Discovery of Novel Chinese Medicine Compounds Targeting 3CL Protease by Virtual Screening and Molecular Dynamics Simulation.

The transmission and infectivity of COVID-19 have caused a pandemic that has lasted for several years. This is due to the constantly changing variants and subvariants that have evolved rapidly from SARS-CoV-2. To discover drugs with therapeutic potential for COVID-19, we focused on the 3CL protease (3CLpro) of SARS-CoV-2, which has been proven to be an important target for COVID-19 infection. Computational prediction techniques are quick and accurate enough to facilitate the discovery of drugs against the 3CLpro of SARS-CoV-2. In this paper, we used both ligand-based virtual screening and structure-based virtual screening to screen the traditional Chinese medicine small molecules that have the potential to target the 3CLpro of SARS-CoV-2. MD simulations were used to confirm these results for future in vitro testing. MCCS was then used to calculate the normalized free energy of each ligand and the residue energy contribution. As a result, we found ZINC15676170, ZINC09033700, and ZINC12530139 to be the most promising antiviral therapies against the 3CLpro of SARS-CoV-2.

MA-Net:Mutex attention network for COVID-19 diagnosis on CT images.

COVID-19 is an infectious pneumonia caused by 2019-nCoV. The number of newly confirmed cases and confirmed deaths continues to remain at a high level. RT-PCR is the gold standard for the COVID-19 diagnosis, but the computed tomography (CT) imaging technique is an important auxiliary diagnostic tool. In this paper, a deep learning network mutex attention network (MA-Net) is proposed for COVID-19 auxiliary diagnosis on CT images. Using positive and negative samples as mutex inputs, the proposed network combines mutex attention block (MAB) and fusion attention block (FAB) for the diagnosis of COVID-19. MAB uses the distance between mutex inputs as a weight to make features more distinguishable for preferable diagnostic results. FAB acts to fuse features to obtain more representative features. Particularly, an adaptive weight multiloss function is proposed for better effect. The accuracy, specificity and sensitivity were reported to be as high as 98.17%, 97.25% and 98.79% on the COVID-19 dataset-A provided by the Affiliated Medical College of Qingdao University, respectively. State-of-the-art results have also been achieved on three other public COVID-19 datasets. The results show that compared with other methods, the proposed network can provide effective auxiliary information for the diagnosis of COVID-19 on CT images.

Impacts of COVID-19 pandemic on foreign trade intermodal transport accessibility: Evidence from the Yangtze River Delta region of mainland China.

We address the problem of the impacts of COVID-19 pandemic on foreign trade transport by introducing a foreign trade intermodal transport accessibility (FTITA) index. First, we present the definition of FTITA, which combines the convenience of transporting domestic cargoes to overseas regions by an international intermodal transport network and the trade attractiveness of the domestic cargoes in the overseas regions. Second, we analyze the path choice behaviors of domestic shippers and propose the measurement method of the FTITA index. Finally, using the 41 cities in the Yangtze River Delta region in mainland China as origins and eight overseas regions as destinations, we empirically analyze the impacts of COVID-19 pandemic on the FTITA. With the empirical study conducted in the prepandemic and postpandemic years, we analyzed the overall trends of the FTITAs from the YRD region to eight overseas regions, spatial patterns of the distributions of the FTITAs in the YRD region, rankings of average FTITA values for the top ten cities in the YRD region, and the FTITAs for different cargoes. The results indicate that the FTITAs of the YRD region in the prepandemic year are significantly higher than those in the postpandemic year. Moreover, in both the prepandemic and postpandemic years, the FTITAs to North America, Japan/South Korea, Europe, and Southeast Asia are significantly higher than those to Oceania, Middle East, South America, and Africa. Through analysis of the spatial patterns of the FTITAs across cities in the YRD region, we find that the cities with high FTITA are mainly close to Shanghai Port and Ningbo Port; the cities with middle-high FTITA are mainly located in southern Zhejiang and the regions along the Yangtze River; the cities with middle-low FTITA are mainly located in northern Jiangsu; and the cities with low FTITA are located in northern Anhui. Furthermore, comparing the impacts of COVID-19 pandemic on the FTITAs for different cargoes, we observe that COVID-19 has the least impact on foodstuffs and event cargoes. Our findings can guide decision makers in implementing policies for alleviating the impacts of COVID-19 pandemic on foreign trade transport and further promoting the sustainable development of port and shipping industries.

Health care worker occupational experiences during the COVID-19 outbreak: A cross-sectional study.

