The Exploration of Prolonged Mask Use on Appearance Anxiety during the COVID-19 Pandemic in Taiwan (preprint)

(1) Background: This study aimed to explore how prolonged mask use during the COVID-19 pandemic affected appearance anxiety; (2) Methods: It implemented a quantitative–qualitative mixed-research approach based on a convenience sample of young people in Taiwan; (3) Results: A total of 1,118 participants completed the online questionnaire. A total of 49 participants reached the 55-point threshold of Appearance Anxiety Scale. Higher score of appearance anxiety was correlated to higher state anxiety statistically (r = 0.4, p < 0.001). Ten participants were interviewed and qualitative content analysis revealed 5 main themes and 16 subthemes. Three of the main themes were related to the positive effects of wearing masks for pandemic prevention and reducing appearance anxiety: “Wearing masks indicates compliance with the epidemic prevention requirement,” “Wearing masks functions as protection against lack of confidence in appearance,” and “Wearing masks helps mitigate the fear of being judged by others.” The remaining two “Wearing masks shifts attention from appearance to figure” and “Prolonged mask wearing exacerbates the anxiety about taking it off” were related to the impacts of long-term mask use; (4) Conclusions: results enhance understanding of negative emotional experiences and anxiety related to physical appearance.

Unbalanced emission reductions of different species and sectors in China during COVID-19 lockdown derived by multi-species surface observation assimilation

The unprecedented lockdown of human activities during the COVID-19 pandemic has significantly influenced social life in China. However, understanding the impact of this unique event on the emissions of different species is still insufficient, prohibiting the proper assessment of the environmental impacts of COVID-19 restrictions. Here we developed a multi-air-pollutant inversion system to simultaneously estimate the emissions of NOx, SO2, CO, PM2.5 and PM10 in China during COVID-19 restrictions with high temporal (daily) and horizontal (15 km) resolutions. Subsequently, contributions of emission changes versus meteorological variations during the COVID-19 lockdown were separated and quantified. The results demonstrated that the inversion system effectively reproduced the actual emission variations in multi-air pollutants in China during different periods of COVID-19 lockdown, which indicate that the lockdown is largely a nationwide road traffic control measure with NOx emissions decreasing substantially by ∼40 %. However, emissions of other air pollutants were found to only decrease by∼10% because power generation and heavy industrial processes were not halted during lockdown, and residential activities may actually have increased due to the stay-at-home orders. Consequently, although obvious reductions of PM2.5 concentrations occurred over the North China Plain (NCP) during the lockdown period, the emission change only accounted for 8.6 % of PM2.5 reductions and even led to substantial increases in O3. The meteorological variation instead dominated the changes in PM2.5 concentrations over the NCP, which contributed 90 % of the PM2.5 reductions over most parts of the NCP region. Meanwhile, our results suggest that the local stagnant meteorological conditions, together with inefficient reductions of PM2.5 emissions, were the main drivers of the unexpected PM2.5 pollution in Beijing during the lockdown period. These results highlighted that traffic control as a separate pollution control measure has limited effects on the coordinated control of O3 and PM2.5 concentrations under current complex air pollution conditions in China. More comprehensive and balanced regulations for multiple precursors from different sectors are required to address O3 and PM2.5 pollution in China.

Correction: Yu et al. Comparison of Physical and Biochemical Characterizations of SARS-CoV-2 Inactivated by Different Treatments. Viruses 2022, 14, 1938.

In the original publication [...].

Does the Message Frame Promote People's Willingness to Vaccinate when they Worry about Side Effects from the COVID-19 Vaccine? Evidence from an Online Survey Experiment in China.

