Sleep disturbance and anxiety symptoms among asymptomatic COVID-19 carriers in Shanghai, China: the mediating role of entrapment and defeat.

BACKGROUND: The COVID-19 pandemic increases the risk of psychological problems, especially for the infected population. Sleep disturbance and feelings of defeat and entrapment are well-documented risk factors of anxiety symptoms. Exploring the psychological mechanism of the development of anxiety symptoms is essential for effective prevention. This study aimed to examine the mediating effects of entrapment and defeat in the association between sleep disturbance and anxiety symptoms among asymptomatic COVID-19 carriers in Shanghai, China. METHODS: A cross-sectional study was conducted from March to April, 2022. Participants were 1,283 asymptomatic COVID-19 carriers enrolled from the Ruijin Jiahe Fangcang Shelter Hospital, Shanghai (59.6% male; mean age = 39.6 years). Questionnaire measures of sleep disturbance, entrapment, defeat, anxiety symptoms, and background characteristics were obtained. A mediation model was constructed to test the mediating effects of entrapment and defeat in the association between sleep disturbance and anxiety symptoms. RESULTS: The prevalence rates of sleep disturbance and anxiety symptoms were 34.3% and 18.8%. Sleep disturbance was positively associated with anxiety symptoms (OR [95%CI] = 5.013 [3.721-6.753]). The relationship between sleep disturbance and anxiety symptoms (total effect: Std. Estimate = 0.509) was partially mediated by entrapment (indirect effect: Std. Estimate = 0.129) and defeat (indirect effect: Std. Estimate = 0.126). The mediating effect of entrapment and defeat accounted for 50.3% of the association between sleep disturbance and anxiety symptoms. CONCLUSION: Sleep disturbance and anxiety symptoms were prevalent among asymptomatic COVID-19 carriers. Entrapment and defeat mediate the association between sleep disturbance and anxiety symptoms. More attention is needed to monitoring sleep conditions and feelings of defeat and entrapment to reduce the risk of anxiety.

Fu-Zheng-Xuan-Fei formula promotes macrophage polarization and Th17/Treg cell homeostasis against the influenza B virus (Victoria strain) infection.

ETHNOPHARMACOLOGICAL RELEVANCE: Fu-Zheng-Xuan-Fei formula (FF) is a prescription that has been clinically used through the basic theory of traditional Chinese medicine (TCM) for treating viral pneumonia. Although FF possesses a prominent clinical therapeutic effect, seldom pharmacological studies have been reported on its anti-influenza B virus (IBV) activity. AIM OF THE STUDY: Influenza is an acute infectious respiratory disease caused by the influenza virus, which has high annual morbidity and mortality worldwide. With a global decline in the COVID-19 control, the infection rate of influenza virus is gradually increasing. Therefore, it is of great importance to develop novel drugs for the effective treatment of influenza virus. Apart from conventional antiviral drugs, TCM has been widely used in the clinical treatment of influenza in China. Therefore, studying the antiviral mechanism of TCM can facilitate the scientific development of TCM. MATERIALS AND METHODS: Madin-Darby canine kidney cells (MDCK) and BALB/c mice were infected with IBV, and FF was added to evaluate the anti-IBV effects of FF both in vitro and in vivo by Western blotting, immunofluorescence, flow cytometry, and pathological assessment. RESULTS: It was found that FF exhibited anti-viral activity against IBV infection both in vivo and in vitro, while inducing macrophage activation and promoting M1 macrophage polarization. In addition, FF effectively regulated the signal transducer and activator of transcription (STAT) signaling pathway-mediated Th17/Treg balance to improve the lung tissue damage caused by IBV infection-induced inflammation. The findings provided the scientific basis for the antiviral mechanism of FF against IBV infection. CONCLUSIONS: This study shows that FF is a potentially effective antiviral drug against IBV infection.

Antiviral effects of Atractyloside A on the influenza B virus (Victoria strain) infection.

