A variant-proof SARS-CoV-2 vaccine targeting HR1 domain in S2 subunit of spike protein.

The emerging SARS-CoV-2 variants, commonly with many mutations in S1 subunit of spike (S) protein are weakening the efficacy of the current vaccines and antibody therapeutics. This calls for the variant-proof SARS-CoV-2 vaccines targeting the more conserved regions in S protein. Here, we designed a recombinant subunit vaccine, HR121, targeting the conserved HR1 domain in S2 subunit of S protein. HR121 consisting of HR1-linker1-HR2-linker2-HR1, is conformationally and functionally analogous to the HR1 domain present in the fusion intermediate conformation of S2 subunit. Immunization with HR121 in rabbits and rhesus macaques elicited highly potent cross-neutralizing antibodies against SARS-CoV-2 and its variants, particularly Omicron sublineages. Vaccination with HR121 achieved near-full protections against prototype SARS-CoV-2 infection in hACE2 transgenic mice, Syrian golden hamsters and rhesus macaques, and effective protection against Omicron BA.2 infection in Syrian golden hamsters. This study demonstrates that HR121 is a promising candidate of variant-proof SARS-CoV-2 vaccine with a novel conserved target in the S2 subunit for application against current and future SARS-CoV-2 variants.

Effectiveness of Digital Cognitive Behavior Therapy for the Treatment of Insomnia: Spillover Effects of dCBT.

The effects of digital Cognitive Behavior Therapy for insomnia (dCBT-i) on sleep quality have been previously demonstrated but the spillover effects on fatigue, flow (a state of immersion in activities of interest), and cognitive flexibility remain unclear. The current study examined the effectiveness of dCBT-i. A total of 97 college students (20.96 ± 1.87 years, 73.1% female students) were randomly selected from a shortlist and divided into sleep intervention (n = 39), conventional education (n = 37), and healthy control (n = 21) groups. Task switching paradigm, Fatigue Severity Scale (FSS), Flow Experience Scale (FES), and the Chinese version of the Pittsburgh Sleep Quality Index (CPSQI) were measured pre- and post-intervention. Results show that the sleep quality of the intervention group improved, and fatigue was relieved. Participants in the sleep intervention group had increased flow experience scores post-intervention and improved cognitive flexibility. The control group's sleep quality deteriorated and fatigue level increased. dCBT-i can not only achieve a significant improvement in sleep quality and reduce fatigue, but also improve learning abilities, quality of life, flow, and cognitive flexibility. Future research should pay attention to indicators such as work efficiency, sedative use, and the durability and stability of such effects.

Early severity prediction of BPD for premature infants from chest X-ray images using deep learning: A study at the 28th day of oxygen inhalation.

BACKGROUND AND OBJECTIVE: Bronchopulmonary dysplasia is a common respiratory disease in premature infants. The severity is diagnosed at the 56th day after birth or discharge by analyzing the clinical indicators, which may cause the delay of the best treatment opportunity. Thus, we proposed a deep learning-based method using chest X-ray images of the 28th day of oxygen inhalation for the early severity prediction of bronchopulmonary dysplasia in clinic. METHODS: We first adopted a two-step lung field extraction method by combining digital image processing and human-computer interaction to form the one-to-one corresponding image and label. The designed XSEG-Net model was then trained for segmenting the chest X-ray images, with the results being used for the analysis of heart development and clinical severity. Therein, Six-Point cardiothoracic ratio measurement algorithm based on corner detection was designed for the analysis of heart development; and the transfer learning of deep convolutional neural network models were used for the early prediction of clinical severities. RESULTS: The dice and cross-entropy loss value of the training of XSEG-Net network reached 0.9794 and 0.0146. The dice, volumetric overlap error, relative volume difference, precision, and recall were used to evaluate the trained model in testing set with the result being 98.43 ± 0.39%, 0.49 ± 0.35%, 0.49 ± 0.35%, 98.67 ± 0.40%, and 98.20 ± 0.47%, respectively. The errors between the Six-Point cardiothoracic ratio measurement method and the gold standard were 0.0122 ± 0.0084. The deep convolutional neural network model based on VGGNet had the promising prediction performance, with the accuracy, precision, sensitivity, specificity, and F1 score reaching 95.58 ± 0.48%, 95.61 ± 0.55%, 95.67 ± 0.44%, 96.98 ± 0.42%, and 95.61±0.48%, respectively. CONCLUSIONS: These experimental results of the proposed methods in lung field segmentation, cardiothoracic ratio measurement and clinic severity prediction were better than previous methods, which proved that this method had great potential for clinical application.

Symptomatic and optimal supportive care of critical COVID-19: A case report and literature review.

