Background:Coronavirus disease 2019 , formerly known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and 2019 novel coronavirus (2019-nCoV), was first identified in December 2019 in Wuhan City, China. Structural equation modeling (SEM) is a multivariate analysis method to determine the structural relationship between measured variables. This observational study aimed to use SEM to determine the effects of social support on sleep quality and function of medical staff who treated patients with COVID-19 in January and February 2020 in Wuhan, China. Material/Methods:A one-month cross-sectional observational study included 180 medical staff who treated patients with COVID-19 infection. Levels of anxiety, self-efficacy, stress, sleep quality, and social support were measured using the and the Self-Rating Anxiety Scale (SAS), the General Self-Efficacy Scale (GSES), the Stanford Acute Stress Reaction (SASR) questionnaire, the Pittsburgh Sleep Quality Index (PSQI), and the Social Support Rate Scale (SSRS), respectively. Pearson's correlation analysis and SEM identified the interactions between these factors. Results:Levels of social support for medical staff were significantly associated with self-efficacy and sleep quality and negatively associated with the degree of anxiety and stress. Levels of anxiety were significantly associated with the levels of stress, which negatively impacted self-efficacy and sleep quality. Anxiety, stress, and self-efficacy were mediating variables associated with social support and sleep quality. Conclusions:SEM showed that medical staff in China who were treating patients with COVID-19 infection during January and February 2020 had levels of anxiety, stress, and self-efficacy that were dependent on sleep quality and social support.

The presence of COVID-19 has had psychological consequences among health personnel; these include fear, anxiety, and depression. In the current study, we used the Fear of COVID-19 Scale (FCV-19S) to assess the response to fear within health staff in Mexico. This was a cross-sectional survey study in which we administered the FCV-19S to hospital staff. A total of 2,860 participants-1,641 female and 1,218 male personnel from three hospitals-were included in the study. We found a global FCV-19S mean score of 19.3 ± 6.9, with a signi cant difference in scores for women and men. There was a high correlation between items 3, 5, 6, and 7, suggesting that these items could indicate the physiological responses to fear, and a high correlation between items 1, 2, and 4, suggesting these items could represent the emotional responses to fear. Our survey shows a signi cantly higher level of fear in nursing and administrative personnel, which may be explained by the nursing staff being in close contact with infected patients and the administrative staff lacking understanding of the possible implications of the infection, compared with nonclinical hospital personnel. The FCV-19S showed validity and reliability in our population to assess fear in response to COVID-19. Our results are consistent with those of other researchers.

Human activity causes vibrations that propagate into the ground as high-frequency seismic waves. Measures to mitigate the COVID-19 pandemic caused widespread changes in human activity, leading to a months-long reduction in seismic noise of up to 50%. The 2020 seismic noise quiet period is the longest and most prominent global anthropogenic seismic noise reduction on record. While the reduction is strongest at surface seismometers in populated areas, this seismic quiescence extends for many kilometers radially and hundreds of meters in depth. This provides an opportunity to detect subtle signals from subsurface seismic sources that would have been concealed in noisier times and to benchmark sources of anthropogenic noise. A strong correlation between seismic noise and independent measurements of human mobility suggests that seismology provides an absolute, real-time estimate of population dynamics.

Severe acute respiratory syndrome coronavirus (SARS-CoV) encodes a highly basic nucleocapsid (N) protein of 422 amino acids. Similar to other coronavirus N proteins, SARS-CoV N protein is predicted to be phosphorylated and may contain nuclear localization signals, serine/arginine-rich motif, RNA binding domain and regions responsible for selfassociation and homo-oligomerization. In this study, we demonstrate that the protein is posttranslationally modified by covalent attachment to the small ubiquitin-like modifier. The major sumoylation site was mapped to the 62 lysine residue of the N protein. Further expression and characterization of wild type N protein and K62A mutant reveal that sumoylation of the N protein drastically promotes its homo-oligomerization, and plays certain roles in the N protein-mediated interference of host cell division. This is the first report showing that a coronavirus N protein undergoes posttranslational modification by sumoylation, and the functional implication of this modification in the formation of coronavirus ribouncleoprotein complex, virion assembly and virus-host interactions.

