Synergistic effect of elevated glucose levels with SARS-CoV-2 spike protein induced NOX-dependent ROS production in endothelial cells.

BACKGROUND: Diabetic patients infected with coronavirus disease 2019 (COVID-19) often have a higher probability of organ failure and mortality. The potential cellular mechanisms through which blood glucose exacerbates tissue damage due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is still unclear. METHODS AND RESULTS: We cultured endothelial cells within differing glucose mediums with an increasing concentration gradient of SARS-CoV-2 Spike protein (S protein). S protein can cause the reduction of ACE2 and TMPRSS2, and activation of NOX2 and NOX4. A high glucose medium was shown to aggravate the decrease of ACE2 and activation of NOX2 and NOX4 in cultured cells, but had no effect on TMPRSS2. S protein mediated activation of the ACE2-NOX axis induced oxidative stress and apoptosis within endothelial cells, leading to cellular dysfunction via the reduction of NO and tight junction proteins which may collectively be exacerbated by elevated glucose. In addition, the glucose variability model demonstrated activation of the ACE2-NOX axis in a similar manner observed in the high glucose model in vitro. CONCLUSIONS: Our present study provides evidence for a mechanism through which hyperglycemia aggravates endothelial cell injury resulting from S protein mediated activation of the ACE2-NOX axis. Our research thus highlights the importance of strict monitoring and control of blood glucose levels within the context of COVID-19 treatment to potentially improve clinical outcomes.

Depression and anxiety among Macau residents during the COVID-19 outbreak: A network analysis perspective.

Background: The 2019 novel coronavirus disease (COVID-19) outbreak affected people's lifestyles and increased their risk for depressive and anxiety symptoms (depression and anxiety, respectively hereafter). We assessed depression and anxiety in residents of Macau during "the 6.18 COVID-19 outbreak" period and explored inter-connections of different symptoms from the perspective of network analysis. Methods: In this cross-sectional study, 1,008 Macau residents completed an online survey comprising the nine-item Patient Health Questionnaire (PHQ-9) and seven-item Generalized Anxiety Disorder Scale (GAD-7) to measure depression and anxiety, respectively. Central and bridge symptoms of the depression-anxiety network model were evaluated based on Expected Influence (EI) statistics, while a bootstrap procedure was used to test the stability and accuracy of the network model. Results: Descriptive analyses indicated the prevalence of depression was 62.5% [95% confidence interval (CI) = 59.47-65.44%], the prevalence of anxiety was 50.2% [95%CI = 47.12-53.28%], and 45.1% [95%CI = 42.09-48.22%] of participants experienced comorbid depression and anxiety. "Nervousness-Uncontrollable worry" (GADC) (EI = 1.15), "Irritability" (GAD6) (EI = 1.03), and "Excessive worry" (GAD3) (EI = 1.02) were the most central symptoms, while "Irritability" (GAD6) (bridge EI = 0.43), "restlessness" (GAD5) (bridge EI = 0.35), and "Sad Mood" (PHQ2) (bridge EI = 0.30) were key bridge symptoms that emerged in the network model. Conclusion: Nearly half of residents in Macau experienced comorbid depression and anxiety during the 6.18 COVID-19 outbreak. Central and bridge symptoms identified in this network analysis are plausible, specific targets for treatment and prevention of comorbid depression and anxiety related to this outbreak.

The Association between Perceived Teacher Support, Students' ICT Self-Efficacy, and Online English Academic Engagement in the Blended Learning Context

The present study intended to examine the relationship between perceived teacher support, students' ICT self-efficacy, and online English academic engagement in the blended learning setting, especially in mobile-assisted foreign language instruction contexts. A sample of 960 Chinese undergraduate and postgraduate students was recruited to participate in the online questionnaire. SPSS version 24.0 was used for descriptive, correlation, independent samples t-test, and mediation analysis of the three variables. The results showed that: (1) there is a significant correlation between perceived teacher support, students' ICT self-efficacy, and online English academic engagement;(2) students' ICT self-efficacy partially mediates the relationship between perceived teacher support and student online English academic engagement;(3) students' ICT self-efficacies differed by sex and level of education, but not by major;(4) students' sense of self-competence in ICT self-efficacy has a significant positive influence on engagement with online English learning. The findings reveal that students' ICT self-efficacy positively impacts students' online English learning, and perceived teacher support also affects students' learning engagement. School administrators should encourage teachers to focus on students' online self-efficacy, especially the sense of environmental control. Implications and further directions for future research are presented at the end.

