Diagnostic value and characteristic analysis of serum nucleocapsid antigen in COVID-19 patients.

Background: To date, several types of laboratory tests for coronavirus disease 2019 (COVID-19) diagnosis have been developed. However, the clinical importance of serum severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleocapsid antigen (N-Ag) remains to be fully elucidated. In this study, we sought to investigate the value of serum SARS-CoV-2 N-Ag for COVID-19 diagnosis and to analyze N-Ag characteristics in COVID-19 individuals. Methods: Serum samples collected from 215 COVID-19 patients and 65 non-COVID-19 individuals were used to quantitatively detect N-Ag via chemiluminescent immunoassay according to the manufacturer's instructions. Results: The sensitivity and specificity of the N-Ag assay were 64.75% (95% confidence interval (95% CI) [55.94-72.66%]) and 100% (95% CI [93.05-100.00%]), respectively, according to the cut-off value recommended by the manufacturer. The receiver operating characteristic (ROC) curve showed a sensitivity of 100.00% (95% CI [94.42-100.00%]) and a specificity of 71.31% (95% CI [62.73-78.59%]). The positive rates and levels of serum SARS-CoV-2 N-Ag were not related to sex, comorbidity status or disease severity of COVID-19 (all P < 0.001). Compared with RT‒PCR, there was a lower positive rate of serum N-Ag for acute COVID-19 patients (P < 0.001). The positive rate and levels of serum SARS-CoV-2 N-Ag in acute patients were significantly higher than those in convalescent patients (all P < 0.001). In addition, the positive rate of serum SARS-CoV-2 N-Ag in acute COVID-19 patients was higher than that of serum antibodies (IgM, IgG, IgA and neutralizing antibodies (Nab)) against SARS-CoV-2 (all P < 0.001). However, the positive rate of serum SARS-CoV-2 N-Ag in convalescent COVID-19 patients was significantly lower than that of antibodies (all P < 0.001). Conclusion: Serum N-Ag can be used as a biomarker for early COVID-19 diagnosis based on appropriate cut-off values. In addition, our study also demonstrated the relationship between serum N-Ag and clinical characteristics.

Thyroid function and associated mood changes after COVID-19 vaccines in patients with Hashimoto thyroiditis.

Context: Severe acute respiratory syndrome-coronavirus 2 (COVID-19) vaccines may incur changes in thyroid functions followed by mood changes, and patients with Hashimoto thyroiditis (HT) were suggested to bear a higher risk. Objectives: We primarily aim to find whether COVID-19 vaccination could induce potential subsequent thyroid function and mood changes. The secondary aim was to find inflammatory biomarkers associated with risk. Methods: The retrospective, multi-center study recruited patients with HT receiving COVID-19-inactivated vaccines. C-reactive proteins (CRPs), thyroid-stimulating hormones (TSHs), and mood changes were studied before and after vaccination during a follow-up of a 6-month period. Independent association was investigated between incidence of mood state, thyroid functions, and inflammatory markers. Propensity score-matched comparisons between the vaccine and control groups were carried out to investigate the difference. Results: Final analysis included 2,765 patients with HT in the vaccine group and 1,288 patients in the control group. In the matched analysis, TSH increase and mood change incidence were both significantly higher in the vaccine group (11.9% versus 6.1% for TSH increase and 12.7% versus 8.4% for mood change incidence). An increase in CRP was associated with mood change (p< 0.01 by the Kaplan-Meier method) and severity (r = 0.75) after vaccination. Baseline CRP, TSH, and antibodies of thyroid peroxidase (anti-TPO) were found to predict incidence of mood changes. Conclusion: COVID-19 vaccination seemed to induce increased levels and incidence of TSH surge followed by mood changes in patients with HT. Higher levels of pre-vaccine serum TSH, CRP, and anti-TPO values were associated with higher incidence in the early post-vaccine phase.

Impact of energy depletion, human development, and income distribution on natural resource sustainability.