Influenza viruses pose a serious threat to human health, infecting hundreds of millions of people worldwide each year, resulting in a significant increase in global morbidity and mortality. Influenza activity has declined at the onset of the COVID-19 pandemic, but the genetic diversity of B/Victoria lineage viruses has increased significantly during this period. Therefore, the prevention and treatment of the influenza B Victoria strain virus should continue to attract research attention. In this study, we found that Atractyloside A (AA), one of the effective components in Atractylodes lancea (Thunb.) DC shows potential antiviral properties. This study shows that AA not only possesses anti-influenza B virus infection effects in vivo and in vitro but also can regulate macrophage polarization to the M2 type, which can effectively attenuate the damage caused by influenza B virus infection. Therefore, Atractyloside A may be an effective natural drug against B/Victoria influenza infection.

Antiviral effects of Atractyloside A on the influenza B virus (Victoria strain) infection

Influenza viruses pose a serious threat to human health, infecting hundreds of millions of people worldwide each year, resulting in a significant increase in global morbidity and mortality. Influenza activity has declined at the onset of the COVID-19 pandemic, but the genetic diversity of B/Victoria lineage viruses has increased significantly during this period. Therefore, the prevention and treatment of the influenza B Victoria strain virus should continue to attract research attention. In this study, we found that Atractyloside A (AA), one of the effective components in Atractylodes lancea (Thunb.) DC shows potential antiviral properties. This study shows that AA not only possesses anti-influenza B virus infection effects in vivo and in vitro but also can regulate macrophage polarization to the M2 type, which can effectively attenuate the damage caused by influenza B virus infection. Therefore, Atractyloside A may be an effective natural drug against B/Victoria influenza infection.

A novel hybrid multi-criteria group decision-making approach with intuitionistic fuzzy sets to design reverse supply chains for COVID-19 medical waste recycling channels.

The COVID-19 pandemic has led to exponential growth in COVID-19 medical waste (CMW) generation worldwide. This tremendous growth in CMW is a major transmission medium for COVID-19 virus and thus brings serious challenges to medical waste (MW) management. Designing an efficient and reliable CMW reverse supply chain in this situation can help to prevent epidemic spread. Nowadays, the assessment of CMW recycling channels has become a challenging mission for health-care institutions, especially in developing countries. It can be seen as a complex multi-criteria group decision-making (MCGDM) problem that requires the consideration of multiple conflicting tangible and intangible criteria. Nevertheless, few academics have been concerned about this issue. Moreover, current MCGDM methods have limited support for CMW recycling channel evaluation and they do not consider hospitals' reverse supply chain strategy when evaluating. Thus, this study presents a novel MCGDM approach based on intuitionistic fuzzy sets (IFSs) and the VIKOR method for assessing the capacity of CWM recycling channels. According to the characteristics of CMW, processing flow and the TOE (Technology, Organization and Environment) theoretical framework, we established a new CMW recycling channel capacity evaluation index system which makes our proposed method more targeted and efficient. In the decision-making process, we integrate the best-worst method (BWM) and entropy to determine the decision makers (DMs) weighting in a more comprehensive way, considering both subjective and objective criteria, which was ignored by many MCGDM methods. A new aggregation operator called IFWA is proposed by us, considering the priority of DMs. Based on both the ranking of capacity and disposal charges, we then position the alternatives in the recycling channel priority index (RCPI) matrix constructed by us. According to this PCPI matrix and the reverse supply chain strategy of hospitals, a more reasonable CMW allocation strategy is determined and a more efficient CMW reverse supply chain is designed. Finally, a real case study from Wuhan was examined to illustrate the validation of our approach.

Prediction Model for COVID-19 Vaccination Intention among the Mobile Population in China: Validation and Stability.

