A viral challenge test with the B.1.617.2 (Delta) variant confirmed that the both schedules of “1+1” and “2+1” administration ensured a clinical protective effect against this strain. All of these results not only suggested the feasibility of our strategy for protecting against new variants but also provided a technical pathway to enhance the anamnestic immune response in the immunized population.

Purifying selection determines the short-term time dependency of evolutionary rates in SARS-CoV-2 and pH1N1 influenza (preprint)

High throughput sequencing enables rapid genome sequencing during infectious disease outbreaks and provides an opportunity to quantify the evolutionary dynamics of pathogens in near real-time. One difficulty of undertaking evolutionary analyses over short timescales is the dependency of the inferred evolutionary parameters on the timespan of observation. Here, we characterise the molecular evolutionary dynamics of SARS-CoV-2 and 2009 pandemic H1N1 (pH1N1) influenza during the first 12 months of their respective pandemics. We use Bayesian phylogenetic methods to estimate the dates of emergence, evolutionary rates, and growth rates of SARS-CoV-2 and pH1N1 over time and investigate how varying sampling window and dataset sizes affects the accuracy of parameter estimation. We further use a generalised McDonald-Kreitman test to estimate the number of segregating non-neutral sites over time. We find that the inferred evolutionary parameters for both pandemics are time-dependent, and that the inferred rates of SARS-CoV-2 and pH1N1 decline by ~50% and ~100%, respectively, over the course of one year. After at least 4 months since the start of sequence sampling, inferred growth rates and emergence dates remain relatively stable and can be inferred reliably using a logistic growth coalescent model. We show that the time-dependency of the mean substitution rate is due to elevated substitution rates at terminal branches which are 2-4 times higher than those of internal branches for both viruses. The elevated rate at terminal branches is strongly correlated with an increasing number of segregating non-neutral sites, demonstrating the role of purifying selection in generating the time-dependency of evolutionary parameters during pandemics.

Recommendations for control and prevention of infections for pediatric orthopedics during the epidemic period of COVID-19

The outbreak of Coronavirus Disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged and spread rapidly throughout the world. As of February 29, 2020, 79 389 cases of COVID-19 have been reported, and the outbreak is linked to 2838 deaths. The population is generally susceptible to the disease, and differences in incubation periods after infection exist among individuals. These two aspects of COVID-19 pose significant challenges to pediatric orthopedic diagnosis and treatment. As a dedicated center for managing pediatric cases of SARS-CoV-2 in Shanghai, our hospital has mobilized all branches and departments to undertake joint actions for scientific prevention and control, precise countermeasure and comprehensive anti-epidemic efforts. Combined with our experience, we have consulted the relevant national regulations and the latest research advances and have formulated the prevention and control measures of SARS-CoV-2 infection, including outpatient, emergency, inpatient and surgical cares, for clinical practices of pediatric orthopedics according to the physicochemical properties of SARS-CoV-2. It may serve as practical references and recommendations for managing SARS-CoV-2 infection in other pediatric specialties and in other hospitals.

Co-benefits of reducing PM2.5 and improving visibility by COVID-19 lockdown in Wuhan

The less improvement of ambient visibility suspects the government’s efforts on alleviating PM2.5 pollution. The COVID-19 lockdown reduced PM2.5 and increased visibility in Wuhan. Compared to pre-lockdown period, the PM2.5 concentration decreased by 39.0 μg m−3, dominated by NH4NO3 mass reduction (24.8 μg m−3) during lockdown period. The PM2.5 threshold corresponding to visibility of 10 km (PTV10) varied in 54–175 μg m−3 and an hourly PM2.5 of 54 μg m−3 was recommended to prevent haze occurrence. The lockdown measures elevated PTV10 by 9–58 μg m−3 as the decreases in PM2.5 mass scattering efficiency and optical hygroscopicity. The visibility increased by 107%, resulted from NH4NO3 extinction reduction. The NH4NO3 mass reduction weakened its mutual promotion with aerosol water and increased PM2.5 deliquescence humidity. Controlling TNO3 (HNO3 + NO3−) was more effective to reduce PM2.5 and improve visibility than NHx (NH3 + NH4+) unless the NHx reduction exceeded 11.7–17.5 μg m−3.

