Study of fusion peptide release for the spike protein of SARS-CoV-2.

The spike protein of SARS-CoV-2 can recognize the ACE2 membrane protein on the host cell and plays a key role in the membrane fusion process between the virus envelope and the host cell membrane. However, to date, the mechanism for the spike protein recognizing host cells and initiating membrane fusion remains unknown. In this study, based on the general assumption that all three S1/S2 junctions of the spike protein are cleaved, structures with different forms of S1 subunit stripping and S2' site cleavage were constructed. Then, the minimum requirement for the release of the fusion peptide was studied by all-atom structure-based MD simulations. The results from simulations showed that stripping an S1 subunit from the A-, B- or C-chain of the spike protein and cleaving the specific S2' site on the B-chain (C-chain or A-chain) may result in the release of the fusion peptide, suggesting that the requirement for the release of FP may be more relaxed than previously expected.

Negative elements of cryptocurrencies: Exploring the drivers of Bitcoin carbon footprints

This paper adopts an interactive network approach to investigate the factors driving the carbon footprint of Bitcoin, a negative aspect of cryptocurrencies. Our findings demonstrate that the dynamics of Bitcoin prices, including both returns and volatility, have a significant impact on the system comprising carbon emissions, energy prices, carbon prices, and financial indicators. Particularly during the first two years of the COVID-19 pandemic period, the spillover effects are observed to be particularly strong. Furthermore, we find that the dynamics of Bitcoin prices play a crucial role in driving its associated carbon emissions.

Learning from real world data about combinatorial treatment selection for COVID-19.

COVID-19 is an unprecedented global pandemic with a serious negative impact on virtually every part of the world. Although much progress has been made in preventing and treating the disease, much remains to be learned about how best to treat the disease while considering patient and disease characteristics. This paper reports a case study of combinatorial treatment selection for COVID-19 based on real-world data from a large hospital in Southern China. In this observational study, 417 confirmed COVID-19 patients were treated with various combinations of drugs and followed for four weeks after discharge (or until death). Treatment failure is defined as death during hospitalization or recurrence of COVID-19 within four weeks of discharge. Using a virtual multiple matching method to adjust for confounding, we estimate and compare the failure rates of different combinatorial treatments, both in the whole study population and in subpopulations defined by baseline characteristics. Our analysis reveals that treatment effects are substantial and heterogeneous, and that the optimal combinatorial treatment may depend on baseline age, systolic blood pressure, and c-reactive protein level. Using these three variables to stratify the study population leads to a stratified treatment strategy that involves several different combinations of drugs (for patients in different strata). Our findings are exploratory and require further validation.

Upgrading Island Tourism Value from the Perspective of the Tourist Experience—A Case Study of Tianheng Island, China

Although island tourism is vital to the economy of developing countries, many islands with great potential for tourism development do not plan for it adequately. The objective of this paper is to establish an island tourism value mining and promotion model from the tourist perspective by selecting the status value indicators of basic conditions, vacation tourism resources, and sightseeing tourism resources, as well as the promotion indicators of five types of recreational fisheries, including beach activities, recreational fishing, marine sports, rock climbing, and sightseeing platforms. Then, we evaluate the whole island and develop suitable areas by using an analytic hierarchy process. This study took Tianheng Island as an example and divided the study area into grids and land use types. The results indicate that the basic conditions and tourism resources of Tianheng Island are in a general level, and the vacation tourism resources are in high quality, while there is further room to improve them. We identified that the island has four areas which are suitable for scenic development, two sandy beaches, two recreation fishing areas, one marine sports area, and one island rock climbing area. Our findings are consistent with the actual situation in Tianheng Island, demonstrating that the model is practical and can provide an essential reference for the scientific protection and utilization of island tourism resources.

Social asset or social liability? How partisanship moderates the relationship between social capital and Covid-19 vaccination rates across United States counties.

