Identifying conditions for a third dose intention of COVID-19 vaccination in college students: A fuzzy-set qualitative comparative analysis.

Background: During the pandemic, a third dose of the COVID-19 vaccine effectively reduces the proportion of severe cases in those infected, but vaccine hesitancy impedes this reasonable prevention method. Epidemic control in China is being tested due to the large population base, especially in crowded places like college campuses. This study aimed to explore the configuration paths of psychological antecedents for college students to receive a third COVID-19 vaccine. Methods: An anonymous cross-sectional survey was carried out in five universities in Wuhan using convenience sampling. A long version of the 5C 7-point Likert scale was used to measure college students' intention and psychological antecedents on the third dose of the COVID-19 vaccine. A fuzzy-set Qualitative Comparative Analysis (QCA) approach was performed to explore the configuration of conditions to the vaccination willingness. Results: 31.67% of respondents surveyed did not receive their third dose of the COVID-19 vaccine. The score of intention to get the vaccine for college students who did not receive the booster vaccine was 4.93 (±1.68). Average scores of 5.19 (±1.24), 4.35 (±1.75), 4.02 (±1.45), 5.84 (±1.23), and 4.61(±1.32) were reported for confidence, complacency, constraints, calculation, and collective responsibility in them. QCA showed high confidence and collective responsibility playing a central role in third dose vaccination intention. Meanwhile, low confidence and collective responsibility are the core conditions of low vaccination willingness. Conclusion: Eliminating vaccine hesitancy necessitates focusing on the psychological antecedents of vaccination intentions to identify critical targets for policy and interventions. This study identified trust and collective responsibility are core elements of the psychological antecedents of college students' intention to receive the booster vaccine for COVID-19. To achieve herd immunity as soon as possible, health administration and campus can start with vaccine confidence-building and collective responsibility cultivation to take appropriate actions and measures to improve coverage of the booster vaccination.

Factors Affecting University Students' Sleep Quality during the Normalisation of COVID-19 Epidemic Prevention and Control in China: A Cross-Sectional Study

Background: Insufficient and poor-quality sleep have significant negative health consequences for university students in China. In this study, we aimed to assess the subjective sleep quality of university students during the normalisation of COVID-19 epidemic prevention and control in China and to identify key factors affecting their sleep quality. Materials and Methods: A cross-sectional survey was conducted among 1326 university students from Hubei Province, China. Latent profile analysis was conducted on the results of class-difference tests of sleep patterns. Multinomial logistic regression was used to explore the relationship between the influencing factors and three classes of sleep quality. Results: The overall score of sleep quality (9.18 ±3.22) among university students was assessed by using the PSQI scale, and 427 (32.20%) students reported poor sleep quality. Three distinct classes of sleep patterns were identified, namely, good sleepers (Class 1, 70.44%), poor sleep quality with less medication use (Class 2, 26.55%) and poor sleepers (Class 3, 3.01%). Conclusions: Compared with 'good sleepers', students having 'poor sleep quality with less hypnotic drug use' were influenced by their education stage, smoking habits, physical activity, depression and anxiety. Meanwhile, 'poor sleepers' may be affected by their age, origins, smoking habits, mental stress, depression and anxiety. Significant heterogeneity was confirmed in the sleep patterns of university students. Their behavioural lifestyles and mental health-related factors demonstrated different relationship patterns with sleep quality. Multiple sleep promotion interventions, including moderate aerobic exercises, psychological counselling and mindfulness training, should be regularly performed in groups to improve their sleep quality.

Egg-Derived Anti-SARS-CoV-2 Immunoglobulin Y (IgY) With Broad Variant Activity as Intranasal Prophylaxis Against COVID-19.