Constant exploitation of natural resources has resulted from the industrialization and urbanization of society. One of the possible causes of the COVID-19 pandemic is an ecological disturbance caused by excessive resource exploitation. Countries worldwide have taken precautionary measures to limit the spread of this disease because of its highly infectious nature: lockdowns, quarantines, curfews, etc. This paper explores the impacts of energy depletion and the human development index on natural resources, considering the roles of CO2 emissions and economic growth in China from 1971 to 2019. We apply advanced economic modeling using the Phillips-Ouliaris test for integration, Gaussian identity mixed-effects Generalized Linear Model, and Robust GEE population-averaged model for long-run estimates. Results explain that CO2 emissions and economic growth devalue natural resources, while the human development index and energy depletion increase them. Depletion of natural resources occurs due to overexploitation and overuse of natural resources, as well as unsustainable planning and waste. In the case of natural resources that man uses to make other resources, such as dams, roads, sports complexes, etc., these are considered human-made resources. It is, therefore, essential to develop human resources as a part of the natural resource development process. Research limitations and future directions are discussed.

Factors Influencing the Uptake of Seasonal Influenza Vaccination among Community-Dwelling Older Adults during COVID-19: A Mixed Methods Study.

Background: Despite making the influenza vaccine accessible and affordable, vaccination rates remained low among community-dwelling older adults. Therefore, this study aimed to explore the factors influencing vaccine uptake and the impact of COVID-19 on vaccine uptake among community-dwelling older adults in Singapore. Methods: A mixed methods study involving a survey and semi-structured interviews were conducted between September 2020 and July 2021. Community-dwelling older adults aged ≥ 65 years were recruited from 27 Community Nurse Posts. Data on participants' demographics, health condition(s), vaccination status, attitudes towards influenza infections and vaccinations, willingness to pay, intention for future vaccination and source of information were collected via the survey. Semi-structured interviews were conducted to understand vaccination experiences, key enablers and barriers, and the impact of COVID-19 on vaccine uptake. All interviews were analysed using Braun and Clarke's thematic analysis. Quantitative data were analysed using descriptive statistics, chi-square tests and multinomial logistic regressions. Results: A total of 235 participants completed the survey. Living arrangement was a statistically significant contributing factor for influenza vaccine uptake (ꭓ2= -0.139; p = 0.03). Participants who lived alone were 2.5 times more likely to be vaccinated than those living with others (OR = 2.504, 95% CI: 1.294-4.842, p = 0.006). Avoidance of getting infected (82.5%), avoidance of transmission to others (84.7%), and advice from healthcare professionals to receive vaccination (83.4%) were key enablers, while concerns about possible side effects (41.2%), the effectiveness of the vaccine (42.6%), and not having enough information (48.1%) were barriers. Twenty participants were interviewed. The findings were congruent with the survey results. Five themes were identified as follows: (1) Perceived importance of influenza vaccination, (2) Sphere of influence, (3) Healthcare schemes and medical subsidies, (4) Psychological impediments, and (5) Inconsistent emphases at various touch points. Conclusions: Greater public health efforts are needed to reach out to the larger population of older adults of different living arrangements and those concerned about the possible side effects and effectiveness of the influenza vaccine. Healthcare professionals need to provide more information to address these concerns, especially during COVID-19, to encourage vaccine uptake.

Risk factors and digital interventions for anxiety disorders in college students: Stakeholder perspectives.

The worldwide prevalence of anxiety disorders among college students is high, which negatively affects countries, schools, families, and individual students to varying degrees. This paper reviews the relevant literature regarding risk factors and digital interventions for anxiety disorders among college students from the perspectives of different stakeholders. Risk factors at the national and societal levels include class differences and the coronavirus disease 2019 pandemic. College-level risk factors include the indoor environment design of the college environment, peer relationships, student satisfaction with college culture, and school functional levels. Family-level risk factors include parenting style, family relationship, and parental level of education. Individual-level risk factors include biological factors, lifestyle, and personality. Among the intervention options for college students' anxiety disorders, in addition to traditional cognitive behavioral therapy, mindfulness-based interventions, psychological counseling, and group counseling, digital mental health interventions are increasingly popular due to their low cost, positive effect, and convenient diagnostics and treatment. To better apply digital intervention to the prevention and treatment of college students' anxiety, this paper suggests that the different stakeholders form a synergy among themselves. The nation and society should provide necessary policy guarantees, financial support, and moral and ethical supervision for the prevention and treatment of college students' anxiety disorders. Colleges should actively participate in the screening and intervention of college students' anxiety disorders. Families should increase their awareness of college students' anxiety disorders and take the initiative to study and understand various digital intervention methods. College students with anxiety disorders should actively seek psychological assistance and actively accept and participate in digital intervention projects and services. We believe that in the future, the application of methods such as big data and artificial intelligence to improve digital interventions and provide individualized treatment plans will become the primary means of preventing and treating anxiety disorders among college students.

