Knowledge, Attitudes, and Practices Towards COVID-19 Among Rural Residents of Hebei Province: A Cross-sectional Survey.

OBJECTIVE: COVID-19 has spread worldwide due to high infectivity. The social sexual environment in rural areas of China and the weak basic medical facilities, may affect the treatment and transmission of the disease. The aim of this study was to understand the knowledge, attitude and practice (KAP) related to COVID-19 among residents in rural areas experiencing the epidemic and the factors, to provide a basis for further epidemic prevention and control. METHODS: The COVID-19 KAP of rural residents in Hebei Province was collected by the snowball sampling method. The COVID-19 KAP questionnaire was distributed on social platforms such as WeChat and QQ through a network questionnaire. RESULTS: The overall level of COVID-19 KAP in rural residents was good, but in terms of knowledge, the correct rate of isolation was 73.2%, the correct rate of two disinfection items were 72.3% and 77.4%, and the correct rate about hand washing was 70.7%. 54.5% residents feel panic. 81.0% disinfected household items, and 84.9% washed hands correctly. Residents still needed to strengthen these aspects. Binary logistic analysis showed that age, education and whether to participated in training were factors affecting the level of COVID-19 KAP. CONCLUSIONS: This study found that rural residents had good levels of COVID-19 KAP, but there were gaps in specific issues that warrant attention. We advocate training on COVID-19 for rural residents.

LDANet: Automatic lung parenchyma segmentation from CT images.

Automatic segmentation of the lung parenchyma from computed tomography (CT) images is helpful for the subsequent diagnosis and treatment of patients. In this paper, based on a deep learning algorithm, a lung dense attention network (LDANet) is proposed with two mechanisms: residual spatial attention (RSA) and gated channel attention (GCA). RSA is utilized to weight the spatial information of the lung parenchyma and suppress feature activation in irrelevant regions, while the weights of each channel are adaptively calibrated using GCA to implicitly predict potential key features. Then, a dual attention guidance module (DAGM) is designed to maximize the integration of the advantages of both mechanisms. In addition, LDANet introduces a lightweight dense block (LDB) that reuses feature information and a positioned transpose block (PTB) that realizes accurate positioning and gradually restores the image resolution until the predicted segmentation map is generated. Experiments are conducted on two public datasets, LIDC-IDRI and COVID-19 CT Segmentation, on which LDANet achieves Dice similarity coefficient values of 0.98430 and 0.98319, respectively, outperforming a state-of-the-art lung segmentation model. Additionally, the effectiveness of the main components of LDANet is demonstrated through ablation experiments.

HADCNet: Automatic segmentation of COVID-19 infection based on a hybrid attention dense connected network with dilated convolution.

the automatic segmentation of lung infections in CT slices provides a rapid and effective strategy for diagnosing, treating, and assessing COVID-19 cases. However, the segmentation of the infected areas presents several difficulties, including high intraclass variability and interclass similarity among infected areas, as well as blurred edges and low contrast. Therefore, we propose HADCNet, a deep learning framework that segments lung infections based on a dual hybrid attention strategy. HADCNet uses an encoder hybrid attention module to integrate feature information at different scales across the peer hierarchy to refine the feature map. Furthermore, a decoder hybrid attention module uses an improved skip connection to embed the semantic information of higher-level features into lower-level features by integrating multi-scale contextual structures and assigning the spatial information of lower-level features to higher-level features, thereby capturing the contextual dependencies of lesion features across levels and refining the semantic structure, which reduces the semantic gap between feature maps at different levels and improves the model segmentation performance. We conducted fivefold cross-validations of our model on four publicly available datasets, with final mean Dice scores of 0.792, 0.796, 0.785, and 0.723. These results show that the proposed model outperforms popular state-of-the-art semantic segmentation methods and indicate its potential use in the diagnosis and treatment of COVID-19.

Follow-up of patients with COVID-19 by the Delta variant after hospital discharge in Guangzhou, Guandong, China.