Spatio-temporal heterogeneity in the international trade resilience during COVID-19

The COVID-19 pandemic and subsequent lockdowns have created immeasurable health and economic crises, leading to unprecedented disruptions to world trade. The COVID-19 pandemic shows diverse impacts on different economies that suffer and recover at different rates and degrees. This research aims to evaluate the spatio-temporal heterogeneity of international trade network vulnerabilities in the current crisis to understand the global production resilience and prepare for the future crisis. We applied a series of complex network analysis approaches to the monthly international trade networks at the world, regional, and country scales for the pre- and post- COVID-19 outbreak period. The spatio-temporal patterns indicate that countries and regions with an effective COVID-19 containment such as East Asia show the strongest resilience, especially Mainland China, followed by high-income countries with fast vaccine roll-out (e.g., U.S.), whereas low-income countries (e.g., Africa) show high vulnerability. Our results encourage a comprehensive strategy to enhance international trade resilience when facing future pandemic threats including effective non-pharmaceutical measures, timely development and rollout of vaccines, strong governance capacity, robust healthcare systems, and equality via international cooperation. The overall findings elicit the hidden global trading disruption, recovery, and growth due to the adverse impact of the COVID-19 pandemic.

Positive Matrix Factorization as Source Apportionment of Paddy Soil Heavy Metals in Black Shale Areas in Western Zhejiang Province, China

The source apportionment of pollutants is the key to preventing and controlling the pollution caused by heavy metals in soils. The aim of this study was to investigate the main sources of heavy metals in the soils of black shale areas in western Zhejiang, China. Based on geostatistical spatial analysis, this research employed positive matrix factorization (PMF) for the source apportionment of heavy metals in paddy soil. The results showed that contaminated arable soils were concentrated in the western and southern study areas. At least five major sources of heavy metals were screened in this study: natural sources (39.66%), traffic emissions (32.85%), industrial emissions (9.23%), agricultural activities (9.17%), and mining (9.10%). To be specific, Cd was mainly from mining;As originated from agricultural inputs such as fertilizers and pesticides;and Hg, as an industrial pollutant, was transported by atmospheric deposition in the study area. The accumulation of Pb, Zn, and Cu was mainly influenced by natural sources and anthropogenic sources, i.e., traffic emissions, while that of Cr and Ni was controlled by natural sources.

Psychosocial crisis intervention for coronavirus disease 2019 patients and healthcare workers. / æ–°åž‹å† çŠ¶ç— æ¯’è‚ºç‚Žæ‚£è€ å’ŒåŒ»åŠ¡äººå‘˜çš„å¿ƒç†ç¤¾ä¼šå±æœºå¹²é¢„ï¼ˆè‹±æ–‡ï¼‰.

OBJECTIVES: Shelter hospital was an alternative way to provide large-scale medical isolation and treatment for people with mild coronavirus disease 2019 (COVID-19). Due to various reasons, patients admitted to the large shelter hospital was reported high level of psychological distress, so did the healthcare workers. This study aims to introduce a comprehensive and multifaceted psychosocial crisis intervention model. METHODS: The psychosocial crisis intervention model was provided to 200 patients and 240 healthcare workers in Wuhan Wuchang shelter hospital. Patient volunteers and organized peer support, client-centered culturally sensitive supportive care, timely delivery of scientific information about COVID-19 and its complications, mental health knowledge acquisition of non-psychiatric healthcare workers, group activities, counseling and education, virtualization of psychological intervention, consultation and liaison were exhibited respectively in the model. Pre-service survey was done in 38 patients and 49 healthcare workers using the Generalized Anxiety Disorder 7-item (GAD-7) scale, the Patient Health Questionnaire 2-item (PHQ-2) scale, and the Primary Care PTSD screen for the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (PC-PTSD-5). Forty-eight healthcare workers gave feedback after the intervention. RESULTS: The psychosocial crisis intervention model was successfully implemented by 10 mental health professionals and was well-accepted by both patients and healthcare workers in the shelter hospital. In pre-service survey, 15.8% of 38 patients were with anxiety, 55.3% were with stress, and 15.8% were with depression; 16.3% of 49 healthcare workers were with anxiety, 26.5% were with stress, and 22.4% were with depression. In post-service survey, 62.5% of 48 healthcare workers thought it was very practical, 37.5% thought more practical; 37.5% of them thought it was very helpful to relief anxiety and insomnia, and 27.1% thought much helpful; 37.5% of them thought it was very helpful to recognize patients with anxiety and insomnia, and 29.2% thought much helpful; 35.4% of them thought it was very helpful to deal with patients' anxiety and insomnia, and 37.5% thought much helpful. CONCLUSIONS: Psychological crisis intervention is feasible, acceptable, and associated with positive outcomes. Future tastings of this model in larger population and different settings are warranted.