A new method for solving the mobile payment scheduling problem using harris hawks optimization algorithm during the COVID-19 pandemic

The Coronavirus Disease 2019 (COVID-19) epidemic is causing once-in-a-century upheavals in global civilization. Payment systems have advanced lately, from simple cash or credit card transactions to various forms of mobile payment systems. This transformation is occurred due to COVID 19 and shifts in the economy, the growth of social networks, technical advancements on the Internet, and the increased usage of mobile devices. Throughout COVID19, this article offers a unique approach to the payment scheduling issue, which seeks out a timetable that enhances the project's stakeholders' benefit. Both the sponsor and the contractor in a project want to have a strong payment plan on their own. To create an equal schedule between the sponsor and the development team, the timing of payments and the completion periods of project activities are decided concurrently. The Harris hawks optimization method is designed to tackle the problem because of its high NP-hardness. Harris hawks optimization is a novel meta-heuristic nature-inspired optimizer inspired by how Harris hawks hunt food in nature. By comparing the suggested Harris hawks optimization optimizer to existing nature-inspired methods, the efficacy of the suggested Harris hawks optimization optimizer is determined. The Harris hawks optimization algorithm appears to be highly promising based on the statistical findings and comparisons. The MATLAB simulator's simulation findings confirm the algorithm's superiority over earlier efforts regarding energy, cost, delay time, and net value.

Systems biology approach reveals a common molecular basis for COVID-19 and non-alcoholic fatty liver disease (NAFLD).

BACKGROUND: Patients with non-alcoholic fatty liver disease (NAFLD) may be more susceptible to coronavirus disease 2019 (COVID-19) and even more likely to suffer from severe COVID-19. Whether there is a common molecular pathological basis for COVID-19 and NAFLD remains to be identified. The present study aimed to elucidate the transcriptional alterations shared by COVID-19 and NAFLD and to identify potential compounds targeting both diseases. METHODS: Differentially expressed genes (DEGs) for COVID-19 and NAFLD were extracted from the GSE147507 and GSE89632 datasets, and common DEGs were identified using the Venn diagram. Subsequently, we constructed a protein-protein interaction (PPI) network based on the common DEGs and extracted hub genes. Then, we performed gene ontology (GO) and pathway analysis of common DEGs. In addition, transcription factors (TFs) and miRNAs regulatory networks were constructed, and drug candidates were identified. RESULTS: We identified a total of 62 common DEGs for COVID-19 and NAFLD. The 10 hub genes extracted based on the PPI network were IL6, IL1B, PTGS2, JUN, FOS, ATF3, SOCS3, CSF3, NFKB2, and HBEGF. In addition, we also constructed TFs-DEGs, miRNAs-DEGs, and protein-drug interaction networks, demonstrating the complex regulatory relationships of common DEGs. CONCLUSION: We successfully extracted 10 hub genes that could be used as novel therapeutic targets for COVID-19 and NAFLD. In addition, based on common DEGs, we propose some potential drugs that may benefit patients with COVID-19 and NAFLD.

Construction and Analysis of Emotion Recognition and Psychotherapy System of College Students under Convolutional Neural Network and Interactive Technology.

