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1.
2nd International Conference on Electronics, Communications and Information Technology, CECIT 2021 ; : 292-297, 2021.
Article in English | Scopus | ID: covidwho-1831727

ABSTRACT

COVID-19 is breaking out and spreading globally, posing a severe threat to public health and economies worldwide due to its highly transmissible and pathogenic nature. Early, accurate and rapid diagnosis of COVID-19 can effectively stop the spread of the COVID-19 virus. Automatic diagnostic models based on deep learning can detect COVID-19 quickly and accurately. This paper uses a three-dimensional Convolutional Neural Network (3D CNN) to build a COVID-19 diagnostic prediction model for COVID-19 detection. All 192 sets of chest Computed Tomography(CT) data collected are used for this study, including 96 sets of confirmed COVID-19 patients and 96 sets of CT scans of normal human lungs. 5-fold cross-validation is used to train and validate the model. 154 data sets are used to train the model, and 38 sets are used for testing. All experimental data are segmented using a pre-trained SP-V-Net to obtain 3D lung masks fed into 3D CNN for training and validation of the prediction model. In addition, to verify the accuracy of the model predictions and provide interpretability for medical diagnosis, we visualize the experimental results using Class Activation Maps(CAM) to localize the predicted disease regions. The results from several experiments show that the accuracy of our prediction model is 0.911, the Area Under Curve (AUC) 0.976, for no-COVID-19(Precision, 0.902, Recall 0.911, F1-Score 0.900), COVID-19 (Precision, 0.932, Recall 0.911, F1-Score 0.902). The experimental results show that our established diagnostic model can help physicians make a rapid and accurate diagnosis of COVID-19 in response to the spread of COVID-19. © 2021 IEEE.

2.
SAGE Open ; 12(1), 2022.
Article in English | Scopus | ID: covidwho-1741898

ABSTRACT

This global lockdown of educational institutions by COVID-19 has caused overwhelming disruption in students’ learning and assessment, which has substantial effects on their academic emotions. This study applied a mixed methods approach to investigate how COVID-19 influences Gaokao applicants’ academic emotions in the Chinese context. The study found that Gaokao applicants during the COVID-19 pandemic had strong positive activating emotions, positive deactivating emotions, and negative activating emotions. The results showed that there were significant gender differences in academic emotions, and students’ physical exercise was also related. This study found that there was no correlation between the Gaokao applicants’ academic emotions and their parents’ occupations, parents’ academic qualifications, or types of exams. As COVID-19 continues to be a worldwide public challenge, this study has implications on how to alleviate negative academic emotions of students who will take high-risk tests under the pressure of the pandemic. © The Author(s) 2022.

3.
PubMed; 2022.
Preprint in English | PubMed | ID: ppcovidwho-329164

ABSTRACT

The SARS-CoV-2 B.1.1.529 lineage, Omicron variant, was first detected in November 2021 and carries 32 amino acid mutations in the spike protein (15 in RBD) and exhibits significant escape of neutralizing antibodies targeting the parental SARS-CoV-2 virus. Here, we performed a high-resolution multiplex (16-plex) surrogate virus neutralization assay covering all major SARS-CoV-2 variants and pre-emergent ACE2-binding sarbecoviruses against 20 different human serum panels from infected, vaccinated and hybrid immune individuals which had vaccine-breakthrough infections or infection followed by vaccination. Among all sarbecoviruses tested, we observed 1.1 to 4.7-, 2.3 to 10.3- and 0.7 to 33.3-fold reduction in neutralization activities to SARS-CoV-2 Beta, Omicron and SARS-CoV-1, respectively. Among the SARS-CoV-2 related sarbecoviruses, it is found that the genetically more distant bat RaTG13 and pangolin GX-P5L sarbecoviruses had less neutralization escape than Omicron. Our data suggest that the SARS-CoV-2 variants emerged from the changed immune landscape of human populations are more potent in escaping neutralizing antibodies, from infection or vaccination, than pre-emergent sarbecoviruses naturally evolved in animal populations with no or less immune selection pressure.