Spatio-temporal heterogeneity in the international trade resilience during COVID-19.

The COVID-19 pandemic and subsequent lockdowns have created immeasurable health and economic crises, leading to unprecedented disruptions to world trade. The COVID-19 pandemic shows diverse impacts on different economies that suffer and recover at different rates and degrees. This research aims to evaluate the spatio-temporal heterogeneity of international trade network vulnerabilities in the current crisis to understand the global production resilience and prepare for the future crisis. We applied a series of complex network analysis approaches to the monthly international trade networks at the world, regional, and country scales for the pre- and post- COVID-19 outbreak period. The spatio-temporal patterns indicate that countries and regions with an effective COVID-19 containment such as East Asia show the strongest resilience, especially Mainland China, followed by high-income countries with fast vaccine roll-out (e.g., U.S.), whereas low-income countries (e.g., Africa) show high vulnerability. Our results encourage a comprehensive strategy to enhance international trade resilience when facing future pandemic threats including effective non-pharmaceutical measures, timely development and rollout of vaccines, strong governance capacity, robust healthcare systems, and equality via international cooperation. The overall findings elicit the hidden global trading disruption, recovery, and growth due to the adverse impact of the COVID-19 pandemic.

Prevalence and factors associated with anxiety and depression among community-dwelling older adults in Hunan, China: a cross-sectional study.

BACKGROUND: Older adults' psychological health is a public health issue that cannot be ignored, especially when these psychological health problems and related factors change across different social backgrounds because of rapid changes in traditions and family structures and the epidemic responses after the outbreak of COVID-19 in China. The aim of our study is to determine the prevalence of anxiety and depression and their associated factors among community-dwelling older adults in China. METHODS: A cross-sectional study was conducted from March to May 2021 with 1173 participants aged 65 years or above from three communities in Hunan Province, China who were selected using convenience sampling. A structured questionnaire including sociodemographic characteristics, clinical characteristics, the Social Support Rating Scale (SSRS), the 7-Item Generalized Anxiety Disorder scale (GAD-7), and the Patient Health Questionnaire-9 Item (PHQ-9) was used to collect relevant demographic and clinical data and to measure social support status, anxiety symptoms, and depressive symptoms, respectively. Bivariate analyses were conducted to explore the difference in anxiety and depression based on samples' different characteristics. The multivariable logistic regression analysis was performed to test for significant predictors of anxiety and depression. RESULTS: The prevalence of anxiety and depression were 32.74% and 37.34%, respectively. Multivariable logistic regression analysis revealed that being female, being unemployed before retirement age, lacking physical activity, having physical pain, and having three or more comorbidities were significant predictors for anxiety. Subjective social support and support utilization were significant protective factors. Regarding depression, religion, lacking physical activity, having physical pain, having three or more comorbidities were found to be significant predictors. Support utilization was a significant protective factor. CONCLUSIONS: The study group showed a high prevalence of anxiety and depression. Gender, employment status, physical activity, physical pain, comorbidities, and social support were associated with psychological health problems of older adults. These findings suggest that governments should focus on the psychological health problems of older adults by raising community awareness of issues related to older adults' psychological health. They should also screen for anxiety and depression among high-risk groups and encourage individuals to seek supportive counseling.

Antidepressants for COVID-19: A systematic review.