This study's aim is to effectively establish a psychological intervention and treatment system for college students and discover and correct their psychological problems encountered in a timely manner. From the perspectives of pedagogy and psychology, the college students majoring in physical education are selected as the research objects, and an interactive college student emotion recognition and psychological intervention system is established based on convolutional neural network (CNN). The system takes face recognition as the data source, adopts feature recognition algorithms to effectively classify the different students, and designs a psychological intervention platform based on interactive technology, and it is compared with existing systems and models to further verify its effectiveness. The results show that the deep learning CNN has better ability to recognize student emotions than backpropagation neural network (BPNN) and decision tree (DT) algorithm. The recognition accuracy (ACC) can be as high as 89.32%. Support vector machine (SVM) algorithm is adopted to classify the emotions, and the recognition ACC is increased by 20%. When the system's K value is 5 and d value is 8, the ACC of the model can reach 92.35%. The use of this system for psychotherapy has a significant effect, and 45% of the students are very satisfied with the human-computer interaction of the system. This study aims to guess the psychology of students through emotion recognition and reduce human participation based on the human-computer interaction, which can provide a new research idea for college psychotherapy. At present, the mental health problems of college students cannot be ignored; especially every year, there will be news reports of college students' extreme behaviors due to depression and other psychological problems. An interactive college student emotion recognition and psychological intervention system based on convolutional neural network (CNN) is established. This system uses face recognition as the basic support technology and uses feature recognition algorithms to effectively classify different students. An interaction technology-based psychological intervention platform is designed and compared with existing systems and models to further verify the effectiveness of the proposed system. The results show that deep learning has better student emotion recognition ability than backpropagation neural network (BPNN) and decision tree algorithm. The recognition accuracy is up to 89.32%. Support vector machine algorithm is employed to classify emotions, and the recognition acceptability rate increases by 20%. When K is 5 and d is 8, the acceptability rate of the model can reach 92.35%. The effect of this system in psychotherapy is remarkable, and 45% of students are very satisfied with the human-computer interaction of this system. This work aims to speculate students' psychology through emotion recognition, reduce people's participation via human-computer interaction, and provide a new research idea for university psychotherapy.

A randomized, double-blind, placebo-controlled phase 1 and phase 2 clinical trial to evaluate efficacy and safety of a SARS-CoV-2 vaccine SCoK in adults.

BACKGROUND: To determine an appropriate dose of, and immunization schedule for, a vaccine SCoK against COVID-19 for an efficacy study; herein, we conducted randomized controlled trials to assess the immunogenicity and safety of this vaccine in adults. METHODS: These randomized, double-blind, placebo-controlled phase 1 and 2 trials of vaccine SCoK were conducted in Binhai District, Yan City, Jiangsu Province, China. Younger and older adult participants in phase 1 and 2 trials were sequentially recruited into different groups to be intramuscularly administered 20 or 40 µg vaccine SCoK or placebo. Participants were enrolled into our phase 1 and 2 studies to receive vaccine or placebo. RESULTS: No serious vaccine-related adverse events were observed in either trial. In both trials, local and systemic adverse reactions were absent or mild in most participants. In our phase 1 and 2 studies, the vaccine induced significantly increased neutralizing antibody responses to pseudovirus and live SARS-CoV-2. The vaccine induced significant neutralizing antibody responses to live SARS-CoV-2 on day 14 after the last immunization, with NT50s of 80.45 and 92.46 in participants receiving 20 and 40 µg doses, respectively; the seroconversion rates were 95.83% and 100%. The vaccine SCoK showed a similar safety and immunogenicity profiles in both younger participants and older participants. The vaccine showed better immunogenicity in phase 2 than in phase 1 clinical trial. Additionally, the incidence of adverse reactions decreased significantly in phase 2 clinical trial. The vaccine SCoK was well tolerated and immunogenic.

Psychological effects and associated factors among vaccinated and unvaccinated general population against COVID-19 infection in Bangladesh.