Vaccination is an effective strategy for controlling the coronavirus disease 2019 (COVID-19) pandemic. However, worrying about side effects (WSE) from the COVID-19 vaccine is the leading concern making people hesitant to get vaccinated. Regrettably, there are few studies on alleviating the negative impacts of WSE on COVID-19 vaccination. This study aimed to assess whether message framing (gain- and loss-framed) can moderate the impacts of WSE on the willingness to vaccinate. We conducted an online self-administered survey experiment with three groups: control group (non-framed group), gain-framed groups, and loss-framed groups. In total, 981 participants were randomly assigned to one of the three groups, and their willingness to vaccinate themselves, their children, and elderly members was recorded. People with a higher level of WSE exhibited a lower willingness to vaccinate against COVID-19. However, the gain- and loss-framed messages increased people's willingness to vaccinate themselves, their children, and the elderly. Compared to the gain-framed messages, the loss-framed messages had a greater impact on enhancing people's willingness to self-vaccinate, but not on vaccinating their children and the elderly. Although the gain- and loss-framed messages weakened the negative impacts of WSE on the willingness to be vaccinated, their buffer effect was non-significantly different. The findings in this study suggest that a loss-framed messaging strategy could be a valuable tool in disseminating information on vaccination against COVID-19.

The preclinical and clinical progress of cell sheet engineering in regenerative medicine.

Cell therapy is an accessible method for curing damaged organs or tissues. Yet, this approach is limited by the delivery efficiency of cell suspension injection. Over recent years, biological scaffolds have emerged as carriers of delivering therapeutic cells to the target sites. Although they can be regarded as revolutionary research output and promote the development of tissue engineering, the defect of biological scaffolds in repairing cell-dense tissues is apparent. Cell sheet engineering (CSE) is a novel technique that supports enzyme-free cell detachment in the shape of a sheet-like structure. Compared with the traditional method of enzymatic digestion, products harvested by this technique retain extracellular matrix (ECM) secreted by cells as well as cell-matrix and intercellular junctions established during in vitro culture. Herein, we discussed the current status and recent progress of CSE in basic research and clinical application by reviewing relevant articles that have been published, hoping to provide a reference for the development of CSE in the field of stem cells and regenerative medicine.

Management of centralized transition ward in a large general hospital in Shanghai during the epidemic caused by Severe acute respiratory syndrome coronavirus 2 omicron variant infection

The epidemic of coronavirus disease 2019 (COVID-19) has seriously affected people's normal work, life, and medical treatment. Since Mar. 2022, there has been a pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) omicron variant in Shanghai. In order to meet the needs of hospitalization for patients, and at the same time for better control of epidemic and nosocomial infections, a large hospital in Shanghai innovatively set up a centralized transition ward in the hospital, and established scientific rules of medical work, regulations for prevention of nosocomial infections and efficient norms for patient admission. During the operation of the ward, a total of 211 patients were treated and one of the patients was confirmed of COVID-19 recurrence. All work was carried out methodically, and neither hospitalized patients nor medical staff had nosocomial infection of COVID-19. The preparation, operation and management of the central transition ward in our hospital are summarized here to provide guidance and reference for general hospitals to carry out similar work under the epidemic.

Awake prone positioning in acute hypoxaemic respiratory failure.

Awake prone positioning (APP) of patients with acute hypoxaemic respiratory failure gained considerable attention during the early phases of the coronavirus disease 2019 (COVID-19) pandemic. Prior to the pandemic, reports of APP were limited to case series in patients with influenza and in immunocompromised patients, with encouraging results in terms of tolerance and oxygenation improvement. Prone positioning of awake patients with acute hypoxaemic respiratory failure appears to result in many of the same physiological changes improving oxygenation seen in invasively ventilated patients with moderate-severe acute respiratory distress syndrome. A number of randomised controlled studies published on patients with varying severity of COVID-19 have reported apparently contrasting outcomes. However, there is consistent evidence that more hypoxaemic patients requiring advanced respiratory support, who are managed in higher care environments and who can be prone for several hours, benefit most from APP use. We review the physiological basis by which prone positioning results in changes in lung mechanics and gas exchange and summarise the latest evidence base for APP primarily in COVID-19. We examine the key factors that influence the success of APP, the optimal target populations for APP and the key unknowns that will shape future research.

An ensemble prediction model for COVID-19 mortality risk.

