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Little is known about the status of occupational well-being among the Chinese medical workers after the implementation of Normalized Epidemic Prevention and Control strategy as most studies are performed during the COVID-19 pandemic. This study was designed to investigate the occupational well-being among the medical workers in our city in the COVID-19 after the release of Normalized Epidemic Prevention and Control Strategy since May 7, 2020 in mainland China. We included the medical workers involved in the front-line of COVID-19 that were randomly selected from 7 hospitals in Inner Mongolia Autonomous Region, China. The occupational well-being among medical workers was evaluated using the modified occupational well-being scales and the symptom Checklist-90 (SCL-90) scale. Then Logistic regression analysis was given to identify the risk factors that may affect the occupational well-being among the medical workers. Our data showed that hospital type (p < 0.01), hospital grade (p < 0.01), marital status (p < 0.01) and monthly income (p < 0.01) were independent risk factors for the occupational well-being among the medical workers. Obsessive-compulsive disorder, somatization, phobic anxiety, depression and interpersonal sensitivity were risk factors for poor occupational well-being. Therefore, attention should be given to the occupational well-being of the medical workers. Meanwhile, appropriate measurements are necessary to improve their working quality.

The Coronavirus Disease 2019 (COVID-19) pandemic continues to infect people worldwide. While the vaccinated population has been increasing, the rising breakthrough infection persists in the vaccinated population. For living with the virus, the dietary guidelines to prevent virus infection are worthy of and timely to develop further. Tannic acid has been demonstrated to be an effective inhibitor of coronavirus and is under clinical trial. Here we found that two other members of the tannins family, oligomeric proanthocyanidins (OPCs) and punicalagin, are also potent inhibitors against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection with different mechanisms. OPCs and punicalagin showed inhibitory activity against omicron variants of SARS-CoV-2 infection. The water extractant of the grape seed was rich in OPCs and also exhibited the strongest inhibitory activities for viral entry of wild-type and other variants in vitro. Moreover, we evaluated the inhibitory activity of grape seed extractants (GSE) supplementation against SARS-CoV-2 viral entry in vivo and observed that serum samples from the healthy human subjects had suppressive activity against different variants of SARS-CoV-2 Vpp infection after taking GSE capsules. Our results suggest that natural tannins acted as potent inhibitors against SARS-CoV-2 infection, and GSE supplementation could serve as healthy food for infection prevention.
Since it first surfaced in late 2019, the COVID-19 pandemic has had a significant impact on people’s lives. While several vaccines have been created, infections have not disappeared. This is largely due to new variants of the virus responsible for the disease (SARS-CoV-2) emerging, which current vaccines do not work as well against. Indeed, several reports suggest that protection from the omicron variant wanes as shortly as four to six months after vaccination. Therefore, other strategies are needed to reduce the risk of SARS-CoV-2 infections. In 2022, researchers discovered that tannic acid blocked two proteins that SARS-CoV-2 needs to enter and replicate inside human cells. Tannic acid is part of the tannin family, which includes natural molecules found in plant-based meals and beverages. Here, Chen et al. – including some of the researchers involved in the 2022 studies – set out to find whether two other tannins found in nature (OPCs and punicalagin) could also inhibit SARS-CoV-2. Chen et al. administered tannic acid, OPCs and punicalagin to human cells cultured in a laboratory that had been infected with SARS-CoV-2. This revealed that all three tannins suppress the activity of the same proteins required for viral entry and replication, but to varying degrees suggesting that they block SARS-CoV-2 infections via different mechanisms. The compounds were also able to inhibit different variants of the virus, including omicron, from infecting the lab-grown cells. Further experiments revealed that water extracted from seeded grapes, which contains high levels of OPCs, could also block SARS-CoV-2 entry in the cell culture system. To test this further, Chen et al. gave 18 healthy individuals capsules containing different concentrations of grape seed extract and collected samples of their serum. The serum samples suppressed entry of different variants of SARS-CoV-2 in the cell culture system, with serums from subjects that received the higher dose having the greatest effect. These findings suggest that naturally occurring tannins can suppress multiple variants of SARS-CoV-2 from entering and replicating in cells. Consuming supplements of grape seed extract could potentially reduce the risk of SARS-CoV-2 infections. However, further experiments, including clinical trials, are needed to test this possibility.

Cervical cancer has killed millions of women over the past decade. In 2019 the World Health Organization launched the Cervical Cancer Elimination Strategy, which included ambitious targets for vaccination, screening, and treatment. The COVID-19 pandemic disrupted progress on the strategy, but lessons learned during the pandemic - especially in vaccination, self-administered testing, and coordinated mobilization on a global scale - may help with efforts to achieve its targets. However, we must also learn from the failure of the COVID-19 response to include adequate representation of global voices. Efforts to eliminate cervical cancer will only succeed if those countries most affected are involved from the very start of planning. In this article we summarize innovations and highlight missed opportunities in the COVID response, and make recommendations to leverage the COVID experience to accelerate the elimination of cervical cancer globally.