Background: The global effort to develop herd immunity in the general public against the COVID-19 pandemic is currently ongoing. However, to the best of our knowledge, there have been no studies on how the COVID-19 vaccine affects mental health in the context of the COVID-19 pandemic in Bangladesh. The present study investigated the psychological effects and associated factors among vaccinated and unvaccinated general populations against COVID-19 infection in Bangladesh. Methods: A nationwide online cross-sectional survey was conducted in Bangladesh from June 23 to December 25, 2021. The frequency of symptoms of psychological distress, depression, anxiety, stress, post-traumatic stress disorder (PTSD), insomnia, and fear was assessed using the Bangla versions of the GHQ-12, PHQ-2, GAD-2, PSS-4, PC-PTSD-5, ISI, and FCV-19S scales, respectively. Results: The study included 3,013 persons from all eight divisions of Bangladesh, with 1,272 (42.2%) being vaccinated and 1,741 (57.8%) being unvaccinated. Compared with unvaccinated populations, vaccinated populations had significantly lower prevalence rates of psychological distress (36.4 vs. 51.5%), depression (21.1 vs. 37.9%), anxiety (25.1 vs. 44.9%), stress (19.4 vs. 30.4%), PTSD (29.4 vs. 38.3%), insomnia (18.7 vs. 39.4%), and fear symptoms (16.1 vs. 27.5%). Among vaccinated populations, respondents who lived in nuclear families were significantly associated with higher risk of psychological distress (AOR, 1.38; 95% CI, 1.09-1.78), depression (AOR, 1.49; 95% CI, 1.11-1.98), anxiety (AOR, 1.77; 95% CI, 1.21-1.98), and fear (AOR, 1.43; 95% CI, 1.11-1.83) symptoms. Participants who lost family members, friends, or colleagues due to the COVID-19 pandemic had significantly higher risk of symptoms of psychological distress (AOR, 1.35; 95% CI, 1.02-1.79), anxiety (AOR, 1.41; 95% CI, 1.11-1.87), and PTSD (AOR, 1.76; 95% CI, 1.24-2.19). On the other hand, unvaccinated populations who lived in the Dhaka division were significantly associated with an increased risk of depression (AOR, 2.06; 95% CI, 1.40-2.52), anxiety (AOR, 1.86; 95% CI, 1.15-2.47), stress (AOR, 1.92; 95% CI, 1.12-2.88), and insomnia (AOR, 1.88; 95% CI, 1.20-2.94) symptoms. Except for PTSD and fear symptoms, unemployed participants had considerably higher rates of psychological distress, depression, anxiety, stress, and insomnia symptoms (e.g., psychological distress: AOR, 1.83; 95% CI, 1.10-2.62; depression: AOR, 1.74; 95% CI, 1.37-2.19). Conclusions: This study recommends immunizing unvaccinated populations as soon as possible to prevent infection and boost mental health. Vulnerable people needed special care, health-related education, and psychological assistance.

Obesity and clinical outcomes in COVID-19 patients without comorbidities, a post-hoc analysis from ORCHID trial.

Objective: Large body of studies described individuals with obesity experiencing a worse prognosis in COVID-19. However, the effects of obesity on the prognosis of COVID-19 in patients without comorbidities have not been studied. Therefore, the current study aimed to provide evidence of the relationship between obesity and clinical outcomes in COVID-19 patients without comorbidities. Methods: A total of 116 hospitalized COVID-19 patients without comorbidities from the ORCHID study (Patients with COVID-19 from the Outcomes Related to COVID-19 Treated with Hydroxychloroquine among Inpatients with Symptomatic Disease) were included. Obesity is defined as a BMI of ≥30 kg/m2. A Cox regression analysis was used to estimate the hazard ratio (HR) for discharge and death after 28 days. Results: The percentage of obesity in COVID-19 patients without comorbidities was 54.3% (63/116). Discharge at 28 days occurred in 56/63 (84.2%) obese and 51/53 (92.2%) non-obese COVID-19 patients without comorbidities. Four (3.4%) COVID-19 patients without any comorbidities died within 28 days, among whom 2/63 (3.2%) were obese and 2/53 (3.8%) were non-obese. Multivariate Cox regression analyses showed that obesity was independently associated with a decreased rate of 28-day discharge (adjusted HR: 0.55, 95% CI: 0.35-0.83) but was not significantly associated with 28-day death (adjusted HR: 0.94, 95% CI: 0.18-7.06) in COVID-19 patients without any comorbidities. Conclusions: Obesity was independently linked to prolonged hospital length of stay in COVID-19 without any comorbidity. Larger prospective trials are required to assess the role of obesity in COVID-19 related deaths.

