N-Butanol Extract of Glycyrrhizae Radix et Rhizoma Inhibits Dengue Virus through Targeting Envelope Protein.

BACKGROUND: At present, about half of the world's population is at risk of being infected with dengue virus (DENV). However, there are no specific drugs to prevent or treat DENV infection. Glycyrrhizae Radix et Rhizome, a well-known traditional Chinese medicine, performs multiple pharmacological activities, including exerting antiviral effects. The aim of this study was to investigate the anti-DENV effects of n-butanol extract from Glycyrrhizae Radix et Rhizome (GRE). METHODS: Compounds analysis of GRE was conducted via ultra-performance liquid chromatography/tandem mass spectrometry (UHPLC-MS/MS). The antiviral activities of GRE were determined by the CCK-8 assay, plaque assay, qRT-PCR, Western blotting, and the immunofluorescence assay. The DENV-infected suckling mice model was constructed to explore the antiviral effects of GRE in vivo. RESULTS: Four components in GRE were analyzed by UHPLC-MS/MS, including glycyrrhizic acid, glycyrrhetnic acid, liquiritigenin, and isoliquiritigenin. GRE inhibited the attachment process of the virus replication cycle and reduced the expression of the E protein in cell models. In the in vivo study, GRE significantly relieved clinical symptoms and prolong survival duration. GRE also significantly decreased viremia, reduced the viral load in multiple organs, and inhibited the release of pro-inflammatory cytokines in DENV-infected suckling mice. CONCLUSIONS: GRE exhibited significant inhibitory activities in the adsorption stage of the DENV-2 replication cycle by targeting the envelope protein. Thus, GRE might be a promising candidate for the treatment of DENV infection.

Effectiveness of SARS-CoV-2-inactivated vaccine and the correlation to neutralizing antibodies: A test-negative case-control study.

Severe acute respiratory syndrome coronavirus 2 breakthrough infection in highly vaccinated populations raises study on the effectiveness for inactivated vaccine, including effectiveness of the vaccine dose, the continuance of effectiveness, the effectiveness against severe/critical coronavirus disease 2019 and against secondary attacks. A population of 10 870 close contacts were investigated in a Delta variant's epidemic. The effectiveness of vaccination was estimated in a test-negative case-control study. In addition, serum was used to detect neutralizing antibodies, to explore their correlation to effectiveness. The vaccine effectiveness (VE) values were estimated for populations aged 12 years or older. The overall adjusted VE was 56.2% and a two-dose vaccine was more effective than a one-dose vaccine (56.7% vs. 43.8%). In addition, the population that got the second dose vaccine within 2 months showed higher VE than the population vaccinated for longer than 2 months (61.5% vs. 52.3%). Among the population who vaccinated 2 doses or within 2 months, a higher level of neutralizing antibodies was observed. For infected cases, vaccinated populations showed lower rates of transmission (2.63% vs. 4.36%). Further, those vaccinated cases, who were not found causing transmission, had a higher level of antibodies. The study provided a full view of the effectiveness of inactivated vaccines in a real-world setting. The time-related VE against infection and lower transmission of breakthrough vaccinated cases were observed, which may indicate that a necessity of a booster vaccine to maintain the effectiveness and high level of neutralizing antibody.

Evaluating the value of anti-SARS-CoV-2 antibody detection and neutralizing responses with euvirus: A population of 10776 close contacts in the epidemic of Fujian.

BACKGROUND: Nucleic acid detection represents limitations due to its false-negative rate and technical complexity in the COVID-19 pandemic. Anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody tests are widely spread all over the world presently. However, there is no report on the effectiveness of anti-SARS-CoV-2 antibody testing methods in China. METHODS: We gathered 10776 serum samples from close contacts of the SARS-CoV-2 infections in Fujian of China and used 2 chemiluminescence immunoassays (Wantai Bio., Yahuilong Bio.) and 2 lateral flow immunoassays (Lizhu Bio. and Dongfang Bio.) to perform the anti-SARS-CoV-2 antibody tests in China. RESULTS: The 4 antibody tests have great diagnostic value for infected or uninfected, especially in the neutralizing antibodies tests, the AUC can reach 0.939 (Wantai Bio.) and 0.916 (Yahuilong Bio.). Furthermore, we used pseudoviruses and euvirus neutralization assay to validate the effectiveness of these antibody test, the results of pseudoviruses neutralization assay or euvirus neutralization assay shows a considerable correlation with the 4 antibody detection respectively, particularly in euvirus neutralization assay, neutralizing antibodies detected by Wantai Bio. or Yahuilong Bio., the correlation can get the level of 0.93 or 0.82. CONCLUSIONS: The findings of this study demonstrate that the detections of antibodies have profound value in the diagnosis of COVID-19.