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Over the past 15 years, interest in additive manufacturing (AM) on lattice structures has significantly increased in producing 3D/4D objects. The purpose of this study is to gain a thorough grasp of the research pattern and the condition of the field\'s research today as well as identify obstacles towards future research. To accomplish the purpose, this work undertakes a scientometric analysis of the international research conducted on additive manufacturing for lattice structure materials published from 2002 to 2022. A total of 1290 journal articles from the Web of Science (WoS) database and 1766 journal articles from the Scopus database were found using a search system. This paper applied scientometric science, which is based on bibliometric analysis. The data were subjected to a scientometric study, which looked at the number of publications, authorship, regions by countries, keyword co-occurrence, literature coupling, and scientometric mapping. VOSviewer was used to establish research patterns, visualize maps, and identify transcendental issues. Thus, the quantitative determination of the primary research framework, papers, and themes of this research field was possible. In order to shed light on current developments in additive manufacturing for lattice structures, an extensive systematic study is provided. The scientometric analysis revealed a strong bias towards researching AM on lattice structures but little concentration on technologies that emerge from it. It also outlined its unmet research needs, which can benefit both the industry and academia. This review makes a prediction for the future, with contributions by educating researchers, manufacturers, and other experts on the current state of AM for lattice structures.

This study aims to bridge the gap that has remained unfilled after the initial scrutiny and reporting of the damaging effects of Covid-19 on financial markets. The study analyzes 10 European stock markets and compares their pre and post covid return dynamics. Our findings are surprisingly pleasant, albeit counterintuitive to some. We observe a quick and unprecedented recovery in the European stock market, yielding significantly higher returns post covid, given a reasonably large holding period. We also observe an alteration and change in the status quo of countries while transmitting or receiving cross-market spillovers.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA contamination was reported on China\'s imported frozen foods and packaging materials. However, there was no evidence of this disease initiated by environment-to-human transmission until the outbreak of coronavirus disease 2019 (COVID-19) in Beijing in June 2020. This article aimed to analyze and summarize COVID-19 outbreaks related to cold-chain foods to provide a scientific basis for tracing the epidemiological trajectory of the pandemic, providing risk assessments, and mitigation policies. Overall, 37 COVID-19 outbreaks and 5,741 infected cases were reported within the study period. It was found that 7 outbreaks and 689 cases were linked to imported frozen foods. The first index case among the 7 outbreaks was exposed to SARS-CoV-2-contaminated outer packaging of frozen food, triggering the subsequent community transmission. This study supported the speculation that cold-chain foods act as a pathway for SARS-CoV-2 and might present a risk for virus transmission between countries and regions. Handlers and processors exposed to the imported frozen foods should be effectively self-protected, daily monitored for clinical manifestations of COVID-19, and tested for SARS-CoV-2 nucleic acid at regular intervals.

This is the first systematic review and meta-analysis to determine the factors that contribute to poor antibody response in organ transplant recipients after receiving the 2-dose severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine.
Data was obtained from Embase, PubMed, Web of Science, Cochrane Library, China National Knowledge Infrastructure (CNKI), and Chinese Biomedical Literature Database (CBM). Studies reporting factors associated with antibody responses to the 2-dose SARS-CoV-2 vaccine in solid organ transplant recipients were included in our study based on the inclusion and exclusion criteria. Two researchers completed the literature search, screening, and data extraction. Randomized models were used to obtain results. Egger\'s test was performed to determine publication bias. Sensitivity analysis was performed to determine the stability of the result. The heterogeneity was determined using the Galbraith plot and subgroup analysis.
A total of 29 studies were included in the present study. The factors included living donor, BNT162b2, tacrolimus, cyclosporine, antimetabolite, mycophenolic acid (MPA) or mycophenolate mofetil (MMF), azathioprine, corticosteroids, high-dose corticosteroids, belatacept, mammalian target of rapamycin (mTOR) inhibitor, tritherapy, age, estimated glomerular filtration rate (eGFR), hemoglobin, and tacrolimus level were significantly different. Multivariate analysis showed significant differences in age, diabetes mellitus, MPA or MMF, high-dose corticosteroids, tritherapy, and eGFR.
The possible independent risk factors for negative antibody response in patients with organ transplants who received the 2-dose SARS-CoV-2 vaccine include age, diabetes mellitus, low eGFR, MPA or MMF, high-dose corticosteroids, and triple immunosuppression therapy. mTOR inhibitor can be a protective factor against weak antibody response.
PROSPERO, identifier CRD42021257965.

Population size has made disease monitoring a major concern in the healthcare system, due to which auto-detection has become a top priority. Intelligent disease detection frameworks enable doctors to recognize illnesses, provide stable and accurate results, and lower mortality rates. An acute and severe disease known as Coronavirus (COVID19) has suddenly become a global health crisis. The fastest way to avoid the spreading of Covid19 is to implement an automated detection approach. In this study, an explainable COVID19 detection in CT scan and chest X-ray is established using a combination of deep learning and machine learning classification algorithms. A Convolutional Neural Network (CNN) collects deep features from collected images, and these features are then fed into a machine learning ensemble for COVID19 assessment. To identify COVID19 disease from images, an ensemble model is developed which includes, Gaussian Naive Bayes (GNB), Support Vector Machine (SVM), Decision Tree (DT), Logistic Regression (LR), K-Nearest Neighbor (KNN), and Random Forest (RF). The overall performance of the proposed method is interpreted using Gradient-weighted Class Activation Mapping (Grad-CAM), and t-distributed Stochastic Neighbor Embedding (t-SNE). The proposed method is evaluated using two datasets containing 1,646 and 2,481 CT scan images gathered from COVID19 patients, respectively. Various performance comparisons with state-of-the-art approaches were also shown. The proposed approach beats existing models, with scores of 98.5% accuracy, 99% precision, and 99% recall, respectively. Further, the t-SNE and explainable Artificial Intelligence (AI) experiments are conducted to validate the proposed approach.