OBJECTIVE: To systematically examine the efficacy and safety of antidepressants for the treatment of coronavirus disease 2019 (COVID-19). METHODS: A systematic search was performed independently by two researchers based on Chinese Journal Net, WanFang, PsycINFO, Cochrane Library, PubMed, and EMBASE. RESULTS: Seven studies (n = 92,947) including three retrospective studies (n = 91,083), two randomized clinical trials (RCTs, n = 1649), two prospective cohort study (n = 215) involving (n = 92,947) patients with COVID-19 were examined. For RCTs, fluvoxamine outperformed placebo in reducing clinical deterioration and hospitalisation for COVID-19 patients. For retrospective studies, antidepressants (2 studies) and fluoxetine (1 study) possibly reduced the risk of mortality in patients with COVID-19. Results from two remaining studies supported the superiority of fluvoxamine in reducing risk of mortality in COVID-19 patients. The two RCTs that examined the safety of fluvoxamine for COVID-19 patients found inconsistent results but no significant group differences in the dropout rate. CONCLUSION: This systematic review found emerging evidence for fluvoxamine in reducing the risk of mortality and hospitalisation in COVID-19 patients, but inconsistent evidence for the safety of fluvoxamine in COVID-19 patients. More studies are needed to determine the efficacy and safety of antidepressants for the treatment of COVID-19.

Identification of Parameters Representative of Immune Dysfunction in Patients with Severe and Fatal COVID-19 Infection: a Systematic Review and Meta-analysis.

Abnormal immunological indicators associated with disease severity and mortality in patients with COVID-19 have been reported in several observational studies. However, there are marked heterogeneities in patient characteristics and research methodologies in these studies. We aimed to provide an updated synthesis of the association between immune-related indicators and COVID-19 prognosis. We conducted an electronic search of PubMed, Scopus, Ovid, Willey, Web of Science, Cochrane library, and CNKI for studies reporting immunological and/or immune-related parameters, including hematological, inflammatory, coagulation, and biochemical variables, tested on hospital admission of COVID-19 patients with different severities and outcomes. A total of 145 studies were included in the current meta-analysis, with 26 immunological, 11 hematological, 5 inflammatory, 4 coagulation, and 10 biochemical variables reported. Of them, levels of cytokines, including IL-1ß, IL-1Ra, IL-2R, IL-4, IL-6, IL-8, IL-10, IL-18, TNF-α, IFN-γ, IgA, IgG, and CD4+ T/CD8+ T cell ratio, WBC, neutrophil, platelet, ESR, CRP, ferritin, SAA, D-dimer, FIB, and LDH were significantly increased in severely ill patients or non-survivors. Moreover, non-severely ill patients or survivors presented significantly higher counts of lymphocytes, monocytes, lymphocyte/monocyte ratio, eosinophils, CD3+ T,CD4+T and CD8+T cells, B cells, and NK cells. The currently updated meta-analysis primarily identified a hypercytokinemia profile with the severity and mortality of COVID-19 containing IL-1ß, IL-1Ra, IL-2R, IL-4, IL-6, IL-8, IL-10, IL-18, TNF-α, and IFN-γ. Impaired innate and adaptive immune responses, reflected by decreased eosinophils, lymphocytes, monocytes, B cells, NK cells, T cells, and their subtype CD4+ and CD8+ T cells, and augmented inflammation, coagulation dysfunction, and nonpulmonary organ injury, were marked features of patients with poor prognosis. Therefore, parameters of immune response dysfunction combined with inflammatory, coagulated, or nonpulmonary organ injury indicators may be more sensitive to predict severe patients and those non-survivors.

Effects of Dust Event Days on Influenza: Evidence from Arid Environments in Lanzhou

Airborne aerosol is believed to be an important pathway for infectious disease transmissions like COVID-19 and influenza. However, the effects of dust event days on influenza have been rarely explored, particularly in arid environments. This study explores the effects of ambient particulate matter (PM) and dust events on laboratory-confirmed influenza in a semi-arid city. A descriptive analysis of daily laboratory-confirmed influenza (influenza) cases, PM (PM10 and PM2.5), meteorological parameters, and dust events were conducted from 2014 to 2019 in Lanzhou, China. The case-crossover design combined with conditional Poisson regression models was used to estimate the lagging effects of PM and dust events on influenza. In addition, a hierarchical model was used to quantitatively evaluate the interactive effect of PM with ambient temperature and absolute humidity on influenza. We found that PM and dust events had a significant effect on influenza. The effects of PM10 and PM2.5 on influenza became stronger as the cumulative lag days increased. The greatest estimated relative risks (RRs) were 1.018 (1.011,1.024) and 1.061 (1.034,1.087), respectively. Compared with the non-dust days, the effects of dust events with duration ≥ 1 day and with duration ≥ 2 days on influenza were the strongest at lag0 day, with the estimated RRs of 1.245 (95% CI: 1.061–1.463) and 1.483 (95% CI: 1.232–1.784), respectively. Subgroup analysis showed that pre-school children and school-aged children were more sensitive to PM and dust events exposure. Besides, we also found that low humidity and temperature had an interaction with PM to aggravate the risk of influenza. In summary, ambient PM and dust events exposure may increase the risk of influenza, and the risk of influenza increases with the dust events duration. Therefore, more efforts from the government as well as individuals should be strengthened to reduce the effect of PM on influenza, particularly in cold and dry weather.