COVID-19 emergency use authorizations and approvals for vaccines were achieved in record time. However, there remains a need to develop additional safe, effective, easy-to-produce, and inexpensive prevention to reduce the risk of acquiring SARS-CoV-2 infection. This need is due to difficulties in vaccine manufacturing and distribution, vaccine hesitancy, and, critically, the increased prevalence of SARS-CoV-2 variants with greater contagiousness or reduced sensitivity to immunity. Antibodies from eggs of hens (immunoglobulin Y; IgY) that were administered the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein were developed for use as nasal drops to capture the virus on the nasal mucosa. Although initially raised against the 2019 novel coronavirus index strain (2019-nCoV), these anti-SARS-CoV-2 RBD IgY surprisingly had indistinguishable enzyme-linked immunosorbent assay binding against variants of concern that have emerged, including Alpha (B.1.1.7), Beta (B.1.351), Delta (B.1.617.2), and Omicron (B.1.1.529). This is different from sera of immunized or convalescent patients. Culture neutralization titers against available Alpha, Beta, and Delta were also indistinguishable from the index SARS-CoV-2 strain. Efforts to develop these IgY for clinical use demonstrated that the intranasal anti-SARS-CoV-2 RBD IgY preparation showed no binding (cross-reactivity) to a variety of human tissues and had an excellent safety profile in rats following 28-day intranasal delivery of the formulated IgY. A double-blind, randomized, placebo-controlled phase 1 study evaluating single-ascending and multiple doses of anti-SARS-CoV-2 RBD IgY administered intranasally for 14 days in 48 healthy adults also demonstrated an excellent safety and tolerability profile, and no evidence of systemic absorption. As these antiviral IgY have broad selectivity against many variants of concern, are fast to produce, and are a low-cost product, their use as prophylaxis to reduce SARS-CoV-2 viral transmission warrants further evaluation. Clinical Trial Registration: https://www.clinicaltrials.gov/ct2/show/NCT04567810, identifier NCT04567810.

Large-scale integration of meta-QTL and genome-wide association study discovers the genomic regions and candidate genes for yield and yield-related traits in bread wheat.

KEY MESSAGE: Based on the large-scale integration of meta-QTL and Genome-Wide  Association Study, 76 high-confidence MQTL regions and 237 candidate genes that affected wheat yield and yield-related traits were discovered. Improving yield and yield-related traits are key goals in wheat breeding program. The integration of accumulated wheat genetic resources provides an opportunity to uncover important genomic regions and candidate genes that affect wheat yield. Here, a comprehensive meta-QTL analysis was conducted on 2230 QTL of yield-related traits obtained from 119 QTL studies. These QTL were refined into 145 meta-QTL (MQTL), and 89 MQTL were verified by GWAS with different natural populations. The average confidence interval (CI) of these MQTL was 2.92 times less than that of the initial QTL. Furthermore, 76 core MQTL regions with a physical distance less than 25 Mb were detected. Based on the homology analysis and expression patterns, 237 candidate genes in the MQTL involved in photoperiod response, grain development, multiple plant growth regulator pathways, carbon and nitrogen metabolism and spike and flower organ development were determined. A novel candidate gene TaKAO-4A was confirmed to be significantly associated with grain size, and a CAPS marker was developed based on its dominant haplotype. In summary, this study clarified a method based on the integration of meta-QTL, GWAS and homology comparison to reveal the genomic regions and candidate genes that affect important yield-related traits in wheat. This work will help to lay a foundation for the identification, transfer and aggregation of these important QTL or candidate genes in wheat high-yield breeding.

Dynamical Variations of the Global COVID-19 Pandemic Based on a SEICR Disease Model: A New Approach of Yi Hua Jie Mu.