BACKGROUND: Coronavirus disease 2019 (COVID-19) severity is classified as asymptomatic, mild, moderate, severe, and critical. Mild cases account for a large percentage of cases in the epidemic and typically exhibit a favorable prognosis. However, a 49%-67% mortality is noted in critical cases. No COVID-19-specific drug has been reported to date, and symptomatic and optimal supportive care, including oxygenation, anti-coinfection treatments, and ventilation, represent the mainstay of treatment for this disease, especially in critical patients. CASE SUMMARY: In the above-mentioned context, we share our experience with the treatment of one critical COVID-19 case and review the relevant literature. CONCLUSION: Timely tracheal intubation, reasonable mechanical ventilation support, appropriate anti-infection treatment, and early anticoagulation and immunity support are key factors in the successful treatment of this case.

Chinese Expert Consensus on Protection for Ultrasound Healthcare Workers against COVID-19.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has caused a worldwide pandemic and poses a serious public health risk. It has been proven that lung ultrasound can be extremely valuable in the diagnosis and treatment of the disease, which could also minimize the number of exposed healthcare workers and equipment. Because healthcare workers in ultrasound departments are in close contact with patients who might be infected or virus carriers, it is extremely important that they be provided sufficient protection. Extremely aggressive protection should be avoided because it might lead to a lack of protection equipment for the hospital. Guidance on proper protection management should be provided in detail, for example, how to choose personal protective equipment, how to disinfect the environment. To address these problems, on behalf of the Chinese Ultrasound Doctors Association, Chinese PLA Professional Committee of Ultrasound in Medicine, Beijing Institute of Ultrasound in Medicine and Chinese Research Hospital Association Ultrasound Professional Committee, the authors have summarized the recommendations for effective protection according to existing hygienic standards, their experience and available literature. After the recommendations were completed, two online conferences were held on January 31, 2020 and February 7, 2020, at which the recommendations were discussed in detail. A modified version of the work was circulated and finally approved by all authors, and is the present Chinese Expert Consensus on Protection for Ultrasound Healthcare Workers against COVID-19.

Prolonged prothrombin time at admission predicts poor clinical outcome in COVID-19 patients.

BACKGROUND: The prognostic value of coagulation disorder in coronavirus disease 2019 (COVID-19) patients should be demonstrated. AIM: To investigate the abnormalities of coagulation parameters in the patients with COVID-19 and their prognostic values. METHODS: Consecutive patients admitted in the isolation ward of Renmin Hospital of Wuhan University from January 31 to February 5, 2020 with confirmed COVID-19 were included. The primary outcomes were death and survival as of March 11. Demographics, vital signs, comorbidities and laboratory tests were collected and compared between those who died and survivors. Logistic regression analysis for prognostic factors was performed. Kaplan-Meier analysis was used to compare the estimated survival rate between patients with prolonged prothrombin time and normal prothrombin time. RESULTS: The total number of patients with confirmed COVID-19 who were enrolled was 213. The median age was 62 years, and 95 patients (44.6%) were men. Fifty-one patients were critical (23.9%), 79 patients were severe (37.1%) and 83 patients were moderate (39%). As of March 11, 2020, 99 patients were discharged (46.5%), 79 patients (37.1%) stayed in the hospital and 35 patients (16.2%) died. Median time to death was 6 (4-8) d, while median hospital stay was 32 (22-36) d in survivors (P < 0.001). More men (P = 0.002) and elderly patients (P < 0.001) were found in the group of those who died. The respiration rate at admission was higher in the group of those who died (P < 0.001). The incidences of hypertension (P = 0.028), cerebrovascular disease (P < 0.001), chronic kidney disease (P = 0.02) and chronic obstructive pulmonary disease (P < 0.001) were higher in the group of those who died. Platelet count was decreased in the group of those who died (P = 0.002) whereas prothrombin time (P < 0.001), activated partial thromboplastin time (P = 0.033), concentration of D-dimer (P < 0.001) and fibrin degradation products (P < 0.001) were increased in the group of those who died. Prothrombin time [odds ratio (OR): 2.19, P = 0.004], respiration rate (OR: 1.223, P < 0.001), age (OR: 1.074, P < 0.001) and fibrin degradation products concentration (OR: 1.02, P = 0.014) were predictors of death. The survival rate was significantly lower in patients with prolonged prothrombin time compare to those with normal prothrombin time (P < 0.001). CONCLUSION: Prothrombin time, concentration of fibrin degradation products, respiration rate and age were predictive factors for clinical outcomes of COVID-19 patients.

Infection Control against COVID-19 in Departments of Radiology.

The COVID-19 epidemic, which is caused by the novel coronavirus SARS-CoV-2, has spread rapidly to become a world-wide pandemic. Chest radiography and chest CT are frequently used to support the diagnosis of COVID-19 infection. However, multiple cases of COVID-19 transmission in radiology department have been reported. Here we summarize the lessons we learned and provide suggestions to improve the infection control and prevention practices of healthcare workers in departments of radiology.