Since China's launch of the COVID-19 vaccination, the situation of the public, especially the mobile population, has not been optimistic. We investigated 782 factory workers for whether they would get a COVID-19 vaccine within the next 6 months. The participants were divided into a training set and a testing set for external validation conformed to a ratio of 3:1 with R software. The variables were screened by the Lead Absolute Shrinkage and Selection Operator (LASSO) regression analysis. Then, the prediction model, including important variables, used a multivariate logistic regression analysis and presented as a nomogram. The Receiver Operating Characteristic (ROC) curve, Kolmogorov-Smirnov (K-S) test, Lift test and Population Stability Index (PSI) were performed to test the validity and stability of the model and summarize the validation results. Only 45.54% of the participants had vaccination intentions, while 339 (43.35%) were unsure. Four of the 16 screened variables-self-efficacy, risk perception, perceived support and capability-were included in the prediction model. The results indicated that the model has a high predictive power and is highly stable. The government should be in the leading position, and the whole society should be mobilized and also make full use of peer education during vaccination initiatives.

Prevalence and related factors of depression, anxiety, and insomnia among medical staff during COVID-19 pandemic

[Background] The epidemic of coronavirus disease 2019(COVID-19) seriously affects the psychological status of medical staff who directly face the risk of the disease.[Objective] This study investigates the prevalence and related factors of depression, anxiety, and insomnia among medical staff during the COVID-19 pandemic.[Methods] From February 13 to March 1, 2020, a network questionnaire survey was conducted among 482 medical staff selected by convenience sampling. A self-designed questionnaire was used to investigate the basic demographic information and COVID-19-related questions. The Patient Health Questionnaire-9(PHQ-9), Generalized Anxiety Disorder-7(GAD-7), and Insomnia Severity Index(ISI) were used to estimate the prevalence of depression, anxiety, and insomnia among the medical staff. Stepwise multiple linear regression analysis was performed with PHQ-9 score, GAD-7 score, and ISI score as dependent variables. Multivariate logistic regression analysis(forward-conditional method) on depression, anxiety, and insomnia as dependent variables was performed with basic demographic information and COVID-19-related questions as independent variables. [Results] Among the surveyed medical staff, the prevalence rates of depression, anxiety, and insomnia were 14.3%, 11.2%, and 23.2%, respectively. There were no significant differences in the prevalence rates among different age, gender, local risk level, and occupation groups and those aiding Hubei Province or not. The medical staff who directly contacted fever or diagnosed patients had more serious depression(b=1.73, 95% CI: 0.79-2.66) and insomnia(b=2.43, 95% CI: 1.48-3.39) and a higher risk of insomnia(OR=1.89, 95% CI: 1.21-2.96). The medical staff whose current protective measures cannot prevent infection had more serious depression(b=1.72, 95% CI: 0.65-2.80), anxiety(b=1.75, 95% CI: 0.76-2.75), and insomnia(b=1.73, 95% CI: 0.63-2.82), and had a higher risk of depression(OR=1.97, 95% CI: 1.11-3.49), anxiety(OR=3.00, 95% CI: 1.64-5.46), and insomnia(OR=1.79, 95% CI: 1.08-2.96).[Conclusion] During the COVID-19 epidemic, the risks of depression, anxiety, and insomnia among selected medical staff are increased compared with the non-epidemic period. Occupational exposure to high-risk groups and protective measures would significantly affect mental health of medical staff.

Blockchain Use in IoT for Privacy-Preserving Anti-Pandemic Home Quarantine

The outbreak of the respiratory disease caused by the new coronavirus (COVID-19) has caused the world to face an existential health crisis. To contain the infectious disease, many countries have quarantined their citizens for several weeks to months and even suspended most economic activities. To track the movements of residents, the governments of many states have adopted various novel technologies. Connecting billions of sensors and devices over the Internet, the so-called Internet of Things (IoT), has been used for outbreak control. However, these technologies also pose serious privacy risks and security concerns with regards to data transmission and storage. In this paper, we propose a blockchain-based system to provide the secure management of home quarantine. The privacy and security attributes for various events are based on advanced cryptographic primitives. To demonstrate the application of the system, we provide a case study in an IoT system with a desktop computer, laptop, Raspberry Pi single-board computer, and the Ethereum smart contract platform. The obtained results prove its ability to satisfy security, efficiency, and low-cost requirements.