A new perspective to improve the treatment of Lianhuaqingwen on COVID-19 and prevent the environmental health risk of medication.

Lianhuaqingwen (LH), one traditional Chinese medicine (TCM), has been used to treat the coronavirus disease 2019 (COVID-19), but its ecotoxicity with potential human health security has not been well investigated. To overcome such adverse effects and improve its medication efficacy, an intelligent multi-method integrated dietary scheme, screening, and performance evaluation approach was developed. Thirteen LH compounds were selected, and the main protease (Mpro) was used as the potential drug target. Resulted information showed that the more compounds of LH added, the higher medication efficacy obtained using multi-method integrated screening system, expert consultation method, and molecular dynamics simulation. Pharmacodynamic mechanism analysis showed that low total energy and polar surface area of LH active compound (i.e., ß-sitosterol) will contribute to the best therapeutic effect on COVID-19 using quantitative structure-activity relationships (QSAR) and sensitivity models. Additionally, when mild COVID-19 patients take LH with the optimum dietary scheme (i.e., ß-lactoglobulin, α-lactalbumin, vitamin A, vitamin B, vitamin C, carotene, and vitamin E), the medication efficacy were significantly improved (23.58%). Pharmacokinetics and toxicokinetics results showed that LH had certain human health risks and ecotoxicity. This study revealed the multi-compound interaction mechanism of LH treatment on COVID-19, and provided theoretical guidance for improving therapeutic effect, evaluating TCM safety, and preventing human health risk.

Psychological Health and Sleep Quality of Medical Graduates During the Second Wave of COVID-19 Pandemic in Post-epidemic Era.

Recently, a COVID-19 virus variant spread rapidly in Guangzhou, China, causing public panic. This study aimed to understand the psychological and sleep-related consequences of the secondary outbreak of the pandemic on medical students. In this cross-sectional survey-based study, participants anonymously completed structured questionnaires online from June 8-22, 2021. We collected participants' demographic and general information. Anxiety, depression, and sleep quality were measured using the Zung Self-Rating Anxiety Scale (SAS), Self-Rating Depression Scale (SDS), and Pittsburgh Sleep Quality Index (PSQI), respectively. Protective factors were assessed using the Coping Style Questionnaire (CSQ). Uni- and multivariate logistic regression analyses were performed examining factors associated with mental health and sleep quality problems. During the second wave of the pandemic in local outbreak areas in Guangzhou, China, more than one-third of medical students' mental health and sleep quality were affected. The prevalence of anxiety, depression, and poor sleep quality were 27.54%, 27.58%, and 18.19%, respectively. Students belonging to the Class of 2019, aged over 29 years, those with siblings, and those whose hometowns were in other provinces were more prone to the three health problems. Factors associated with an increased risk of mental health problems were vaccination status (adjusted odds ratio 1.603-1.839) and diet status (adjusted odds ratio 1.62-1.929). Positive coping styles served as protective factors (p < 0.05). We discovered that completed vaccination status, good diet, and positive coping styles were related to good mental health and sleep quality.

Psychological Behavior, Work Stress, and Social Support of Frontline Nurses During the COVID-19 Pandemic.

Using a cluster sampling method, 248 nurses from frontline departments of three large general hospitals in Sichuan Province, China, were selected as participants in the current study. Risk perception and coping methods during the coronavirus disease 2019 (COVID-19) pandemic, negative emotions and psychological workload, and awareness of social support among nurses were studied. Negative emotions among nurses increased significantly, with fear being the most common (73.4%, n = 182). Psychological workload of nurses in close contact with patients with COVID-19 was higher than that of nurses in other positions (p < 0.05). Family was the major source of social support. Social support was negatively associated with depression (-0.206, p < 0.05), obsessive-compulsiveness/anxiety (-0.185, p < 0.05), and hypochondriasis (-0.234, p < 0.05). Psychological workload of nurses was positively correlated with depression (0.251, p < 0.05), neurasthenia (0.242, p < 0.05), and obsessive-compulsiveness/anxiety (0.231, p < 0.05). Nursing staff in frontline departments encountered psychological workload burdens to varying degrees during the COVID-19 pandemic. Thus, it is important to implement and strengthen psychological counseling for nurses in close contact positions, and to seek family and social support for nurses. [Journal of Psychosocial Nursing and Mental Health Services, 60(10), 21-27.].