Dual roles of a novel oncolytic viral vector-based SARS-CoV-2 vaccine: preventing COVID-19 and treating tumor progression (preprint)

The ongoing coronavirus disease 2019 (COVID-19) pandemic is caused by infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Cancer patients are usually immunocompromised and thus are particularly susceptible to SARS-CoV-2 infection resulting in COVID-19. Although many vaccines against COVID-19 are being preclinically or clinically tested or approved, none have yet been specifically developed for cancer patients or reported as having potential dual functions to prevent COVID-19 and treat cancer. Here, we confirmed that COVID-19 patients with cancer have low levels of antibodies against the spike (S) protein, a viral surface protein mediating the entry of SARS-CoV-2 into host cells, compared with COVID-19 patients without cancer. We developed an oncolytic herpes simplex virus-1 vector-based vaccine named oncolytic virus (OV)-spike. OV-spike induced abundant anti-S protein neutralization antibodies in both tumor-free and tumor-bearing mice, which inhibit infection of VSV-SARS-CoV-2 and wild-type (WT) live SARS-CoV-2 as well as the B.1.1.7 variant in vitro. In the tumor-bearing mice, OV-spike also inhibited tumor growth, leading to better survival in multiple preclinical tumor models than the untreated control. Furthermore, OV-spike induced anti-tumor immune response and SARS-CoV-2-specific T cell response without causing serious adverse events. Thus, OV-spike is a promising vaccine candidate for both preventing COVID-19 and enhancing the anti-tumor response. One Sentence Summary A herpes oncolytic viral vector-based vaccine is a promising vaccine with dual roles in preventing COVID-19 and treating tumor progression

New development: Administrative accountability and early responses during public health crises—lessons from Covid-19 in China

The administrative accountability system in China has evolved during public health crises. By holding public officials accountable, the system hopes to improve their performance during emergencies. However, Covid-19 exposed an unexpected effect of the system. Instead of incentivizing public officials to take responsibility, it may have discouraged them from making timely, but potentially risky, decisions. Based on a holistic case analysis of the early response in Wuhan city, the authors demonstrate the lessons learnt and a way to improve the system. The case adds to an increasing academic literature on responsible risk-taking behaviours and decisions under uncertainties, extending the academic discussion by providing the critical contextual information for such behaviours and decisions in China.

Clinical significance of T-lymphocyte subsets in the treatment of COVID-19

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is widely spread due to its strong infectivity by close contact via droplets or skin touch. With fever or cough as the first symptom, some patients suffering from coronavirus disease 2019 (COVID-19) quickly progressed to serious condition, which severely threatened the health of patients. As immunodeficiency is a significant factor of the poor condition, the relationship between COVID-19 and T-lymphocyte subsets will be summarized. The paper is written to indicate the clinical significance of T-lymphocyte subsets in the monitoring and treatment of COVID-19. It is suggested that the subgroup levels of T-lymphocyte subsets should be dynamically monitored during the course of disease for better understanding the condition and taking positive intervention, which will provide guidance to control immune inflammatory cascade and hold back the development of critical situation.

Computational Study of Ions and Water Permeation and Transportation Mechanisms of the SARS-CoV-2 Pentameric E Protein Channel (preprint)

Coronavirus disease 2019 (COVID-19) is caused by a novel coronavirus (SARS-CoV-2) and represents the causative agent of a potentially fatal disease that is of public health emergency of international concern. Coronaviruses, including SARS-CoV-2, encode an envelope (E) protein, which is a small, hydrophobic membrane protein; the E protein of SARS-CoV-2 has high homology with that of severe acute respiratory syndrome coronavirus. (SARS-CoV) In this study, we provide insights into the function of the SARS-CoV-2 E protein channel and the ion and water permeation mechanisms on the basis of combined in silico methods. Our results suggest that the pentameric E protein promotes the penetration of monovalent ions through the channel. Analysis of the potential mean force (PMF), pore radius and diffusion coefficient reveals that Leu10 and Phe19 are the hydrophobic gates of the channel. In addition, the pore demonstrated a clear wetting/dewetting transition with monovalent cation selectivity under transmembrane voltage, which indicates that it is a hydrophobic voltage-dependent channel. Overall, these results provide structural-basis insights and molecular-dynamic information that are needed to understand the regulatory mechanisms of ion permeability in the pentameric SARS-CoV-2 E protein channel.

Clinical outcomes of 402 patients with COVID-2019 from a single center in Wuhan, China (preprint)

The SARS-CoV-2 outbreak is causing widespread infections and significant mortality. Previous studies describing clinical characteristics of the disease contained small cohorts from individual centers or larger series consisting of mixed cases from different hospitals. We report analyses of mortality and disease severity among 402 patients from a single hospital. The cohort included 297 patients with confirmed and 105 with suspected diagnosis. The latter group met the criteria for clinical diagnosis but nucleic acid tests results were initially interpreted as suspicious. Data were compared between genders and among different age groups. The overall case fatality is 5.2%. However, patients 70 years of age or older suffered a significantly higher mortality (17.8%), associated with more patients having severe or critical illness (57.5%). Patients 50 years of age or older had a mortality of 8.0%, and those younger than 50 years, 1.2%. Male patients had a mortality of 7.6% versus 2.9% in females.