Understanding Learners' Metacognition of Online Teacher Feedback Amid COVID-19: A Case Study in a University Livestream Instruction Context.

While research on metacognition in second language (L2) learning has burgeoned in the past two decades, its relation to actual teaching behaviors, such as teacher feedback, remains to be fully described and explained in L2 classroom, especially in livestream English teaching settings. To fill this gap, this case study examined how learners utilize and regulate metacognition of online teacher feedback during COVID-19 in a Chinese inner land university. Data were gathered through semi-structured interviews. With qualitative and interpretive analysis, it is revealed that leaners positively receive online teacher feedback for its detrimentalness together with a growth mindset and high levels of resilience, but, on the whole, there is a metacognitive deficit: they misinterpret self-consciousness about online feedback which is underpinned by a conception of tasks that characterizes online L2 learning. This research expands our understanding of L2 learning processes pertaining to awareness and management of teacher feedback receiving and may also shed light on solutions to empower livestream teaching by building external scaffolding devices to compensate weaknesses of online L2 education during the pandemic and beyond.

Effectiveness of containment strategies in preventing SARS-CoV-2 transmission.

BACKGROUND: Despite substantial resources deployed to curb SARS-CoV-2 transmission, controlling the COVID-19 pandemic has been a major challenge. New variants of the virus are frequently emerging leading to new waves of infection and re-introduction of control measures. In this study, we assessed the effectiveness of containment strategies implemented in the early phase of the pandemic. METHODS: Real-world data for COVID-19 cases was retrieved for the period Jan 1 to May 1, 2020 from a number of different sources, including PubMed, MEDLINE, Facebook, Epidemic Forecasting and Google Mobility Reports. We analyzed data for 18 countries/regions that deployed containment strategies such as travel restrictions, lockdowns, stay-at-home requests, school/public events closure, social distancing, and exposure history information management (digital contact tracing, DCT). Primary outcome measure was the change in the number of new cases over 30 days before and after deployment of a control measure. We also compared the effectiveness of centralized versus decentralized DCT. Time series data for COVID-19 were analyzed using Mann-Kendall (M-K) trend tests to investigate the impact of these measures on changes in the number of new cases. The rate of change in the number of new cases was compared using M-K z-values and Sen's slope. RESULTS: In spite of the widespread implementation of conventional strategies such as lockdowns, travel restrictions, social distancing, school closures, and stay-at-home requests, analysis revealed that these measures could not prevent the spread of the virus. However, countries which adopted DCT with centralized data storage were more likely to contain the spread. CONCLUSIONS: Centralized DCT was more effective in containing the spread of COVID-19. Early implementation of centralized DCT should be considered in future outbreaks. However, challenges such as public acceptance, data security and privacy concerns will need to be addressed.

SARS‐CoV‐2 spike protein harnesses SNX27‐mediated endocytic recycling pathway

SARS‐CoV‐2 is an enveloped positive‐sense RNA virus that depends on host factors for all stages of its life. Membrane receptor ACE2 is a well‐established factor for SARS‐CoV‐2 docking. In addition to ACE2, whole‐genome genetic screens have identified additional proteins, such as endosomal trafficking regulators SNX27 and retromer, as key host factors required for SARS‐CoV‐2 infection. However, it is poorly understood how SARS‐CoV‐2 utilize host endocytic transport pathways to produce productive infection. Here, we report that SNX27 interacts with the SARS‐CoV‐2 spike (S) protein to facilitate S protein surface expression. Interestingly, S protein binds to the PDZ domain of SNX27, although it does not contain a PDZ‐binding motif (PDZbm). Either abrogation of the SNX27 PDZ domain or S protein “MTSC” motif, which is critical for SNX27 binding, decreases surface expression of S protein and viral production. Collectively, our study highlights a novel approach utilized by SARS‐CoV‐2 to facilitate virion trafficking to establish virus infection. Proposed model showing SNX27 promotes intracellular trafficking of S protein and viral production. (a) SNX27, via its PDZ domain, interacts with S protein and promotes endosome‐to‐plasma membrane trafficking of S protein. SNX27 could also promote the production of SARS‐CoV‐2 virions in host cells, although the mechanism remains poorly defined. (b) Depletion of SNX27 impairs endosome‐to‐plasma membrane trafficking of S protein, leading to its lysosomal degradation.