4.
Embase;
Preprint in English | EMBASE | ID: ppcovidwho-326841

ABSTRACT

Rapid assessment of whether a pandemic pathogen may have increased transmissibility or be capable of evading existing vaccines and therapeutics is critical to mounting an effective public health response. Over the period of seven days, we utilized rapid computational prediction methods to evaluate potential public health implications of the emerging SARS-CoV-2 Omicron variant. Specifically, we modeled the structure of the Omicron variant, examined its interface with human angiotensin converting enzyme 2 (ACE-2) and evaluated the change in binding affinity between Omicron, ACE-2 and publicly known neutralizing antibodies. We also compared the Omicron variant to known Variants of Concern (VoC). Seven of the 15 Omicron mutations occurring in the spike protein receptor binding domain (RBD) occur at the ACE-2 cell receptor interface, and therefore may play a critical role in enhancing binding to ACE-2. Our estimates of Omicron RBD-ACE-2 binding affinities indicate that at least two of RBD mutations, Q493R and N501Y, contribute to enhanced ACE-2 binding, nearly doubling delta-delta-G (ddG) free energies calculated for other VoC's. Binding affinity estimates also were calculated for 55 known neutralizing SARS-CoV-2 antibodies. Analysis of the results showed that Omicron substantially degrades binding for more than half of these neutralizing SARS-CoV-2 antibodies, and for roughly 10 times as many of the antibodies than the currently dominant Delta variant. This early study lends support to use of rapid computational risk assessments to inform public health decision-making while awaiting detailed experimental characterization and confirmation.

5.
33rd International Conference for High Performance Computing, Networking, Storage and Analysis: Science and Beyond, SC 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1551077

ABSTRACT

Structure-based Deep Fusion modelswere recently shown to outperform several physicsand machine learning-based protein-ligand binding affinity prediction methods. As part of a multi-institutional COVID-19 pandemic response, over 500 million small molecules were computationally screened against four protein structures from the novel coronavirus (SARS-CoV-2), which causes COVID-19. Three enhancements to Deep Fusion were made in order to evaluate more than 5 billion docked poses on SARS-CoV-2 protein targets. First, the Deep Fusion concept was refined by formulating the architecture as one, coherently backpropagated model (Coherent Fusion) to improve bindingaffinity prediction accuracy. Secondly, the model was trained using a distributed, genetic hyper-parameter optimization. Finally, a scalable, high-Throughput screening capability was developed to maximize the number of ligands evaluated and expedite the path to experimental evaluation. In this work, we present both the methods developed for machine learning-based high-Throughput screening and results from using our computational pipeline to find SARS-CoV-2 inhibitors. © 2021 IEEE Computer Society. All rights reserved.

6.
M&Som-Manufacturing & Service Operations Management ; : 21, 2021.
Article in English | Web of Science | ID: covidwho-1511799

ABSTRACT

Problem definition: We study the disproportionate impact of the lockdown as a result of the COVID-19 outbreak on female and male academic research productivity in social science. Academic/practical relevance: The lockdown has caused substantial disruptions to academic activities, requiring people to work from home. How this disruption affects productivity and the related gender equity is an important operations and societal question. Methodology: We collect data from the largest open-access preprint repository for social science on 41,858 research preprints in 18 disciplines produced by 76,832 authors across 25 countries over a span of two years. We use a difference-in-differences approach leveraging the exogenous pandemic shock. Results: Our results indicate that, in the 10 weeks after the lockdown in the United States, although total research productivity increased by 35%, female academics' productivity dropped by 13.2% relative to that of male academics. We also show that this intensified productivity gap is more pronounced for assistant professors and for academics in top-ranked universities and is found in six other countries. Managerial implications: Our work points out the fairness issue in productivity caused by the lockdown, a finding that universities will find helpful when evaluating faculty productivity. It also helps organizations realize the potential unintended consequences that can arise from telecommuting.

