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The factors affecting the antibody responses to the ZF2001 vaccine remain unknown. To address this, we conducted a cross-sectional serological study in the real world. Adults with no prior SARS-CoV-2 infection history and received three doses of ZF2001 vaccine were invited to our study in the early stages of the COVID-19 epidemic in Chongqing between 7 April 2021 and 17 November 2021. A questionnaire survey was conducted to obtain demographic characteristics, health information, and the frequency of lifestyles at the time of enrollment. A total of 266 eligible subjects aged 18 to 86 years, with a median age of 56.00 (IQR: 34-66) participated. 68.80% of them were female. Hypertension (13.16%) and diabetes (6.02%) were common comorbidities. Serum samples were collected at one month after the third dose of ZF2001 vaccination, and serological testing was conducted using the Pseudovirus-Based Neutralization Assay. The chi-square test was employed to compare seropositivity rates, and the Mann-Whitney U test or the Kruskal-Wallis test was used to analyze the neutralizing antibodies level in stratified groups. Subsequently, univariate and multivariate linear regression analyses were conducted to identify the influencing factors. We observed that seropositivity rates was 76.32%, with 95% confidence interval (95%CI) 70.85%-81.03%, and geometric mean titer (GMT) was 120.26, with 95%CI 100.38-144.08. Age, diabetes, and frequently of alcohol were negative associations with antibody response ( β = -0.2021, 95% CI: -0.2507 to -0.1535, β = -0.2873, 95% CI: -0.5590 to -0.0155, β = -0.2082, 95% CI: -0.3419 to-0.0746, P < 0.0001, P  = 0.0384, P  = 0.0024). Conversely, the -interval between 1 and 2 dose and frequently of tea were positive associations with antibody response ( β  = 0.1369, 95% CI: 0.0463 to 0.2275, β  = 0.0830, 95% CI: 0.0106 to 0.1554, P  = 0.0032, P  = 0.0247). Overall, the ZF2001 vaccine-induced antibody response was influenced by a multifactor that may provide a reference for the development of personalized antigen vaccines and vaccination strategies in the future.

Background: School closures and home confinement due to the ongoing COVID-19 pandemic may lead to disrupted sleep patterns. Consequently, it could increase the risk of children and adolescents' mental health disorders., Methods: In this prospective study, we randomly selected ten schools in Shanghai and conducted cluster sampling of students from each school. The first wave of the survey was conducted between January 3 and 21, 2020. Approximately two months after the COVID-19 outbreak declared, a second wave of the survey was conducted. In total, 2427 individuals were surveyed in both waves using the same sampling method. Participants' mental health status (depression, anxiety and stress), sleep patterns and other demographic information were measured in both waves. Multivariate regression analysis was used to examine the associations between sleep patterns and mental health status., Results: During the COVID-19 pandemic, a total of 873 participants (19.9%), 1100 participants (25.1%), and 670 participants (15.3%) reported depression, anxiety, and stress symptoms, respectively. Significant changes of both sleep duration and sleep-wake cycle patterns were observed before and during the COVID-19 pandemic. Moreover, shorter sleep duration and late to rise patterns (including early to bed late to rise and late to bed late to rise) were found to be associated with higher odds of having mental illnesses during the pandemic., Conclusion: These results suggest there is a pressing need to monitor children's and adolescents' health behavior and mental health and develop timely evidence-based strategies and interventions to mitigate adverse behavioral and psychological impacts caused by these unprecedented challenges., (Copyright © 2021. Published by Elsevier B.V.)

Data regarding the epidemiologic characteristics and clinical features of pediatric hematologic patients are limited in this corona virus disease 2019 (COVID-19) crisis. We investigated the status of 113 pediatric hematologic patients in Wuhan union hospital during the COVID-19 pandemic from January 23 to March 10, 2020. All the patients had routine blood and biochemical examination, as well as chest computed tomography scans, and the nucleic acid, immunoglobulin G-immunoglobulin M combined antibodies tests for SARS-CoV-2. After admission, all patients were single-room isolated for 5 to 7 days. The results showed that only 1 (0.88%) child with leukemia was confirmed to have SARS-CoV-2 infection and 15 (13.2%) children were considered as suspected cases. Comparing to the nonsuspected patients, the suspected cases had lower white blood cell count, hemoglobin level, neutrophil count, serum calcium ion level and serum albumin concentration, as well as higher levels of C-reactive protein. All the suspected cases were ruled out of SARS-CoV-2 infection by twice negative tests for the virus. Therefore, the incidence of SARS-CoV-2 infection in hematologic malignancy children was low during the COVID-19 pandemic in China. COVID-19 got early detected and the virus spread out in the ward was effectively blocked by increasing test frequency and using single-room isolation for 5 to 7 days after admission., Competing Interests: The authors declare no conflict of interest., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