Background: It's critical to identify COVID-19 patients with a higher death risk at early stage to give them better hospitalization or intensive care. However, thus far, none of the machine learning models has been shown to be successful in an independent cohort. We aim to develop a machine learning model which could accurately predict death risk of COVID-19 patients at an early stage in other independent cohorts. Methods: We used a cohort containing 4711 patients whose clinical features associated with patient physiological conditions or lab test data associated with inflammation, hepatorenal function, cardiovascular function, and so on to identify key features. To do so, we first developed a novel data preprocessing approach to clean up clinical features and then developed an ensemble machine learning method to identify key features. Results: Finally, we identified 14 key clinical features whose combination reached a good predictive performance of area under the receiver operating characteristic curve 0.907. Most importantly, we successfully validated these key features in a large independent cohort containing 15 790 patients. Conclusions: Our study shows that 14 key features are robust and useful in predicting the risk of death in patients confirmed SARS-CoV-2 infection at an early stage, and potentially useful in clinical settings to help in making clinical decisions.

Analysis of the prevalence and influencing factors of anxiety and depression in the Chinese population: A cross-sectional survey.

To explore the prevalence and influencing factors of anxiety and depression symptoms among Chinese people in 2021. Investigation teams were recruited in 120 cities across the country. Based on the data from "the Seventh National Population Census in 2021″, quota sampling was conducted on the residents of these cities to obtain samples that conformed to population characteristics. Next, baseline information on research objects was collected, and the questionnaire survey was conducted through the online questionnaire Wenjuanxing platform. The Patient Health Questionnaire-9 (PHQ-9) rating scale was used to evaluate the mental state of the subjects. The correlation between baseline information and different PHQ-9 risk intervals was analyzed using the Chi-square test and Logit model. The impact of relevant risk factors on PHQ-9 scores was analyzed using the decision tree. The Chi-square test results revealed that place of residence (p = 0.438) and obesity (p = 0.443) was not significantly correlated with PHQ-9 risk intervals. According to Logit model analysis, age (p = 0.001, 95%CI 0.84-0.96), marital status (p < 0.001, 95%CI 0.71-0.89), drinking (p < 0.001, 95%CI 1.07-1.18), diabetes or hypertension (p = 0.001, 95%CI 1.11-1.47), health care (p < 0.001, 95%CI 0.53-0.66), economic welfare (p = 0.022, 95%CI 0.85-0.99), COVID-19 vaccine (p < 0.001, 95%CI 1.28-1.72), and HPV vaccine (p < 0.001, 95%CI 0.46-0.57) were potential influencing factors of PHQ-9 risk intervals. Decision tree analysis results showed that the grouping strategy in the PHQ-9 two-side groups had a better classification effect on the questionnaire population according to the PHQ-9 score characteristics. The prevalence rate of moderate to severe depression among Chinese people was about 8.29%. Age, marital status, drinking, diabetes or hypertension, health care, economic well, COVID-19 vaccine, and HPV vaccine were potential influencing factors of anxiety and depression symptoms in Chinese people.

Risk assessment of global COVID-19 pandemic in January 2023

Objective: To assess the global epidemic of Coronavirus disease 2019 (COVID-19) in January 2023 and the risk of importation. Methods: According to the daily COVID-19 data publicly released by Johns Hopkins University, combined with the travel restrictions published by Sherpa, an epidemiological description method was used to provide a comprehensive and timely assessment of the global epidemic risk through a general overview, a comprehensive assessment of the epidemic trends in each continent and key countries, as well as a comprehensive analysis of the epidemic and travel requirements in 14 neighbouring countries. Results: Compared with the previous month, the number of confirmed cases and deaths respectively decreased by 40.37% and increased by 147.95% globally in January 2023. Daily new confirmed cases showed a decreasing trend, while deaths in all continents stayed stable except Asia in January. The time taken for every 50 million new confirmed cases and 500 thousand deaths globally has increased slightly. The number of deaths in Japan, America, China, and Australia increased rapidly. Zambia, Argentina, New Zealand and Mexico were the countries that showed a sharp rise in the number of deaths in January. Russia was the country with special concern among the 14 neighbouring countries. Conclusion: The global daily new confirmed cases and deaths showed a downward trend in January, but the epidemic situation was prominent in some regions and countries. It is necessary to continuously monitor countries with global focus and establish a communication mechanism with relevant agencies to exchange information and provide timely warnings.

Awake Prone Positioning in Non-Intubated Patients With Acute Hypoxemic Respiratory Failure Due to COVID-19.