BACKGROUND: Health care workers treating coronavirus disease 2019 (COVID-19) patients experience burnout and stress due to overwork and poor working conditions. AIM: To investigate the work experiences of frontline health care workers in Wuhan city and Qinghai province, China, during the COVID-19 outbreak. METHODS: In this cross-sectional descriptive study, a self-reported questionnaire was designed to evaluate work experiences of medical staff throughout the course of the COVID-19 pandemic. A total of 178 health care workers responded to the questionnaire between February 19 and 29, 2020. Higher questionnaire dimen-sional score confirmed dimensional advantage. RESULTS: Of all dimensions evaluated by this questionnaire, the occupational value dimension had the highest mean score of 2.61 (0.59), followed by the support/security dimension score of 2.30 (0.74). Occupational protection scored lowest at 1.44 (0.75), followed by work environment at 1.97 (0.81). The social relationships dimension had an intermediate score of 2.06 (0.80). Significant differences in working conditions were observed across hospital departments, with the fever ward scoring lowest. Total scores also differed significantly across workplaces; the fever outpatient department scored lowest (P < 0.01). This phenomenon was likely due to the fact that work in the fever outpatient department, where many patients present to hospital, necessitates constant contact with a large number of individuals with insufficient provision of resources (such as protective equipment and social support). Medical workers in the fever outpatient department were burdened with a fear of COVID-19 infection and a lower sense of professional value as compared to workers in other hospital departments. Medical staff in Wuhan worked longer hours (P < 0.01) as compared to elsewhere. The mean support/security dimension score was higher for tertiary hospital as compared to secondary hospital medical staff as well as for Wuhan area as compared to Qinghai region staff (P < 0.01). Staff in Wuhan had a lower mean work environment score as compared to staff in Qinghai (P < 0.05). CONCLUSION: Medical staff treating COVID-19 patients in China report poor occupational experiences strongly affected by work environment, occupational protection and social relationships. Health care managers must address the occupational needs of medical staff by ensuring a supportive and safe work environment.

MA-Net:Mutex attention network for COVID-19 diagnosis on CT images

COVID-19 is an infectious pneumonia caused by 2019-nCoV. The number of newly confirmed cases and confirmed deaths continues to remain at a high level. RT–PCR is the gold standard for the COVID-19 diagnosis, but the computed tomography (CT) imaging technique is an important auxiliary diagnostic tool. In this paper, a deep learning network mutex attention network (MA-Net) is proposed for COVID-19 auxiliary diagnosis on CT images. Using positive and negative samples as mutex inputs, the proposed network combines mutex attention block (MAB) and fusion attention block (FAB) for the diagnosis of COVID-19. MAB uses the distance between mutex inputs as a weight to make features more distinguishable for preferable diagnostic results. FAB acts to fuse features to obtain more representative features. Particularly, an adaptive weight multiloss function is proposed for better effect. The accuracy, specificity and sensitivity were reported to be as high as 98.17%, 97.25% and 98.79% on the COVID-19 dataset-A provided by the Affiliated Medical College of Qingdao University, respectively. State-of-the-art results have also been achieved on three other public COVID-19 datasets. The results show that compared with other methods, the proposed network can provide effective auxiliary information for the diagnosis of COVID-19 on CT images.

The effect of glucocorticoids on mortality in severe COVID-19 patients: Evidence from 13 studies involving 6612 cases.

BACKGROUND: Since the start of the coronavirus disease 2019 (COVID-19) pandemic, there is an urgent need for effective therapies for patients with COVID-19. In this study, we aimed to assess the therapeutic efficacy of glucocorticoids in severe COVID-19. METHODS: A systematic literature search was performed across PubMed, Web of Science, EMBASE, and the Cochrane Library (up to June 26, 2021). The literature investigated the outcomes of interest were mortality and invasive mechanical ventilation. RESULTS: The search identified 13 studies with 6612 confirmed severe COVID-19 patients. Our meta-analysis found that using glucocorticoids could significantly decrease COVID-19 mortality (hazard ratio (HR) 0.60, 95% confidence interval (CI) 0.45-0.79, P < .001), relative to non-use of glucocorticoids. Meanwhile, using glucocorticoids also could significantly decrease the risk of progression to invasive mechanical ventilation for severe COVID-19 patients (HR = 0.69, 95% CI 0.58-0.83, P < .001). Compared with using dexamethasone (HR = 0.68, 95% CI 0.50-0.92, P = .012), methylprednisolone use had a better therapeutic effect for reducing the mortality of patients (HR = 0.35, 95% CI 0.19-0.64, P = .001). CONCLUSION: The result of this meta-analysis showed that using glucocorticoids could reduce mortality and risk of progression to invasive mechanical ventilation in severe COVID-19 patients.

The association between severe COVID-19 and low platelet count: evidence from 31 observational studies involving 7613 participants

A novel coronavirus disease 2019 (COVID-19) broke out at 2019 and had caused a pandemic around the world. This disease was found resulting from the infection of 2019 novel coronavirus (2019-nCoV) (Zhu, et al 2020). The severity of COVID-19 disease has a wide range and varies from asymptomatic to critical severe, clinical researches reported that 10-15% of the patients were in the severe situation and required a great deal of attention of treatment and nursing (WHO-China-Joint-Mission 2020).