The B.1.617.2 (Delta) variant of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has contributed to a new increment in cases across the globe. We conducted a prospective follow-up of COVID-19 cases to explore the recurrence and potential propagation risk of the Delta variant and discuss potential explanations for the infection recurrence. A prospective, non-interventional follow-up of discharged patients who had SARS-CoV-2 infections by the Delta variant in Guangdong, China, from May 2021 to June 2021 was conducted. The subjects were asked to complete a physical health examination and undergo nucleic acid testing and antibody detection for the laboratory diagnosis of COVID-19. In total, 20.33% (25/123) of patients exhibited recurrent positive results after discharge. All patients with infection recurrence were asymptomatic and showed no abnormalities in the pulmonary computed tomography. The time from discharge to the recurrent positive testing was usually between 1-33 days, with a mean time of 9.36 days. The cycle threshold from the real-time polymerase chain reaction assay that detected the recurrence of positivity ranged from 27.48 to 39.00, with an average of 35.30. The proportion of vaccination in the non-recurrent group was higher than that in the recurrently positive group (26% vs. 4%; χ2 = 7.902; P < 0.05). Two months after discharge, the most common symptom was hair loss and 59.6% of patients had no long-term symptoms at all. It is possible for the Delta variant SARS-CoV-2 patients after discharge to show recurrent positive results of nucleic acid detection; however, there is a low risk of continuous community transmission. Both, the physical and mental quality of life of discharged patients were significantly affected. Our results suggest that it makes sense to implement mass vaccination against the Delta variant of SARS-CoV-2.

Development of an Adeno-Associated Virus-Vectored SARS-CoV-2 Vaccine and Its Immunogenicity in Mice.

Owing to the outbreak of the novel coronavirus (SARS-CoV-2) worldwide at the end of 2019, the development of a SARS-CoV-2 vaccine became an urgent need. In this study, we developed a type 9 adeno-associated virus vectored vaccine candidate expressing a dimeric receptor binding domain (RBD) of the SARS-CoV-2 spike protein (S protein) and evaluated its immunogenicity in a murine model. The vaccine candidate, named AAV9-RBD virus, was constructed by inserting a signal peptide to the N-terminus of two copies of RBD, spaced by a linker, into the genome of a type 9 adeno-associated virus. In vitro assays showed that HeLa cells infected by the recombinant AAV virus expressed high levels of the recombinant RBD protein, mostly found in the cell culture supernatant. The recombinant AAV9-RBD virus was cultured and purified. The genome titer of the purified recombinant AAV9-RBD virus was determined to be 2.4 × 1013 genome copies/mL (GC/mL) by Q-PCR. Balb/c mice were immunized with the virus by intramuscular injection or nasal drip administration. Eight weeks after immunization, neutralizing antibodies against the new coronavirus pseudovirus were detected in the sera of all mice; the mean neutralizing antibody EC50 values were 517.7 ± 292.1 (n=10) and 682.8 ± 454.0 (n=10) in the intramuscular injection group and nasal drip group, respectively. The results of this study showed that the recombinant AAV9-RBD virus may be used for the development of a SARS-CoV-2 vaccine.

Variability in transmission risk of SARS-CoV-2 in close contact settings: A contact tracing study in Shandong Province, China.

BACKGROUND: Understanding the relative transmissibility of SARS-CoV-2 virus across different contact settings and the possibility of superspreading events is important for prioritizing disease control. Such assessment requires proper consideration of individual level exposure history, which is made possible by contact tracing. METHODS: The case-ascertained study in Shandong, China including 97 laboratory-confirmed index cases and 3158 close contacts. All close contacts were quarantined after their last exposure of index cases. Contacts were tested for COVID-19 regularly by PCR to identify both symptomatic and asymptomatic infections. We developed a Bayesian transmission model to the contact tracing data to account for different duration of exposure among individuals to transmission risk in different settings, and the heterogeneity of infectivity of cases. RESULTS: We estimate secondary attack rates (SAR) to be 39% (95% credible interval (CrI): 20-64%) in households, 30% (95% CrI: 11-67%) in healthcare facilities, 23% (95% CrI: 7-51%) at workplaces, and 4% (95% CrI: 1-17%) during air travel. Models allowing heterogeneity of infectivity of cases provided a better goodness-of-fit. We estimated that 64% (95% CrI: 55-72%) of cases did not generate secondary transmissions, and 20% (95% CrI: 15-26%) cases explained 80% of secondary transmissions. CONCLUSIONS: Household, healthcare facilities and workplaces are efficient setting for transmission. Timely identification of potential superspreaders in most transmissible settings remains crucial for containing the pandemic.

A robust high-throughput fluorescent polarization assay for the evaluation and screening of SARS-CoV-2 fusion inhibitors.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is a serious threat to global health. One attractive antiviral target is the membrane fusion mechanism employed by the virus to gain access to the host cell. Here we report a robust protein-based fluorescent polarization assay, that mimicking the formation of the six-helix bundle (6-HB) process during the membrane fusion, for the evaluation and screening of SARS-CoV-2 fusion Inhibitors. The IC50 of known inhibitors, HR2P, EK1, and Salvianolic acid C (Sal-C) were measured to be 6.1 nM, 2.5 nM, and 8.9 µM respectively. In addition, we found Sal-A has a slightly lower IC50 (3.9 µM) than Sal-C. Interestingly, simple caffeic acid can also disrupt the formation of 6-HB with a sub-mM concentration. Pilot high throughput screening (HTS) of a small marine natural product library validates the assay with a Z' factor close to 0.8. We envision the current assay provides a convenient way to screen SARS-CoV-2 fusion inhibitors and assess their binding affinity.