A network analysis of anxiety and depression symptoms among Chinese nurses in the late stage of the COVID-19 pandemic.

Background: Nurses are at high risk for depression and anxiety symptoms after the outbreak of the COVID-19 pandemic. We aimed to assess the network structure of anxiety and depression symptoms among Chinese nurses in the late stage of this pandemic. Method: A total of 6,183 nurses were recruited across China from Oct 2020 to Apr 2021 through snowball sampling. We used Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder scale-7 (GAD-7) to assess depression and anxiety, respectively. We used the Ising model to estimate the network. The index "expected influence" and "bridge expected influence" were applied to determine the central symptoms and bridge symptoms of the anxiety-depression network. We tested the stability and accuracy of the network via the case-dropping procedure and non-parametric bootstrapping procedure. Result: The network had excellent stability and accuracy. Central symptoms included "restlessness", "trouble relaxing", "sad mood", and "uncontrollable worry". "Restlessness", "nervous", and "suicidal thoughts" served as bridge symptoms. Conclusion: Restlessness emerged as the strongest central and bridge symptom in the anxiety-depression network of nurses. Intervention on depression and anxiety symptoms in nurses should prioritize this symptom.

The prevalence and risk factors of mental problems in medical students during COVID-19 pandemic: A systematic review and meta-analysis.

BACKGROUND: This meta-analysis and systematic review aimed to evaluate the global prevalence and risk factors of mental problems (i.e., depression, anxiety, stress, sleep disorder, posttraumatic stress disorder (PTSD), burnout, psychological distress, and suicidal ideation) among medical students during the COVID-19 pandemic. METHOD: We searched PubMed, Embase, Web of Science, psycARTICLES, PsycINFO, CNKI, and Wan Fang for studies on the prevalence of mental problems among medical students from January 1, 2020, to April 1, 2022. The pooled prevalence was calculated by random-effect models. We performed a narrative review to identify the risk factors. RESULTS: The meta-analysis included 201 studies (N = 198,000). The prevalence of depression (41 %, 95 % CI, 37-45 %,), anxiety (38 %,95 % CI, 34 %-42 %), stress (34 %, 95 % CI, 27 %-42 %), sleep disorder (52 %, 95 % CI, 44 %-60 %), psychological distress (58 %, 95 % CI, 51 %-65 %), PTSD (34 %, 95 % CI, 22 %-46 %), suicidal ideation (15 %, 95 % CI, 11 %-18 %) and burnout (38 %, 95 % CI, 25 %-50 %) was high. The major risk factors were being female, being junior or preclinical students, exposure to COVID-19, academic stress, psychiatric or physical disorders history, economic trouble, fear of education impairment, online learning trouble, fear of infection, loneliness, low physical activity, low social support, problematic internet or smartphone use, and young age. LIMITATIONS: Most studies were cross-sectional. Few studies provided a reasonable response rate, suggesting potential selection bias. CONCLUSIONS: The study demonstrated a high prevalence and risk factors for mental problems during COVID-19, calling for mental health services. Our findings are valuable for college and health authorities to identify high-risk students and provide targeted intervention.

Efficacy, immunogenicity and safety of COVID-19 vaccines in older adults: a systematic review and meta-analysis.