The ongoing coronavirus disease 2019 (COVID-19) pandemic has caused more than 150 million cases of infection to date and poses a serious threat to global public health. In this study, global COVID-19 data were used to examine the dynamical variations from the perspectives of immunity and contact of 84 countries across the five climate regions: tropical, arid, temperate, and cold. A new approach named Yi Hua Jie Mu is proposed to obtain the transmission rates based on the COVID-19 data between the countries with the same climate region over the Northern Hemisphere and Southern Hemisphere. Our results suggest that the COVID-19 pandemic will persist over a long period of time or enter into regular circulation in multiple periods of 1-2 years. Moreover, based on the simulated results by the COVID-19 data, it is found that the temperate and cold climate regions have higher infection rates than the tropical and arid climate regions, which indicates that climate may modulate the transmission of COVID-19. The role of the climate on the COVID-19 variations should be concluded with more data and more cautions. The non-pharmaceutical interventions still play the key role in controlling and prevention this global pandemic.

An efficient primary screening of COVID-19 by serum Raman spectroscopy.

The outbreak of COVID-19 coronavirus disease around the end of 2019 has become a pandemic. The preferred method for COVID-19 detection is the real-time polymerase chain reaction (RT-PCR)-based technique; however, it also has certain limitations, such as sample-dependent procedures with a relatively high false negative ratio. We propose a safe and efficient method for screening COVID-19 based on Raman spectroscopy. A total of 177 serum samples are collected from 63 confirmed COVID-19 patients, 59 suspected cases, and 55 healthy individuals as a control group. Raman spectroscopy is adopted to analyze these samples, and a machine learning support-vector machine (SVM) method is applied to the spectrum dataset to build a diagnostic algorithm. Furthermore, 20 independent individuals, including 5 asymptomatic COVID-19 patients and 5 symptomatic COVID-19 patients, 5 suspected patients, and 5 healthy patients, were sampled for external validation. In these three groups-confirmed COVID-19, suspected, and healthy individuals-the distribution of statistically significant points of difference showed highly consistency for intergroups after repeated sampling processes. The classification accuracy between the COVID-19 cases and the suspected cases is 0.87 (95% confidence interval [CI]: 0.85-0.88), and the accuracy between the COVID-19 and the healthy controls is 0.90 (95% CI: 0.89-0.91), while the accuracy between the suspected cases and the healthy control group is 0.68 (95% CI: 0.67-0.73). For the independent test dataset, we apply the obtained SVM model to the classification of the independent test dataset to have all the results correctly classified. Our model showed that the serum-level classification results were all correct for independent test dataset. Our results suggest that Raman spectroscopy could be a safe and efficient technique for COVID-19 screening.

Corticosteroid, oseltamivir and delayed admission are independent risk factors for prolonged viral shedding in patients with Coronavirus Disease 2019.

INTRODUCTION: Coronavirus Disease 2019 (COVID-19) has spread worldwide, and it has reached to more than 14.5 million cases. Although Hubei province is the epicenter of China, little is known about epidemiological and clinical features of COVID-19 in other areas in Hubei province around Wuhan. In addition, the virological data, particularly the factors associated with viral shedding of COVID-19 has not been well described. OBJECTIVE: To describe the epidemiological and clinical features of patients with COVID-19 in Tianmen city, and identify risk factors associated with prolonged viral shedding of COVID-19. METHODS: Inpatients with COVID-19 admitted before February 9, 2020 were included. Characteristics were compared between patients with early and late viral RNA shedding. Multivariate cox regression model was used to investigate variables associated with prolonged viral shedding. RESULTS: One hundred and eighty-three patients were included. About 8.2% patients were categorized as critical degree of severity. All patients received antiviral therapy, with arbidol and interferon being the commonest. About 38.3% and 16.9% patients were treated with corticosteroid and immunoglobulin, respectively. Time from onset to admission (HR = 0.829, P < 0.001), and administration of corticosteroid (HR = 0.496, P = 0.002), arbidol (HR = 2.605, P = 0.008) and oseltamivir (HR = 0.416, P < 0.001) were independently associated with duration of viral shedding. CONCLUSION: Symptoms of patients from Tianmen are relatively mild. Treatment should be started as early as possible, but corticosteroid and oseltamivir should be initiated with caution. In addition, clinical trials on arbidol should be conducted to demonstrate its effectiveness.