Mental health outcomes and associated factors among vaccinated and unvaccinated teachers against COVID-19 infection in Bangladesh

Background Vaccination of teachers is recommended during the COVID-19 pandemic to reduce the risk of infection for themselves and their students, as well as to encourage their parents to get immunized. The present study investigated the mental health outcomes and associated factors among vaccinated and unvaccinated teachers against COVID-19 infection in Bangladesh. Methods A cross-sectional survey was conducted in Bangladesh from March 4 to September 9, 2021. The frequency of symptoms of psychological distress, depression, anxiety, stress, post-traumatic stress disorder (PTSD), insomnia, and fear was assessed using the Bangla versions of the GHQ-12, PHQ-2, GAD-2, PSS-4, PC-PTSD-5, ISI, and FCV-19S scales, respectively. Results A total of 1,527 Bangladeshi teachers completed the questionnaire, with 678 (44.4%) being vaccinated and 849 (55.6%) being unvaccinated. Compared with unvaccinated teachers, vaccinated teachers had a statistically significant lower prevalence of psychological distress (35.8 vs. 42.9%), depression (37.6 vs. 46.4%), anxiety (31.9 vs. 45.1%), stress (18.3 vs. 32.0%), PTSD (33.0 vs. 43.8%), insomnia (25.2 vs. 36.9%), and fear symptoms (23.3 vs. 29.6%). Among vaccinated teachers, participants with master’s or lower degree levels had significantly higher symptoms of depression, stress, and fear than other education levels. Respondents with children had a significantly higher risk of depression, anxiety, stress, and fear symptoms than those who did not have children. Participants who lost family members, friends, or colleagues due to the COVID-19 pandemic had a significantly higher chance of experiencing symptoms of anxiety, PTSD, and fear than those who did not. On the other hand, unvaccinated male teachers were significantly associated with a higher risk of all mental health outcomes except psychological distress and PTSD symptoms compared to female teachers. Participants who were smokers had a significantly higher chance of anxiety, stress, and fear symptoms than non-smokers. Compared to participants with strong social support, those with poor social support had a higher risk of all mental health outcomes except PTSD symptoms. Conclusion This study suggests emphasizing the vaccinated to unvaccinated teachers as soon as possible to control the infection and improve mental health outcomes. Vulnerable teachers also required special attention, health-related education, and psychological support.

TCM2COVID: A resource of anti-COVID-19 traditional Chinese medicine with effects and mechanisms.

In China, traditional Chinese medicine (TCM) has been widely used for coronavirus infectious disease 2019 (COVID-19) prevention, treatment, and recovery and has played a part in the battle against the disease. A variety of TCM treatments have been recommended for different stages of COVID-19. But, to the best of our knowledge, a comprehensive database for storing and organizing anti-COVID TCM treatments is still lacking. Herein, we developed TCM2COVID, a manually curated resource of anti-COVID TCM formulas, natural products (NPs), and herbs. The current version of TCM2COVID (1) documents over 280 TCM formulas (including over 300 herbs) with detailed clinical evidence and therapeutic mechanism information; (2) records over 80 NPs with detailed potential therapeutic mechanisms; and (3) launches a useful web server for querying, analyzing and visualizing documented formulas similar to those supplied by the user (formula similarity analysis). In summary, TCM2COVD provides a user-friendly and practical platform for documenting, querying, and browsing anti-COVID TCM treatments, and will help in the development and elucidation of the mechanisms of action of new anti-COVID TCM therapies to support the fight against the COVID-19 epidemic. TCM2COVID is freely available at http://zhangy-lab.cn/tcm2covid/.

Association Between Social Support and Perceived Stress: A Cross-Sectional Study on Staffs of the Epidemic Prevention During the Covid-19 Epidemic in China.

Background: The Coronavirus Disease 2019 (COVID-19) lockdown considerably affects people's life in China, both physically and mentally. Staffs of the epidemic prevention and control in the community have played an irreplaceable role during community lockdown period in Wuhan. However, few studies have focused on their health status during epidemic prevention. This study aimed to appraise the available evidence of health conditions of them and explore the influencing factors. Method: Used a multistage sampling method, we conducted a survey in staffs of the epidemic prevention and control in the community (N = 503). Descriptive analysis was used to characterize the respondents. T-test and analysis of variance were for group differences analysis. Confirmatory factor analysis (CFA) was used to verify the scale validity, correlation analysis and pathway analysis and Structural equation model (SEM) was used to study the relationship between stress perception, social support, mental resilience and sleep quality. Statistical analysis was performed with SPSS 26.0, R version 4.1.3 and Mplus 8.3. Results: The mean Perceived Stress Scale (PSS) score of the respondents was 13.28 ± 7.31 and 51.1% had higher PSS score than the normal. In the absence of social support, people's sleeping quality and psychological resilience may decrease, their perceived stress may elevate and compromise mental health correspondingly. Social support could affect perceived stress directly, while Sleep quality and psychology resilience played significant partial mediating roles in social support affecting perceived stress. The mediating effects accounted for 50.8% of the total. Conclusion: Staffs of the epidemic prevention and control in the community suffered from poor sleep quality and high level of stress perception. Establishment of good social support may effectively reduce their stress and this effect is mediated by sleep quality and psychological resilience. Physical health status would affect the staffs' mental health and they more attention should be paid to those with poor physical health.