Background: Older adults are more susceptible to severe health outcomes for coronavirus disease 2019 (COVID-19). Universal vaccination has become a trend, but there are still doubts and research gaps regarding the COVID-19 vaccination in the elderly. This study aimed to investigate the efficacy, immunogenicity, and safety of COVID-19 vaccines in older people aged ≥ 55 years and their influencing factors. Methods: Randomized controlled trials from inception to April 9, 2022, were systematically searched in PubMed, EMBASE, the Cochrane Library, and Web of Science. We estimated summary relative risk (RR), rates, or standardized mean difference (SMD) with 95% confidence interval (CI) using random-effects meta-analysis. This study was registered with PROSPERO (CRD42022314456). Results: Of the 32 eligible studies, 9, 21, and 25 were analyzed for efficacy, immunogenicity, and safety, respectively. In older adults, vaccination was efficacious against COVID-19 (79.49%, 95% CI: 60.55-89.34), with excellent seroconversion rate (92.64%, 95% CI: 86.77-96.91) and geometric mean titer (GMT) (SMD 3.56, 95% CI: 2.80-4.31) of neutralizing antibodies, and provided a significant protection rate against severe disease (87.01%, 50.80-96.57). Subgroup and meta-regression analyses consistently found vaccine types and the number of doses to be primary influencing factors for efficacy and immunogenicity. Specifically, mRNA vaccines showed the best efficacy (90.72%, 95% CI: 86.82-93.46), consistent with its highest seroconversion rate (98.52%, 95% CI: 93.45-99.98) and GMT (SMD 6.20, 95% CI: 2.02-10.39). Compared to the control groups, vaccination significantly increased the incidence of total adverse events (AEs) (RR 1.59, 95% CI: 1.38-1.83), including most local and systemic AEs, such as pain, fever, chill, etc. For inactivated and DNA vaccines, the incidence of any AEs was similar between vaccination and control groups (p > 0.1), while mRNA vaccines had the highest risk of most AEs (RR range from 1.74 to 7.22). Conclusion: COVID-19 vaccines showed acceptable efficacy, immunogenicity and safety in older people, especially providing a high protection rate against severe disease. The mRNA vaccine was the most efficacious, but it is worth surveillance for some AEs it caused. Increased booster coverage in older adults is warranted, and additional studies are urgently required for longer follow-up periods and variant strains.

Efficacy, immunogenicity and safety of COVID-19 vaccines in older adults: a systematic review and meta-analysis

Background Older adults are more susceptible to severe health outcomes for coronavirus disease 2019 (COVID-19). Universal vaccination has become a trend, but there are still doubts and research gaps regarding the COVID-19 vaccination in the elderly. This study aimed to investigate the efficacy, immunogenicity, and safety of COVID-19 vaccines in older people aged ≥ 55 years and their influencing factors. Methods Randomized controlled trials from inception to April 9, 2022, were systematically searched in PubMed, EMBASE, the Cochrane Library, and Web of Science. We estimated summary relative risk (RR), rates, or standardized mean difference (SMD) with 95% confidence interval (CI) using random-effects meta-analysis. This study was registered with PROSPERO (CRD42022314456). Results Of the 32 eligible studies, 9, 21, and 25 were analyzed for efficacy, immunogenicity, and safety, respectively. In older adults, vaccination was efficacious against COVID-19 (79.49%, 95% CI: 60.55−89.34), with excellent seroconversion rate (92.64%, 95% CI: 86.77−96.91) and geometric mean titer (GMT) (SMD 3.56, 95% CI: 2.80−4.31) of neutralizing antibodies, and provided a significant protection rate against severe disease (87.01%, 50.80−96.57). Subgroup and meta-regression analyses consistently found vaccine types and the number of doses to be primary influencing factors for efficacy and immunogenicity. Specifically, mRNA vaccines showed the best efficacy (90.72%, 95% CI: 86.82−93.46), consistent with its highest seroconversion rate (98.52%, 95% CI: 93.45−99.98) and GMT (SMD 6.20, 95% CI: 2.02−10.39). Compared to the control groups, vaccination significantly increased the incidence of total adverse events (AEs) (RR 1.59, 95% CI: 1.38−1.83), including most local and systemic AEs, such as pain, fever, chill, etc. For inactivated and DNA vaccines, the incidence of any AEs was similar between vaccination and control groups (p > 0.1), while mRNA vaccines had the highest risk of most AEs (RR range from 1.74 to 7.22). Conclusion COVID-19 vaccines showed acceptable efficacy, immunogenicity and safety in older people, especially providing a high protection rate against severe disease. The mRNA vaccine was the most efficacious, but it is worth surveillance for some AEs it caused. Increased booster coverage in older adults is warranted, and additional studies are urgently required for longer follow-up periods and variant strains.