BACKGROUND: Awake prone positioning (APP) has been advocated to improve oxygenation and prevent intubation of patients with acute hypoxemic respiratory failure due to coronavirus disease 2019 (COVID-19). This paper aims to synthesize the available evidence on the efficacy of APP. METHODS: We performed a systematic review of proportional outcomes from observational studies to compare intubation rate in patients treated with APP or with standard care. RESULTS: A total of 46 published and 4 unpublished observational studies that included 2,994 subjects were included, of which 921 were managed with APP and 870 were managed with usual care. APP was associated with significant improvement of oxygenation parameters in 381 cases of 19 studies that reported this outcome. Among the 41 studies assessing intubation rates (870 subjects treated with APP and 852 subjects treated with usual care), the intubation rate was 27% (95% CI 19-37%) as compared to 30% (95% CI 20-42%) (P = .71), even when duration of application, use of adjunctive respiratory assist device (high-flow nasal cannula or noninvasive ventilation), and severity of oxygenation deficit were taken into account. There appeared to be a trend toward improved mortality when APP was compared with usual care (11% vs 22%), which was not statistically significant. CONCLUSIONS: APP was associated with improvement of oxygenation but did not reduce the intubation rate in subjects with acute respiratory failure due to COVID-19. This finding is limited by the high heterogeneity and the observational nature of included studies. Randomized controlled clinical studies are needed to definitively assess whether APP could improve key outcome such as intubation rate and mortality in these patients.

Lung Recruitment Assessed by Electrical Impedance Tomography (RECRUIT): A Multicenter Study of COVID-19 Acute Respiratory Distress Syndrome.

Rationale: Defining lung recruitability is needed for safe positive end-expiratory pressure (PEEP) selection in mechanically ventilated patients. However, there is no simple bedside method including both assessment of recruitability and risks of overdistension as well as personalized PEEP titration. Objectives: To describe the range of recruitability using electrical impedance tomography (EIT), effects of PEEP on recruitability, respiratory mechanics and gas exchange, and a method to select optimal EIT-based PEEP. Methods: This is the analysis of patients with coronavirus disease (COVID-19) from an ongoing multicenter prospective physiological study including patients with moderate-severe acute respiratory distress syndrome of different causes. EIT, ventilator data, hemodynamics, and arterial blood gases were obtained during PEEP titration maneuvers. EIT-based optimal PEEP was defined as the crossing point of the overdistension and collapse curves during a decremental PEEP trial. Recruitability was defined as the amount of modifiable collapse when increasing PEEP from 6 to 24 cm H2O (ΔCollapse24-6). Patients were classified as low, medium, or high recruiters on the basis of tertiles of ΔCollapse24-6. Measurements and Main Results: In 108 patients with COVID-19, recruitability varied from 0.3% to 66.9% and was unrelated to acute respiratory distress syndrome severity. Median EIT-based PEEP differed between groups: 10 versus 13.5 versus 15.5 cm H2O for low versus medium versus high recruitability (P < 0.05). This approach assigned a different PEEP level from the highest compliance approach in 81% of patients. The protocol was well tolerated; in four patients, the PEEP level did not reach 24 cm H2O because of hemodynamic instability. Conclusions: Recruitability varies widely among patients with COVID-19. EIT allows personalizing PEEP setting as a compromise between recruitability and overdistension. Clinical trial registered with www.clinicaltrials.gov (NCT04460859).

Plasma cell-free DNA promise monitoring and tissue injury assessment of COVID-19.

Coronavirus 2019 (COVID-19) is a complex disease that affects billions of people worldwide. Currently, effective etiological treatment of COVID-19 is still lacking; COVID-19 also causes damages to various organs that affects therapeutics and mortality of the patients. Surveillance of the treatment responses and organ injury assessment of COVID-19 patients are of high clinical value. In this study, we investigated the characteristic fragmentation patterns and explored the potential in tissue injury assessment of plasma cell-free DNA in COVID-19 patients. Through recruitment of 37 COVID-19 patients, 32 controls and analysis of 208 blood samples upon diagnosis and during treatment, we report gross abnormalities in cfDNA of COVID-19 patients, including elevated GC content, altered molecule size and end motif patterns. More importantly, such cfDNA fragmentation characteristics reflect patient-specific physiological changes during treatment. Further analysis on cfDNA tissue-of-origin tracing reveals frequent tissue injuries in COVID-19 patients, which is supported by clinical diagnoses. Hence, our work demonstrates and extends the translational merit of cfDNA fragmentation pattern as valuable analyte for effective treatment monitoring, as well as tissue injury assessment in COVID-19.