7.
Chinese Medical Journal ; 28:28, 2021.
Article in English | MEDLINE | ID: covidwho-1209266

ABSTRACT

BACKGROUND: The significant morbidity and mortality resulted from the infection of a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) call for urgent development of effective and safe vaccines. We report the immunogenicity and safety of an inactivated SARS-CoV-2 vaccine, KCONVAC, in healthy adults. METHODS: Phase 1 and phase 2 randomized, double-blind, and placebo-controlled trials of KCONVAC were conducted in healthy Chinese adults aged 18-59 years. The participants in the phase 1 trial were randomized to receive two doses, one each on Days 0 and 14, of either KCONVAC (5 mug/dose or 10 mug/dose) or placebo. The participants in the phase 2 trial were randomized to receive either KCONVAC (at 5 or 10 mug/dose) or placebo on Days 0 and 14 (0/14 regimen) or Days 0 and 28 (0/28 regimen). In the phase 1 trial, the primary safety endpoint was the proportion of participants experiencing adverse reactions/events within 28 days following the administration of each dose. In the phase 2 trial, the primary immunogenicity endpoints were neutralization antibody seroconversion and titer and anti-receptor-binding domain immunoglobulin G seroconversion at 28 days after the second dose. RESULTS: In the phase 1 trial, 60 participants were enrolled and received at least one dose of 5-mug vaccine (n = 24), 10-mug vaccine (n = 24), or placebo (n = 12). In the phase 2 trial, 500 participants were enrolled and received at least one dose of 5-mug vaccine (n = 100 for 0/14 or 0/28 regimens), 10-mug vaccine (n = 100 for each regimen), or placebo (n = 50 for each regimen). In the phase 1 trial, 13 (54%), 11 (46%), and 7 (58%) participants reported at least one adverse event (AE) after receiving 5-mug vaccine, 10-mug vaccine, or placebo, respectively. In the phase 2 trial, 16 (16%), 19 (19%), and 9 (18%) 0/14-regimen participants reported at least one AE after receiving 5-mug vaccine, 10-mug vaccine, or placebo, respectively. Similar AE incidences were observed in the three 0/28-regimen treatment groups. No AEs with an intensity of grade 3+ were reported, expect for one vaccine-unrelated serious AE (foot fracture) reported in the phase 1 trial. KCONVAC induced significant antibody responses;0/28 regimen showed a higher immune responses than that did 0/14 regimen after receiving two vaccine doses. CONCLUSIONS: Both doses of KCONVAC are well tolerated and able to induce robust immune responses in healthy adults. These results support testing 5-mug vaccine in the 0/28 regimen in an upcoming phase 3 efficacy trial. TRIAL REGISTRATION: http://www.chictr.org.cn/index.aspx (No. ChiCTR2000038804, http://www.chictr.org.cn/showproj.aspx?proj=62350;No. ChiCTR2000039462, http://www.chictr.org.cn/showproj.aspx?proj=63353).

8.
Kexue Tongbao/Chinese Science Bulletin ; 66(9):980-986, 2021.
Article in Chinese | Scopus | ID: covidwho-1175360
10.
Zhonghua Yu Fang Yi Xue Za Zhi ; 54(9): 963-967, 2020 Sep 06.
Article in Chinese | MEDLINE | ID: covidwho-750613

ABSTRACT

Objective: To evaluate and share the novel method for recruiting participants in clinical trials of vaccines in emergency situations. Methods: To publish recruitment notice in local areas of Wuhan through websites and medium, and guide interested persons to log in to the"Clinical Trials of SARS-CoV-2 Vaccine Reservation and Health Declaration System"to appoint and register their health information. The "Health Declaration System" provides each volunteer evaluation and risk levels to preliminarily exclude those who do not meet the inclusion criteria. Researchers review the qualified volunteers by telephone, organize them to go to the vaccination site, and finally conduct a strict medical screening to determine the final subjects. Results: A total of 4 819 people and 5 132 people registered in the Phase Ⅰ and Phase Ⅱ recruitment system respectively, with men 2 912 (60.43%) and 2 887 (56.25%) more than women 1 907 (39.57%) and 2 245 (43.75%), mostly in the 20-39 age group, with 3 211 (66.63%) and 3 966 (77.28%). All 13 districts in Wuhan have interested residents to participate clinical research.The initial qualified rate of the Phase Ⅱ recruitment system was higher than that of Phase Ⅰ, with men 2 047 (70.28%) and 2 135(73.95%), higher than women 1 083 (56.80%) and 1 472 (65.57%); 440 and 689 people were reviewed by telephone in Phase Ⅰ and Phase Ⅱ respectively, and the number of verified volunteers was about 440 (35.00%) and 689 (67.20%); Of the 201 603 people who arrived at the vaccination site, 12 and 26 of them were positive for the SARS-CoV-2 antibody with an antibody positive rate of 6.00% and 4.31% respectively. Conclusion: The novel method for recruiting subjects in this clinical study is efficient and reliable, and the recruitment situation of Phase Ⅰ had set a good example for Phase Ⅱ but the medium-and long-term compliance of subjects and the separation of willingness and behaviors still need to be further studied.


