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2.
Int J Disaster Risk Reduct ; 74: 102928, 2022 May.
Article in English | MEDLINE | ID: covidwho-1763752

ABSTRACT

Introduction: The 2019 coronavirus disease (COVID-19) pandemic has burdened and threatened the psychological health of people around the world, especially those of front-line medical staff. This study aimed to explore the mental-health status and its associated factors amongst the medical workforce of Xinjiang province under the normalisation of the COVID-19 epidemic prevention and control. Methods: A total of 408 medical staff were recruited from February 20 to March 10, 2021. Symptom Checklist 90 (SCL-90) scale, Social support Scale, and Simplified Coping-Style Questionnaire were applied to assess their mental-health status and stress-coping tendency. Descriptive analyses, welch's T-test, chi-square test, and binary logistic regression were used to analyse the data. Results: The prevalence of mental-health problems was 20.25% (80/395) amongst the surveyed medical staff, and their total symptom mean score (1.31 ± 0.40) was lower than that of the general population (1.44 ± 0.43). Logistic regression analysis revealed that nurse, individual with poor health condition, those who lived with their elderly parents at home, those receiving less social support, and those with a negative stress-coping style were more likely to show psychological problems. Conclusion: More attention should be paid to the mental state of the medical workforce during the COVID-19 pandemic. The government and professional institutes should facilitate social supportive activities and essential counselling services to help strengthen the psychological resilience of medical staff. Additionally, it is necessary for health administration committee and hospitals to make COVID-19 prevention practice guides and risk communication principles for improving the mental health of the front-line medical staff.

3.
SciFinder; 2020.
Preprint | SciFinder | ID: ppcovidwho-1989

ABSTRACT

This article intends to use mol. docking technol. to find potential inhibitors that can respond to 2019-nCoV from active compounds in Mongolian medicine. Mongolian medicine with anti-inflammatory and antiviral effects is selected from Mongolian medicine prescription preparations TCMSP, ETCM database and document mining methods were used to collect active compounds Swiss TargetPrediction and SuperPred server were used to find targets of compounds with smiles number Drugbank and Genecard database were used to collect antiviral drug targets. Then the above targets were compared and analyzed to screen out antiviral targets of Mongolia medicine. Metascape database platform was used to enrich and analyze the GO (Gene ontol.) annotation and KEGG pathway of the targets. In view of the high homol. of gene sequences between 2019-nCoV S-protein RBD domain and SARS virus, as well as their similarities in pathogenesis and clin. manifestations, we established 2019-nCoV's S-protein model using Swiss-Model. The ZDOCK protein docking software was applied to dock the S-protein with the human angiotensin ACE2 protein to find out the key amino acids of the binding site. Taking ACE2 as the receptor, the mol. docking between the active ingredients and the target protein was studied by using AutoDock mol. docking software. The interaction between ligand and receptor is applied to provide a choice for screening anti-2019-nCoV drugs. A total of 253 active components were predicted. Metascape anal. showed that key candidate targets were significantly enriched in multiple pathways related to different toxins. These key candidate targets were mainly derived from phillyrin and chlorogenic acid. Through the protein docking between S-protein and ACE2, it is found that Glu329/Gln325 and Gln42/Asp38 in ACE2 play an important role in the binding process of the two. The results of mol. docking virtual calculation showed that phillyrin and chlorogenic acid could stably combine with Gln325 and Gln42/Asp38 in ACE2, resp., which hindered the combination between S-protein and ACE2. Phillyrin and chlorogenic acid can effectively prevent the combination of 2019-nCoV S-protein and ACE2 at the mol. level. Phillyrin and chlorogenic acid can be used as potential inhibitors of 2019-nCoV for further research and development.

4.
J Funct Foods ; 71: 104016, 2020 Aug.
Article in English | MEDLINE | ID: covidwho-276140

ABSTRACT

OBJECTIVE: This article intends to use molecular docking technology to find potential inhibitors that can respond to COVID-19 from active compounds in Mongolian medicine. METHODS: Mongolian medicine with anti-inflammatory and antiviral effects is selected from Mongolian medicine prescription preparations. TCMSP, ETCM database and document mining methods were used to collect active compounds. Swiss TargetPrediction and SuperPred server were used to find targets of compounds with smiles number. Drugbank and Genecard database were used to collect antiviral drug targets. Then the above targets were compared and analyzed to screen out antiviral targets of Mongolia medicine. Metascape database platform was used to enrich and analyze the GO (Gene ontology) annotation and KEGG pathway of the targets. In view of the high homology of gene sequences between SARS-CoV-2 S-protein RBD domain and SARS virus, as well as their similarities in pathogenesis and clinical manifestations, we established SARS-CoV-2 S-protein model using Swiss-Model. The ZDOCK protein docking software was applied to dock the S-protein with the human angiotensin ACE2 protein to find out the key amino acids of the binding site. Taking ACE2 as the receptor, the molecular docking between the active ingredients and the target protein was studied by AutoDock molecular docking software. The interaction between ligand and receptor is applied to provide a choice for screening anti-COVID-19 drugs. RESULTS: A total of 253 active components were predicted. Metascape analysis showed that key candidate targets were significantly enriched in multiple pathways related to different toxins. These key candidate targets were mainly derived from phillyrin and chlorogenic acid. Through the protein docking between S-protein and ACE2, it is found that Glu329/Gln325 and Gln42/Asp38 in ACE2 play an important role in the binding process of the two. The results of molecular docking virtual calculation showed that phillyrin and chlorogenic acid could stably combine with Gln325 and Gln42/Asp38 in ACE2, respectively, which hindered the combination between S- protein and ACE2. CONCLUSION: Phillyrin and chlorogenic acid can effectively prevent the combination of SARS-CoV-2 S-protein and ACE2 at the molecular level. Phillyrin and chlorogenic acid can be used as potential inhibitors of COVID-19 for further research and development.

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