Risk assessment of global Coronavirus disease 2019 pandemic in December 2022

Objective: To assess the global epidemic of Coronavirus disease 2019 (COVID-19) in December 2022 and the risk of importation. Methods: According to the daily COVID-19 data publicly released by Johns Hopkins University, combined with the policy stringency index published by the University of Oxford, an epidemiological description method was used to provide a comprehensive and timely assessment of the global epidemiological risk overview, a comprehensive assessment of the epidemic trends in each continent and key countries, as well as a comprehensive analysis of the epidemic and prevention and control policies in 14 neighboring countries. The assessment results for each country are expressed as countries of gl, "countries of the general concern in each continent" and "neighboring countries of special concern". Results: Compared with the previous month, the number of confirmed cases and deaths respectively increased by 38.92% and 25.95% globally in February 2022. Daily new confirmed cases and deaths in the Asia continued to rise in December. The time taken for every new 50 mill confirmed cases and 50 thousand deaths globally has increased significantly. Japan, Korea, America and France were countries with global concern. Brazil, Argentina, Mexico, Mauritius and Australia were the countries of general concern in each continent. Russia with was the special count among the 14 neighboring countries. Conclusion: The global daily new confirmed cases and deaths showed a downward trend after mid-December, but the epidemic situation was prominent in some regions and countries. information and provide timely warnings.

Digital Therapeutics: Emerging New Therapy for Nonalcoholic Fatty Liver Disease.

The increased prevalence of nonalcoholic fatty liver disease (NAFLD) worldwide is particularly worrisome, as no medication has been approved to treat the disease. Lifestyle modifications aimed at promoting weight loss and weight maintenance remain the current first-line treatment for NAFLD. However, due to the lack of standard and scientific guidance and out-of-hospital supervision, long-term outcomes of lifestyle interventions for patients with NAFLD are often unsatisfactory. In addition, the COVID-19 pandemic aggravated this dilemma. At the same time, digital therapeutics (DTx) are expected to be a new method for the convenient management and treatment of patients with NAFLD and are attracting a great deal of attention. DTx, which provide evidence-based medicine through software programs for remote intervention in preventing, treating, or managing diseases, overcome the drawbacks of traditional treatment. The efficacy of the approach has already been demonstrated for some chronic diseases, but DTx have not been fully developed for NAFLD. This study reviews the concepts, clinical value, and practical applications related to DTx, with an emphasis on recommendations based on unmet needs for NAFLD. A better understanding of the current state will help clinicians and researchers develop high-quality, standardized, and efficient DTx products, with the aim of optimizing the prognosis of patients with NAFLD.

Longitudinal proteomic investigation of COVID-19 vaccination.

Although the development of COVID-19 vaccines has been a remarkable success, the heterogeneous individual antibody generation and decline over time are unknown and still hard to predict. In this study, blood samples were collected from 163 participants who next received two doses of an inactivated COVID-19 vaccine (CoronaVac®) at a 28-day interval. Using TMT-based proteomics, we identified 1,715 serum and 7,342 peripheral blood mononuclear cells (PBMCs) proteins. We proposed two sets of potential biomarkers (seven from serum, five from PBMCs) at baseline using machine learning, and predicted the individual seropositivity 57 days after vaccination (AUC = 0.87). Based on the four PBMC's potential biomarkers, we predicted the antibody persistence until 180 days after vaccination (AUC = 0.79). Our data highlighted characteristic hematological host responses, including altered lymphocyte migration regulation, neutrophil degranulation, and humoral immune response. This study proposed potential blood-derived protein biomarkers before vaccination for predicting heterogeneous antibody generation and decline after COVID-19 vaccination, shedding light on immunization mechanisms and individual booster shot planning.