The correlation between mental health status, sleep quality, and inflammatory markers, virus negative conversion time among patients confirmed with 2019-nCoV during the COVID-19 outbreak in China: An observational study.

ABSTRACT: The 2019 coronavirus disease (COVID-19) has spread to the whole world. Psychological and sleep problems among confirmed patients have drawn extensive attention which may be highly related to immune function and inflammatory responses of people. The aim of this study is to examine the correlation of mental health status, sleep quality, and inflammatory markers, virus negative conversion time (NCT) among confirmed patients during the COVID-19 outbreak.A cross-sectional survey was conducted in this study. Data from 66 patients assessed with demographic information, anxious symptom, depressive symptom, stress, and sleep quality were collected using a smartphone-based questionnaire platform and then clinical characteristics and laboratory indicators were collected using case review.Nearly 30% of the participants reported depression, anxiety, perceived pressure, and poor sleep quality. Compared with the group without depression, neutrophil count, and ratio of neutrophil count to lymphocyte count (NLR) in the depression disorder group were increased (P = .028, 0.043). There was also a significant difference in NLR and NCT between the anxiety group and the non-anxiety group (P = .021, .024). Similarly, compared with the good sleep quality group, NLR in the poor sleep quality group was increased (P = .011). Correlation analysis indicated that Self-Rating Depression Scale score was positively related to neutrophil count and NLR (r = 0.366, 0.330, P = .016, .031). The total score of Pittsburgh Sleep Quality Index (PSQI) was negatively related to lymphocyte count (r = -0.317, P = .049), and the sleep disturbance as 1 of the 7 dimensions of PSQI scale was positively correlated with NCT and NLR (r = 0.370, 0.340, P = .020, .034).In our study, confirmed patients were prone to have psychological and sleep problems. The level of inflammation in patients with psychological and sleep problems was higher than that in patients without corresponding problems. The inflammatory level increased with the increase of Self-Rating Depression Scale score, and the lymphocyte count decreased with the increase of the PSQI score. NCT was prolonged in the anxiety group and sleep disturbance was positively correlated with NCT.

[Structural characteristics and catalytic cycle of dihydroorotate dehydrogenase-a review].

Dihydroorotate dehydrogenase is a flavin-dependent mitochondrial enzyme to catalyze the fourth step of the de novo synthesis of pyrimidine and to oxidize dihydroorotate to orotate. By selectively inhibiting dihydroorotate dehydrogenase, thereby inhibiting pyrimidine synthesis, the enzyme has been developed for the treatment of cancer, autoimmune diseases, bacterial or viral infections, parasitic diseases and so on. The development of inhibitory drugs requires a detailed understanding of the structural characteristics and catalytic cycle mechanism of dihydroorotate dehydrogenase. Therefore, this paper reviews these two aspects, and indicates perspectives of these inhibitors in clinical application.

Prevalence and Demographic Correlates of Poor Sleep Quality Among Frontline Health Professionals in Liaoning Province, China During the COVID-19 Outbreak.

BACKGROUND: Little empirical evidence is known about the sleep quality of frontline health professionals working in isolation units or hospitals during the novel coronavirus disease (COVID-19) outbreak in China. This study thus aimed to examine the prevalence of poor sleep quality and its demographic and correlates among frontline health professionals. METHODS: This is a multicenter, cross-sectional survey conducted in Liaoning province, China. Sleep quality was measured by the Pittsburgh Sleep Quality Index (PSQI). RESULTS: A total of 1,931 frontline health professionals were recruited. The prevalence of poor sleep quality was 18.4% (95%CI: 16.6%-20.11%). Multivariate logistic regression analysis found that older age (OR=1.043, 95%CI=1.026-1.061, P < 0.001), being nurse (OR=3.132, 95%CI=1.727-5.681, P < 0.001), and working in outer emergency medical team (OR=1.755, 95%CI=1.029-3.064, P=0.039) were positively associated with poor sleep quality. Participants who were familiar with crisis response knowledge were negatively associated with poor sleep quality (OR=0.70, 95%CI=0.516-0.949, P=0.021). CONCLUSION: The prevalence of poor sleep quality was relatively low among frontline health professionals during the COVID-19 epidemic. Considering the negative impact of poor sleep quality on health professionals' health outcomes and patient outcomes, regularly screening and timely treatments are warranted to reduce the likelihood of poor sleep quality in health professionals.