This study investigates the interactive effect of social capital and partisanship on COVID-19 vaccination rates. Using county-level data from the United States (U.S.), we empirically find that social capital is a double-edged sword. Its effect on the vaccination rate depends on the dominant partisanship of the jurisdiction. In more liberal counties, stronger social capital is a social asset that encourages people to seek vaccination and results in a higher vaccination rate. In contrast, in more conservative counties where the Trump-voting rate reaches 73% and beyond, stronger social capital becomes a social liability for public health by reinforcing residents' hesitancy toward or rejection of vaccinations, leading to a lower vaccination rate. This study implies the need for reducing the partisanship salience and investing in bridging and linking social capital in polarized communities.

Mask Wearing Detection Based on Inceptionv4 and Multi-Scale Retinex Image Enhancement Algorithm

The novel coronavirus is a contagious virus with a high mortality rate, and the international health emergency due to COVID-19 has never stopped since the outbreak, due to this situation, wearing masks has become a basic recommended public epidemic prevention approach for many countries. In the current shortage of medical human resources, we urgently need a non-artificial mask-wearing detection method. In this paper, the multi-scale Retinex algorithm is involved as the preprocessing step of the input image. The mask-wearing detection is based on the InceptionV4 convolutional neural network model. During the experiment, we compared and verified the superiority of the Inception part of the InceptionV4 model compared with the Stem structure of the GoogLenet model, and from LFW (Labeled Faces in the Wild), RMFD (Real-World-Masked-Face-Dataset) more than 10,000 samples were selected from the public datasets for model training. Finally, the precise rate reaches 97.3 %.

Effects of the COVID-19 pandemic on acute stress disorder and career planning among healthcare students.

This study aimed to investigate the effects of COVID-19 on the prevalence of acute stress disorder and subsequent effects on career planning among healthcare students. A cross-sectional survey was conducted among 1158 healthcare students across five medical universities in February 2020. Acute stress disorder was assessed using the Stanford Acute Stress Response Questionnaire. Further data regarding COVID-19 knowledge, individual behaviours, occupational choices, and career planning were collected. Based on the results of the Stanford Acute Stress Response Questionnaire, the students were divided into high-risk and low-risk groups for acute stress disorder. The correlation between acute stress disorder and the impact on career planning was analysed. The high-risk group comprised 143 (12.3%) participants, while 1015 (87.7%) participants were in the low-risk group. Two factors increased the risk of acute stress disorder in the students, including 'I think the pandemic is far away from me' (B: 1.27, 95%CI: 1.60-7.87) and 'Physical contact with confirmed or suspected cases' (B: 2.49, 95%CI: 3.42-42.44). Those who obtained pandemic information from official media sources indicated a lower risk of acute stress disorder (B: -0.24, 95%CI: 0.49-1.26). The high-risk group was more likely to quit the medical profession after graduation. The COVID-19 pandemic may cause acute stress disorder among healthcare students and affect their career planning. Universities and relevant departments should provide more information and moral support for these students.

Management Strategies for Patients After CABG Surgery in the Outbreak of the COVID-19 Pandemic.

BACKGROUND: The novel coronavirus 2019 pandemic (COVID-19) has quickly spread over the world and affected over 100 countries so far. Patients with pre-existing cardiovascular disease may have a higher risk of infection of COVID-19 and worse outcomes than others. To improve the outcome during the pandemic, management strategies for the patients recovering from coronary artery bypass graft (CABG) surgery need to be reconsidered. METHODS: Some precaution advices including self-protection, blood glucose and blood pressure controlling are recommended for the patients recovering from CABG during the pandemic. They are encouraged to communicate with doctors by telephone or Internet when COVID-19 related symptoms such as cough, fever and dyspnea occur. As a follow-up strategy for patients after CABG surgery, cardiac biomarkers and CTA could also be helpful to the diagnosis of COVID-19. Some medications being investigated for COVID-19 therapy may have side effects relevant to cardiovascular disease. Appropriate personal protection equipment (PPE) is necessary for cardiovascular health-care workers operating in clinical settings. RESULTS: There was zero out of over 300 follow-up patients after CABG surgery confirmed to be infected with COVID-19 from January to June 2020. No cardiovascular health-care workers were reported to be infected neither in the Second Xiangya Hospital during the pandemic. CONCLUSION: The management strategy here we proposed could improve the outcome of patients after CABG during the pandemic and benefit both cardiovascular patients and health-care workers.