In response to viral infection, the expression of numerous host genes, including predominantly a number of proinflammatory cytokines and chemokines, is usually up-regulated at both transcriptional and translational levels. It was noted that in cells infected with coronavirus, transcription and translation of some of these genes were differentially induced. Drastic induction of their expression at the transcriptional level was observed in cells infected with coronavirus. However, induction of the same genes at the translational level was usually found to be minimal to moderate. To investigate the underlying mechanisms, yeast two-hybrid screen was carried out using SARS-CoV proteins as baits, revealing that a subunit of the eukaryotic initiation factor 3 (eIF3), eIF3f, may interact with the N-terminal region of the SARS-CoV spike (S) protein. This interaction was subsequently confirmed by co-immunoprecipitation and immunofluorescent staining. Meanwhile, parallel experiments confirmed that eIF3f could also interact with the S protein of another coronavirus, the avian coronavirus infectious bronchitis virus (IBV). These interactions led to the inhibition of translation of a reporter gene in both in vitro expression system and intact cells. Interestingly, IBV-infected cells stably expressing a Flag-tagged eIF3f showed much higher translation of IL-6 and IL-8, suggesting that the interaction between coronavirus S protein and eIF3f plays a functional role in controlling the expression of host genes, especially genes that are induced during coronavirus infection cycles. This study reveals a novel mechanism exploited by coronavirus to regulate viral pathogenesis.

(-)-Epigallocatechin-3-gallate (EGCG) is the most abundant catechin in green tea. In this study, we found that hepatitis C virus (HCV) infection was significantly suppressed by EGCG in an HCV cell culture (HCVcc) system using a JFH1-GFP chimeric virus, with a 50 % effective concentration (EC(50)) of 17.9 μM. The inhibitory activity of EGCG was confirmed by monitoring HCV RNA and protein expression levels in Huh7.5.1 cells infected with the JFH1 virus. Moreover, we demonstrated that the inhibitory mechanisms of EGCG were attributable to the suppression of both the HCV entry and RNA replication steps, although EGCG had little effect on translation directed by the viral internal ribosome entry site (IRES). Furthermore, HCV could be rapidly eliminated from cell cultures after two and five passages in the presence of 50 and 25 μM EGCG, respectively. These results indicate that EGCG is a potential candidate as a preventive and antiviral drug for HCV infection.

BackgroundAmong millions of people who suffer from schistosomiasis in China, adolescents are at increased risk to be infected. However, there is a lack of theory-guided behavioral prevention intervention programs to protect these adolescents. This study attempted to apply the Protection Motivation Theory (PMT) in predicting intentions to engage in protective behaviors against schistosomiasis infection.MethodsThe participants were selected using the stratified cluster sampling method. Survey data were collected using anonymous self-reported questionnaire. The advanced structural equation modeling (SEM) method was utilized to assess the complex relationship among schistosomiasis knowledge, previous risk exposure and protective measures in predicting intentions to engage in protective behavior through the PMT constructs.Principal FindingsApproximately 70% of participants reported they were always aware of schistosomiasis before exposure to water with endemic schistosomiasis, 6% of the participants reported frequency of weekly or monthly prior exposure to snail-conditioned water. 74% of participants reported having always engaged in protective behaviors in the past three months. Approximately 7% were unlikely or very unlikely to avoid contact with snail-conditioned water, and to use protective behaviors before exposure. Results from SEM analysis indicated that both schistosomiasis knowledge and prior exposure to schistosomiasis were indirectly related to behavior intentions through intrinsic rewards and self-efficacy; prior protective behaviors were indirectly related to behavior intentions through severity, intrinsic rewards and self-efficacy, while awareness had an indirect relationship with behavior intentions through self-efficacy. Among the seven PMT constructs, severity, intrinsic rewards and self-efficacy were significantly associated with behavior intentions.ConclusionsThe PMT can be used to predict the intention to engage in protective behaviors against schistosomiasis. Schistosomiasis intervention programs should focus on the severity, intrinsic rewards and self-efficacy of protection motivation, and also increase the awareness of infection, and enrich the contents of schistosomiasis education.

Seismic noise with frequencies above 1 Hz is often called “cultural noise” and is generally correlated quite well with human activities. Recently, cities in mainland China and Italy imposed restrictions on travel and day-to-day activity in response to COVID-19, which gave us an unprecedented opportunity to study the relationship between seismic noise above 1 Hz and human activities. Using seismic records from stations in China and Italy, we show that seismic noise above 1 Hz was primarily generated by the local transportation systems. The lockdown of the cities and the imposition of travel restrictions led to an ∼4–12  dB decrease in seismic noise power in mainland China. Data also show that different Chinese cities experienced distinct periods of diminished cultural noise, related to differences in local response to the epidemic. In contrast, there was only ∼1–6  dB decrease of seismic noise power in Italy, after the country was put under a lockdown. The noise data indicate that traffic flow did not decrease as much in Italy and show how different cities reacted distinctly to the lockdown conditions.