Subject(s)
Clinical Trials as Topic/organization & administration , Patient Selection , Viral Vaccines , Adult , COVID-19 , COVID-19 Vaccines , China/epidemiology , Coronavirus Infections/epidemiology , Coronavirus Infections/prevention & control , Emergencies , Female , Humans , Male , Pandemics/prevention & control , Pneumonia, Viral/epidemiology , Pneumonia, Viral/prevention & control , Volunteers/statistics & numerical data , Young Adult
11.
Ann Oncol ; 31(7): 894-901, 2020 07.
Article in English | MEDLINE | ID: covidwho-16011

ABSTRACT

BACKGROUND: Cancer patients are regarded as a highly vulnerable group in the current Coronavirus Disease 2019 (COVID-19) pandemic. To date, the clinical characteristics of COVID-19-infected cancer patients remain largely unknown. PATIENTS AND METHODS: In this retrospective cohort study, we included cancer patients with laboratory-confirmed COVID-19 from three designated hospitals in Wuhan, China. Clinical data were collected from medical records from 13 January 2020 to 26 February 2020. Univariate and multivariate analyses were carried out to assess the risk factors associated with severe events defined as a condition requiring admission to an intensive care unit, the use of mechanical ventilation, or death. RESULTS: A total of 28 COVID-19-infected cancer patients were included; 17 (60.7%) patients were male. Median (interquartile range) age was 65.0 (56.0-70.0) years. Lung cancer was the most frequent cancer type (n = 7; 25.0%). Eight (28.6%) patients were suspected to have hospital-associated transmission. The following clinical features were shown in our cohort: fever (n = 23, 82.1%), dry cough (n = 22, 81%), and dyspnoea (n = 14, 50.0%), along with lymphopaenia (n = 23, 82.1%), high level of high-sensitivity C-reactive protein (n = 23, 82.1%), anaemia (n = 21, 75.0%), and hypoproteinaemia (n = 25, 89.3%). The common chest computed tomography (CT) findings were ground-glass opacity (n = 21, 75.0%) and patchy consolidation (n = 13, 46.3%). A total of 15 (53.6%) patients had severe events and the mortality rate was 28.6%. If the last antitumour treatment was within 14 days, it significantly increased the risk of developing severe events [hazard ratio (HR) = 4.079, 95% confidence interval (CI) 1.086-15.322, P = 0.037]. Furthermore, patchy consolidation on CT on admission was associated with a higher risk of developing severe events (HR = 5.438, 95% CI 1.498-19.748, P = 0.010). CONCLUSIONS: Cancer patients show deteriorating conditions and poor outcomes from the COVID-19 infection. It is recommended that cancer patients receiving antitumour treatments should have vigorous screening for COVID-19 infection and should avoid treatments causing immunosuppression or have their dosages decreased in case of COVID-19 coinfection.


Subject(s)
Betacoronavirus , Coronavirus Infections/diagnostic imaging , Coronavirus Infections/epidemiology , Hospitalization/trends , Neoplasms/diagnostic imaging , Neoplasms/epidemiology , Pneumonia, Viral/diagnostic imaging , Pneumonia, Viral/epidemiology , Aged , COVID-19 , China/epidemiology , Cohort Studies , Coronavirus Infections/therapy , Female , Humans , Male , Middle Aged , Neoplasms/therapy , Pandemics , Pneumonia, Viral/therapy , Retrospective Studies , SARS-CoV-2
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