In the early 2000s, emerging SARS-CoV-2, which is highly pathogenic, posed a great threat to public health. During COVID-19, epigenetic regulation is deemed to be an important part of the pathophysiology and illness severity. Using the Illumina Infinium Methylation EPIC BeadChip (850 K), we investigated genome-wide differences in DNA methylation between healthy subjects and COVID-19 patients with different disease severities. We conducted a combined analysis and selected 35 "marker" genes that could indicate a SARS-CoV-2 infection, including 12 (ATHL1, CHN2, CHST15, CPLX2, CRHR2, DCAKD, GNAI2, HECW1, HYAL1, MIR510, PDE11A, and SMG6) situated in the promoter region. The functions and pathways of differentially methylated genes were enriched in biological processes, signal transduction, and the immune system. In the "Severe versus Mild" group, differentially methylated genes, after eliminating duplicates, were used for PPI analyses. The four hub genes (GNG7, GNAS, PRKCZ, and PRKAG2) that had the highest degree of nodes were identified and among them, GNG7 and GNAS genes expressions were also downregulated in the severe group in sequencing results. Above all, the results suggest that GNG7 and GNAS may play a non-ignorable role in the progression of COVID-19. In conclusion, the identified key genes and related pathways in the current study can be used to study the molecular mechanisms of COVID-19 and may provide possibilities for specific treatments., (© 2021 John Wiley & Sons Ltd/University College London.)

Despite the large reduction in anthropogenic activities due to the outbreak of COVID-19, air quality in China has witnessed little improvement and featured great regional disparities. Here, by combining observational data and simulations, this work aims to understand the diverse air quality response in two city clusters, Yangtze River Delta region (YRD) and Pearl River Delta region (PRD), China. Though there was a noticeable drop in primary pollutants in both the regions, differently, the maximum daily 8 h average ozone (O 3 ) soared by 20.6-76.8% in YRD but decreased by 15.5-28.1% in PRD. In YRD, nitrogen oxide (NOx) reductions enhanced O 3 accumulation and hence increased secondary aerosol formation. Such an increment in secondary organic and inorganic aerosols under stationary weather reached up to 36.4 and 10.2%, respectively, which was further intensified by regional transport. PRD was quite the opposite. The emission reductions benefited PRD air quality, while regional transport corresponded to an increase of 17.3 and 9.3% in secondary organic and inorganic aerosols, respectively. Apart from meteorology, the discrepancy in O 3 -VOCs-NOx relationships determined the different O 3 responses, indicating that future emission control shall be regionally specific, instead of one-size-fits-all cut. Overall, the importance of regionally coordinated and balanced control strategy for multiple pollutants is highly emphasized.

Background: Almost a year after the outbreak of coronavirus disease 2019 (COVID-19), many hospitalized COVID-19 patients have recovered. However, little is known about the long-term follow-up (> 2 months) of discharged patients., Methods: This study enrolled 527 discharged COVID-19 patients from 05 February to 11 March 2020. Basic characteristics, imaging features, nucleic acid detection results, and antibody levels of these patients were retrospectively reviewed., Results: Of the 527 discharged patients, 32 (6.1%) had re-detectable positive (RP) nucleic acid results for SARS-CoV-2 during follow-up examinations, with 11 and four detections entailing stool samples and anal swabs, respectively, rather than respiratory samples. Juveniles were more susceptible to "infection recurrence" than other age groups, with shorter time spans for re-detectable positive (RP) RNA tests (an average of 8.8 days [6.0-9.0 days]), while the reverse was true for the middle-aged group (17.5 days on average [14.0-17.5 days]). Similar improvements in the imaging features of both RP and no RP (NRP) groups were observed. Negative antibody detections in patients at 3 and 6 months after discharge were 14.2% and 25.0%, respectively. Cases evidencing negative antibodies were more common among juvenile patients (40% vs. 15.6%, P=0.03) 6 months post-discharge., Conclusions: A total of 6.1% of 527 discharged patients showed RP status, which may be easier to be identified from stool samples than from other samples. Given the dropping rate of SARS-CoV-2 antibodies, reinfection may happen, especially in juvenile patients (aged<18 years). These findings have implications for the long-term management of recovered COVID-19 patients., (Copyright © 2021 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

The COVID-19 crisis is affecting our sense of self and touches upon our existential fears. This extends to the self-other relationship, as there is both being infected and infecting the other. What does this pandemic crisis tell us about our self and relatedness, its cultural differences, and how these are rooted in the brain's relation to the world? First, we discuss the psychological and neuronal features of self and self-other relation and how they are rooted in a deeper layer of the brain's neural activity complementing its cognitive surface layer. Second, we demonstrate cultural differences of Eastern and Western concepts of the self (i.e., independency and interdependency) and how these reflect the manifestation of the brain's neuro-social and neuro-ecological alignment. Finally, we highlight the intersubjective and cultural nature of the self and its surface in the COVID-19 crisis. Discussing various lines of empirical data showing the brain's intimate alignment to both social and ecological environmental contexts, our results support the assumption of the brain's deep layer features by laying bare a continuum of different degrees of neuro-social and neuro-ecological alignment. This entails a two-stage model of self with neuro-social-ecological and psychological levels that extends the previously suggested basis model of self-specificity. We conclude that the current pandemic shows the importance of the deeper intersubjective and cultural layers of both the self and brain; their neglect can be life-threatening for the self and others and, paradoxically, might reduce, rather than enlarge, the self's sense of freedom and independence., (© 2020 The Authors Psychiatry and Clinical Neurosciences © 2020 Japanese Society of Psychiatry and Neurology.)