Facing a Real Threat of Death: Dynamic Changes in Death-Thought Accessibility.

Purpose: This study explored the relationship between emotion and death-thought accessibility (DTA) in individuals experiencing true mortality salience (MS), specifically, patients with cancer. Patients and Methods: The study included 255 participants; among them, 132 patients had cancer and represented the MS group, and 123 had dental pain and served as a control group. Participants completed the Projective Diseases Attitude Assessment Questionnaire to induce priming, completed an affect scale, completed one of four calculation tasks as manipulation of cognitive load (all four were done over several sessions), and performed a Pinyin-Chinese characters exercise to measure DTA. Results: MS was associated with strong negative emotional arousal. When these negative emotions are generated, they enter an individual's consciousness and activate proximal defense mechanisms. At this point, DTA can be measured. Patients with cancer had significantly higher levels of DTA in the high-frequency cognitive load condition than in the other three conditions (no task, simple delay task, and single cognitive load task). Patients with dental pain had significantly higher levels of DTA in the no task and simple delay conditions than in the single cognitive load or high-frequency cognitive load conditions. This study also found that negative experiences without MS (specifically, dental pain) are associated with higher levels of DTA. Conclusion: These findings suggest that in addition to death-related events, both negative and stress-inducing events can produce DTA.

Mechanism of Huoxiang Zhengqi oral liquid in the treatment of COVID-19 based on biological information technology

Objective: To explore the network regulation mechanism of Huoxiang Zhengqi Oral Liquid(HXZQ) in the treatment of coronavirus disease 19 (COVID-19).

Application of 2019 Novel Coronavirus (2019-nCoV) specific antibody detection for suspected cases screening

Comparing the accuracy of antibody detection reagents which based on different principles by the diagnosis of suspected cases of new crown, propose an efficient screening plan for suspected cases, and further provide a scientific basis for establishing a clinical screening path for high-risk populations. For 76 suspected cases of COVID-19 that were transferred to designated hospitals for isolation and observation due to the initial IgM antibody test, nasopharyngeal swab nucleic acid tests, serum trace virus neutralizing antibodies and three commercially available antibody test reagents with different principles were tested, combined with lung CT and the examination and clinical symptoms or other information, comprehensively judge the diagnosis or exclusion of the new crown, and compare the three kinds of serological antibody detection reagents with the clinical judgment results to compare the detection rates of the three detection methods. Through comprehensive judgment, 3 suspected cases are confirmed cases, and 73 suspected cases are excluded cases. Compared with the clinical diagnosis/exclusion results, among the three serological antibody detection methods, the chemiluminescence total antibody kit detect positive for all the 9 serums collected from the 3 confirmed cases in different time points, the detection specificity is 97.26% for 73 excluded cases, it's significantly higher than that of the chemiluminescence method IgM/IgG and the colloidal gold method IgM/IgG Separate testing (the specificity is 73.97% on the first day of admission). The chemiluminescence method for the detection of total antibodies to the 2019-nCoV has high sensitivity and high specificity, and can be used for preliminary screening of antibody detection in suspected cases. For the screening of target populations, the 2019-nCoV nucleic acid test should be performed first. If the nucleic acid test is negative, the screening path with the detection of serum total antibodies as the main indicator should be adopted.

Facilitating technology-based character learning in emergency remote teaching

The study reports pedagogical adaptations that Chinese language instructors made to support students' character learning during emergency remote teaching in 2020. Data from an online questionnaire and follow-up interviews show that the handwriting requirement in the language curriculum was ified to way to technology-based instruction, making the conventionally isolated and solitary task of character learning more integrative and interactive. Beginning-level instructors' use of technology in character instruction was correlated with their self-confidence, perceived time sufficiency, technology access, and support received. Meanwhile, intermediate- and upper-level instructors' self-confidence and perceived values of online teaching were factors associated with their technology use. The crucial role of teacher communities in offering language-specific training and peer support is emphasized, and implications to the broader field of foreign language teaching are discussed.