Identification of potent human neutralizing antibodies against SARS-CoV-2 implications for development of therapeutics and prophylactics.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel coronavirus that is spreading rapidly, which seriously impacts global public health and economy. Thus, developing effective drugs remains urgent. We identify two potent antibodies, nCoVmab1 and nCoVmab2, targeting the SARS-CoV-2 spike protein receptor-binding domain (RBD) with high affinities from a naïve human phage-displayed Fab library. nCoVmab1 and nCoVmab2 neutralize authentic SARS-CoV-2 with picomolar and nanomolar IC50 values, respectively. No detectable defects of nCoVmab1 and nCoVmab2 are found during the preliminary druggability evaluation. nCoVmab1 could reduce viral titer and lung injury when administered prophylactically and therapeutically in human angiotensin-converting enzyme II (hACE2)-transgenic mice. Therefore, phage display platform could be efficiently used for rapid development of neutralizing monoclonal antibodies (nmabs) with clinical potential against emerging infectious diseases. In addition, we determinate epitopes in RBD of these antibodies to elucidate the neutralizing mechanism. We also convert nCoVmab1 and nCoVmab2 to their germline formats for further analysis, which reveals the contribution of somatic hypermutation (SHM) during nCoVmab1 and nCoVmab2 maturation. Our findings not only provide two highly potent nmabs against SARS-CoV-2 as prophylactic and therapeutic candidates, but also give some clues for development of anti-SARS-CoV-2 agents (e.g., drugs and vaccines) targeting the RBD.

Kawasaki disease shock syndrome complicated with bilateral lung consolidation in a child: A case report.

INTRODUCTION: Kawasaki disease (KD) is a systemic inflammatory disease. Standard imaging features of KD include interstitial and lobular inflammatory lesions in the lungs, while KD shock syndrome (KDSS), complicated with substantial consolidation and atelectasis in the lung, is rarely reported. PATIENTS CONCERNS: Herein, we report a single case of a 5-year-old female patient who manifested KDSS on the seventh day of the course of KD. Chest enhanced computed tomography indicated large-area consolidation in the lower lobes of the bilateral lungs. DIAGNOSIS: The patient was diagnosed with KDSS complicated with non-infective lung consolidation. INTERVENTIONS: The patient received human intravenous immunoglobulin (2 g/kg) and aspirin (30-50 mg/kgd), methylprednisolone, a vasoactive agent, and albumin. Infective factors were excluded. OUTCOMES: The consolidation in the lower lobe of the bilateral lungs was completely recovered after 3 days of treatment. CONCLUSIONS: Children with KDSS may present with pulmonary lesions such as substantial consolidation and atelectasis; thus, infective factors should be excluded. If there is no etiological evidence, antibiotics should be used with caution.

Liver impairment in COVID-19 patients: A retrospective analysis of 115 cases from a single centre in Wuhan city, China.

BACKGROUND: The SARS-CoV-2 pandemic is an ongoing global health emergency. The aim of our study was to investigate the changes of liver function and its clinical significance in COVID-19 patients. METHOD: This retrospective, single-centre study was conducted on 115 confirmed cases of COVID-19 in Zhongnan hospital of Wuhan University from 18 January 2020 to 22 February 2020. Liver function and related indexes were analysed to evaluate its relationship with disease progression in COVID-19 patients. RESULTS: Part of the COVID-19 patients presented with varying degrees of abnormality in liver function indexes. However, the levels of ALT, AST, TBIL, GGT and LDH in COVID-19 patients were not significantly different when compared with hospitalised community-acquired pneumonia patients, and the levels of albumin is even significantly higher. The levels of ALT, AST, TBIL, LDH and INR showed statistically significant elevation in severe COVID-19 cases compared with that in mild cases. However, the clinical significance of the elevation is unremarkable. Majority of severe COVID-19 patients showed significantly decreasing in albumin level and continuously decreasing in the progress of illness. Most of the liver function indexes in COVID-19 patients were correlated with CRP and NLR, the markers of inflammation. Logistic regression analysis further identified NLR as the independent risk factor for severe COVID-19, as well as age. CONCLUSIONS: Although abnormalities of liver function indexes are common in COVID-19 patients, the impairment of liver function is not a prominent feature of COVID-19, and also may not have serious clinical consequences.