Background: The outbreak of COVID 19 in December 2019 spread quickly and overwhelmed the local healthcare system of the epicenter. A total of 346 medical assistance teams with 42,600 reserve medics were mobilized from around the country for emergency assistance. This study aims to examine the incidence of mental health symptoms and predictors of Post-Traumatic Stress Disorders (PTSD) symptoms among the reserve medics working in Wuhan, the capital city of Hubei Province., Methods: An anonymous survey was conducted from April 4-6, 2020 among the medics upon their returning home. A total of 225 surveys were returned with a response rate of 83%. The survey consisted of questionnaires about the medics' demographic information, social relations, mental health status (e.g. IES-R and DASS-21) and other work-related information. Mann-Whitney U Test, Kruskal-Wallis Test and hierarchical logistic regression models were used to examine the predictors of PTSD symptoms., Results: During the stay in Wuhan, the medics experienced high levels of depression (46.7%), anxiety (35.6%) and stress symptoms (16.0%). Upon returning home, the overall prevalence of clinically concerned PTSD symptoms was as high as 31.6%. Further analyses revealed that PTSD symptoms and its subscales were significantly associated with age, collegial relationship and mental health status during their service., Conclusion: The reserve medics reported a high prevalence of depression, anxiety and stress as well as clinically concerned PTSD symptoms. Comprehensive screening and intervention programs should be in place to help reserve medics cope with mental health challenges and build resilience during the COVID 19 pandemic., (Copyright © 2020. Published by Elsevier Inc.)

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel pathogen, has caused an outbreak of coronavirus disease 2019 (COVID-19) that has spread rapidly around the world. Determining the risk factors for death and the differences in clinical features between severely ill and critically ill patients with SARS-CoV-2 pneumonia has become increasingly important.Aim: This study was intended to provide insight into the difference between severely ill and critically ill patients with SARS-CoV-2 pneumonia.Methods: In this retrospective, multicenter cohort study, we enrolled 62 seriously ill patients with SARS-CoV-2 pneumonia who had been diagnosed by March 12, 2020. Clinical data, laboratory indexes, chest images, and treatment strategies collected from routine medical records were compared between severely ill and critically ill patients. Univariate and multivariate logistic regression analyses were also conducted to identify the risk factors associated with the progression of patients with severe COVID-19.Results: Of the 62 patients with severe or critical illness, including 7 who died, 30 (48%) patients had underlying diseases, of which the most common was cardiovascular disease (hypertension, 34%, and coronary heart disease, 5%). Compared to patients with severe disease, those with critical disease had distinctly higher white blood cell counts, procalcitonin levels, and D-dimer levels, and lower hemoglobin levels and lymphocyte counts. Multivariate regression showed that a lymphocyte count less than 109/L (odds ratio 20.92, 95% CI 1.76-248.18; p=0.02) at admission increased the risk of developing a critical illness.Conclusion: Based on multivariate regression analysis, a lower lymphocyte count (<109/L) on admission is the most critical independent factor that is closely associated with an increased risk of progression to critical illness. Age, underlying diseases, especially hypertension and coronary heart disease, elevated D-dimer, decreased hemoglobin, and SOFA score, and APACH score also need to be taken into account for predicting disease progression. Blood cell counts and procalcitonin levels for the later secondary bacterial infection have a certain reference values. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has highlighted the necessity of advanced modeling inference using the limited data of daily cases. Tracking a long-term epidemic trajectory requires explanatory modeling with more complexities than the one with short-time forecasts, especially for the highly vaccinated scenario in the latest phase. With this work, we propose a novel modeling framework that combines an epidemiological model with Bayesian inference to perform an explanatory analysis on the spreading of COVID-19 in Israel. The Bayesian inference is implemented on a modified SEIR compartmental model supplemented by real-time vaccination data and piecewise transmission and infectious rates determined by change points. We illustrate the fitted multi-wave trajectory in Israel with the checkpoints of major changes in publicly announced interventions or critical social events. The result of our modeling framework partly reflects the impact of different stages of mitigation strategies as well as the vaccination effectiveness, and provides forecasts of near future scenarios. [ABSTRACT FROM AUTHOR]

• Middle-aged adults with no underlying diseases can suffer from severe COVID-19. • Lung biopsies have rarely been reported in patients with serious COVID-19. • In this study, pathological and inflammatory features were investigated in a patient with severe COVID-19. We report the case of a patient diagnosed with severe pneumonia due to coronavirus disease 2019 (COVID-19). A percutaneous lung biopsy was performed under ultrasound guidance. Morphological and ultrastructural characteristics of the patient's lungs are presented, along with details of some important changes in inflammatory biological markers, in order to help better understand the disease and provide clues to allow members of the multidisciplinary team to save more people. [ABSTRACT FROM AUTHOR]