Factors Associated With Psychological Outcomes Among Vaccinated and Unvaccinated Health Care Workers Against COVID-19 Infection in Bangladesh.

Background: Vaccination of healthcare workers (HCWs) is recommended during the COVID-19 pandemic to reduce the risk of infection for themselves and their patients, as well as to encourage their patients to get immunized. The present study aimed to investigate the psychological outcomes and associated factors among vaccinated and unvaccinated HCWs against COVID-19 infection in Bangladesh. Methods: From March to August 2021, an online nationwide survey was conducted with a total of 2,038 Bangladeshi HCWs. The frequency of symptoms of general health problems, depression, anxiety, stress, post-traumatic stress disorder, insomnia, and loneliness was assessed using the Bangla versions of the GHQ-12, PHQ-2, GAD-2, PSS-4, PC-PTSD-5, ISI, and UCLA-LS scales, respectively. Results: Compared with unvaccinated HCWs (n = 1,058), vaccinated HCWs (n = 980) had a statistically significant lower prevalence of general health problems (16.7 vs. 59.1%), depression (15.6 vs. 31.9%), post-traumatic stress disorder (22.3 vs. 30.8%), insomnia (23.8 vs. 64.9%), and loneliness symptoms (13.9 vs. 21.8%). Among vaccinated HCWs, females were significantly associated with a higher risk of symptoms of general health problems (AOR, 2.71; 95% CI, 0.97-7.60), anxiety (AOR, 2.17; 95% CI, 1.14-4.13), and loneliness (AOR, 2.52; 95% CI, 1.11-5.73). Except for anxiety and post-traumatic stress disorder symptoms, participants living in urban areas had a significantly lower risk of all psychological outcomes (e.g., depression: AOR, 0.43; 95% CI, 0.27-0.67; stress: AOR, 0.64; 95% CI, 0.47-0.88). Respondents who were married were significantly less likely to experience symptoms of general health problems (AOR, 0.10; 95% CI, 0.02-0.39), depression (AOR, 0.31; 95% CI, 0.22-0.82), insomnia (AOR, 0.46; 95% CI, 0.20-1.03), and loneliness (AOR, 0.31; 95% CI, 0.10-0.92). Participants who worked as doctors were significantly less chance of experiencing symptoms of general health problems (AOR, 0.18; 95% CI, 0.08-0.37), depression (AOR, 0.51; 95% CI, 0.30-0.87), and anxiety (AOR, 0.54; 95% CI, 0.37-0.78). On the other hand, unvaccinated HCWs who were 18-29 years old and had <5 years of work experience were significantly associated with a higher risk of all psychological outcomes except anxiety and insomnia symptoms (e.g., depression among 18-29 years old: AOR, 1.83; 95% CI, 0.27-2.60; stress among those with <5 years of work experience: AOR, 2.37; 95% CI, 0.93-6.07). Participants who worked as nurses were significantly more likely to suffer from depression (AOR, 1.44; 95% CI, 0.84-2.46), anxiety (AOR, 1.42; 95% CI, 0.24-1.73), and stress (AOR, 1.55; 95% CI, 0.31-0.89) symptoms. Except for anxiety and stress symptoms, respondents who worked as frontline workers and provided direct care to infected patients were the significantly higher chance of experiencing all psychological outcomes (e.g., depression among who worked as frontline workers: AOR, 2.41; 95% CI, 0.23-3.73; insomnia among those who provide direct care to infected patients: AOR, 2.60; 95% CI, 0.34-3.06). Participants who were infected with COVID-19 had a significantly less chance of experiencing symptoms of general health problems (AOR, 0.89; 95% CI, 0.65-1.22), depression (AOR, 0.66; 95% CI, 0.48-0.92), and anxiety (AOR, 0.63; 95% CI, 0.46-0.87). Conclusions: To control the infection and improve psychological outcomes, this study suggests emphasizing the vaccinated to unvaccinated HCWs as soon as possible. They also required special attention, health-related education, and psychological support.