A deep learning algorithm using CT images to screen for Corona Virus Disease (COVID-19) (preprint)

BackgroundThe outbreak of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV-2) has caused more than 2.5 million cases of Corona Virus Disease (COVID-19) in the world so far, with that number continuing to grow. To control the spread of the disease, screening large numbers of suspected cases for appropriate quarantine and treatment is a priority. Pathogenic laboratory testing is the gold standard but is time-consuming with significant false negative results. Therefore, alternative diagnostic methods are urgently needed to combat the disease. Based on COVID-19 radiographical changes in CT images, we hypothesized that Artificial Intelligences deep learning methods might be able to extract COVID-19s specific graphical features and provide a clinical diagnosis ahead of the pathogenic test, thus saving critical time for disease control. Methods and FindingsWe collected 1,065 CT images of pathogen-confirmed COVID-19 cases (325 images) along with those previously diagnosed with typical viral pneumonia (740 images). We modified the Inception transfer-learning model to establish the algorithm, followed by internal and external validation. The internal validation achieved a total accuracy of 89.5% with specificity of 0.88 and sensitivity of 0.87. The external testing dataset showed a total accuracy of 79.3% with specificity of 0.83 and sensitivity of 0.67. In addition, in 54 COVID-19 images that first two nucleic acid test results were negative, 46 were predicted as COVID-19 positive by the algorithm, with the accuracy of 85.2%. ConclusionThese results demonstrate the proof-of-principle for using artificial intelligence to extract radiological features for timely and accurate COVID-19 diagnosis. Author summaryTo control the spread of the COVID-19, screening large numbers of suspected cases for appropriate quarantine and treatment measures is a priority. Pathogenic laboratory testing is the gold standard but is time-consuming with significant false negative results. Therefore, alternative diagnostic methods are urgently needed to combat the disease. We hypothesized that Artificial Intelligences deep learning methods might be able to extract COVID-19s specific graphical features and provide a clinical diagnosis ahead of the pathogenic test, thus saving critical time. We collected 1,065 CT images of pathogen-confirmed COVID-19 cases along with those previously diagnosed with typical viral pneumonia. We modified the Inception transfer-learning model to establish the algorithm. The internal validation achieved a total accuracy of 89.5% with specificity of 0.88 and sensitivity of 0.87. The external testing dataset showed a total accuracy of 79.3% with specificity of 0.83 and sensitivity of 0.67. In addition, in 54 COVID-19 images that first two nucleic acid test results were negative, 46 were predicted as COVID-19 positive by the algorithm, with the accuracy of 85.2%. Our study represents the first study to apply artificial intelligence to CT images for effectively screening for COVID-19.

Epidemiological and clinical features of the 2019 novel coronavirus outbreak in China (preprint)

Our manuscript was based on surveillance cases of COVID-19 identified before January 26, 2020. As of February 20, 2020, the total number of confirmed cases in mainland China has reached 18 times of the number in our manuscript. While the methods and the main conclusions in our original analyses remain solid, we decided to withdraw this preprint for the time being, and will replace it with a more up-to-date version shortly. Should you have any comments or suggestions, please feel free to contact the corresponding author.

Early evaluation of the Wuhan City travel restrictions in response to the 2019 novel coronavirus outbreak (preprint)

Respiratory illness caused by a novel coronavirus (COVID-19) appeared in China during December 2019. Attempting to contain infection, China banned travel to and from Wuhan city on 23 January and implemented a national emergency response. Here we evaluate the spread and control of the epidemic based on a unique synthesis of data including case reports, human movement and public health interventions. The Wuhan shutdown slowed the dispersal of infection to other cities by an estimated 2.91 days (95%CI: 2.54-3.29), delaying epidemic growth elsewhere in China. Other cities that implemented control measures pre-emptively reported 33.3% (11.1-44.4%) fewer cases in the first week of their outbreaks (13.0; 7.1-18.8) compared with cities that started control later (20.6; 14.5-26.8). Among interventions investigated here, the most effective were suspending intra-city public transport, closing entertainment venues and banning public gatherings. The national emergency response delayed the growth and limited the size of the COVID-19 epidemic and, by 19 February (day 50), had averted hundreds of thousands of cases across China.