Factors for peripherally inserted central catheters care delay in cancer patients during the COVID-19 pandemic.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has rapidly evolved into a global pandemic. The public health systems have consequently been placed under tremendous pressure. Peripherally inserted central catheters (PICCs) are widely used in patients with cancers. Little is known about the provision of PICCs care amongst cancer patients during this pandemic. METHODS: We studied 156 cancer patients with PICCs treated at the Cancer Center of the Fifth Affiliated Hospital of Sun Yat-sen University between January 2020 and March 2020. Their clinical characteristics, social features, psychological characteristics, and PICCs care situations were analyzed. The chi-squared (χ2) test or Fisher's exact test were used for univariate analyses. Multivariate logistic regression analyses were performed using stepwise variable selection. Differences were evaluated using a two-tailed test, and P<0.05 was considered statistically significant. RESULTS: Of 156 patients, 57 (36.5%) experienced delays of PICCs care, and 12 (21.1%) suffered from complications including infection, thrombosis, and mechanical failure. Univariate analysis detected that the increased risk of PICCs care delay was associated with older age (≥30), lower level of education (<9 years), working, taking public transport to the hospital, anxiety about COVID-19, lower social support rating scale (SSRS) score (<30). Multivariate analysis detected level of education, being employed or not, mode of transport, and SSRS score were independent predictive factors for the delay in PICCs care. CONCLUSIONS: Physical aspects, social factors, and psychological status commonly influenced patients' health care seeking behaviors such as PICCs maintenance. An increase in effort is required from patients' families and society to assure optimal care for cancer patients during this pandemic.

COVID-Net: a tailored deep convolutional neural network design for detection of COVID-19 cases from chest X-ray images.

The Coronavirus Disease 2019 (COVID-19) pandemic continues to have a devastating effect on the health and well-being of the global population. A critical step in the fight against COVID-19 is effective screening of infected patients, with one of the key screening approaches being radiology examination using chest radiography. It was found in early studies that patients present abnormalities in chest radiography images that are characteristic of those infected with COVID-19. Motivated by this and inspired by the open source efforts of the research community, in this study we introduce COVID-Net, a deep convolutional neural network design tailored for the detection of COVID-19 cases from chest X-ray (CXR) images that is open source and available to the general public. To the best of the authors' knowledge, COVID-Net is one of the first open source network designs for COVID-19 detection from CXR images at the time of initial release. We also introduce COVIDx, an open access benchmark dataset that we generated comprising of 13,975 CXR images across 13,870 patient patient cases, with the largest number of publicly available COVID-19 positive cases to the best of the authors' knowledge. Furthermore, we investigate how COVID-Net makes predictions using an explainability method in an attempt to not only gain deeper insights into critical factors associated with COVID cases, which can aid clinicians in improved screening, but also audit COVID-Net in a responsible and transparent manner to validate that it is making decisions based on relevant information from the CXR images. By no means a production-ready solution, the hope is that the open access COVID-Net, along with the description on constructing the open source COVIDx dataset, will be leveraged and build upon by both researchers and citizen data scientists alike to accelerate the development of highly accurate yet practical deep learning solutions for detecting COVID-19 cases and accelerate treatment of those who need it the most.

The impact of the COVID-19 pandemic on lung cancer patients.

BACKGROUND: The coronavirus disease (COVID-19) poses an unprecedented challenge to health and epidemic prevention system, especially the healthcare of patients with cancer. We sought to study the impact of COVID-19 on lung cancer patients in our center. METHODS: We initiated a retrospectively study to analyze the impact of COVID-19 on lung cancer patients in our center, who were accepted for routine anticancer treatment before the epidemic and planned to return to hospital in January and February of 2020. RESULTS: A total of 161 cases of lung cancer were included in the final analysis. As of April 15, 95 patients had delayed their return visit, and 47 cases were finally designated as having delayed admission during the epidemic and having to discontinue or delay their regular anticancer treatments. Of these 47 delayed patients, 33 were evaluated for tumor status using a computed tomography scan, 6 of these 33 cases (18.18%) were diagnosed as progressive disease (PD), and 5 cases did not return for visit. CONCLUSIONS: This is the first study investigating impact of COVID-19 on non-COVID-19 lung cancer patients during the pandemic. The study demonstrates the significant impact of the COVID-19 crisis on oncological care, indicating the need for appropriate change of treatment decisions and continued follow-up and psycho-oncological support during this pandemic.