COVID-19 prevention and control strategies: learning from the Macau model.

Background: Macau is a densely populated international tourist city. Compared to most tensely populated countries/territories, the prevalence and mortality of COVID-19 in Macau are lower. The experiences in Macau could be helpful for other areas to combat the COVID-19 pandemic. This article introduced the endeavours and achievements of Macau in combatting the COVID-19 pandemic. Method: Both qualitative and quantitative analysis methods were used to explore the work, measures, and achievements of Macau in dealing with the COVID-19 pandemic. Results: The results revealed that Macau has provided undifferentiated mask purchase reservation services, COVID-19 vaccination services to all residents and non-residents in Macau along with delivering multilingual services, in Chinese, English and Portuguese, to different groups of the population. To facilitate the travels of people, business and trades between Macau and mainland China, the Macau government launched the Macau Health Code System, which uses the health status declaration, residence history declaration, contact history declaration of the declarant to match various relevant backend databases within the health authority and provide a risk-related colour code operations. The Macau Health Code System connects to the Chinese mainland's own propriety health code system seamlessly, whilst effectively protecting the privacy of the residents. Macau has also developed the COVID-19 Vaccination Appointment system, the Nucleic Acid Test Appointment system, the Port and Entry/Exit Quarantine system, the medical and other supporting systems. Conclusion: The efforts in Macau have achieved remarkable results in COVID-19 prevention and control, effectively safeguarding the lives and health of the people and manifesting the core principle of "serving the public". The measures used are sustainable and can serve as an important reference for other countries/regions.

Estimation of Broadleaf Tree Canopy Height of Wolong Nature Reserve Based on InSAR and Machine Learning Methods

Tree height is an important parameter for calculating forest carbon sink and assessing forest carbon cycle. In order to obtain forest tree height over a large area both efficiently and at a low cost, this study proposed an Interferometric Synthetic Aperture Radar (InSAR) combined with a machine learning method to estimate the tree canopy height. The forest height in the study area was obtained using Unmanned Aerial Vehicle (UAV) photogrammetry, which was considered to be the true canopy height. Two machine learning methods (Random Forest, Multi-layer perceptron) were used to establish the relationship between phase center height calculated by InSAR DEM differential interference method and coherent amplitude method with true canopy height. The topographic factor, backward scattering coefficient and coherence coefficient were introduced into the relationship model. It was found that the accuracy of tree height estimation using random forest and two InSAR methods can reach 0.95 and 0.94. The root-mean-square error was 1.76 m, 1.86 m, respectively. The accuracy of tree height estimation using multi-layer perceptron and two InSAR methods was 0.25 and 0.2. The root-mean-square error was 3.96 m and 4.13 m. The results indicated that the combination of InSAR and machine learning can estimate canopy height efficiently and at a low cost. Moreover, the integrated learning algorithm random forest demonstrated better stability and higher accuracy than the single learning algorithm multi-layer perceptron.

Resting-state functional connectome predicts individual differences in depression during COVID-19 pandemic.

Stressful life events are significant risk factors for depression, and increases in depressive symptoms have been observed during the COVID-19 pandemic. The aim of this study is to explore the neural makers for individuals' depression during COVID-19, using connectome-based predictive modeling (CPM). Then we tested whether these neural markers could be used to identify groups at high/low risk for depression with a longitudinal dataset. The results suggested that the high-risk group demonstrated a higher level and increment of depression during the pandemic, as compared to the low-risk group. Furthermore, a support vector machine (SVM) algorithm was used to discriminate major depression disorder patients and healthy controls, using neural features defined by CPM. The results confirmed the CPM's ability for capturing the depression-related patterns with individuals' resting-state functional connectivity signature. The exploration for the anatomy of these functional connectivity features emphasized the role of an emotion-regulation circuit and an interoception circuit in the neuropathology of depression. In summary, the present study augments current understanding of potential pathological mechanisms underlying depression during an acute and unpredictable life-threatening event and suggests that resting-state functional connectivity may provide potential effective neural markers for identifying susceptible populations. (PsycInfo Database Record (c) 2022 APA, all rights reserved).